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About this course

Over the past decade emerging technologies, paired with massive changes in regulations, have driven an unprecedented transformation of finance around the world. This process is happening more rapidly in China and Asia than anywhere else. This course is designed to explore FinTech fundamentals and help make sense of this wave of change as it happens.

New players such as start-ups and technology firms are challenging traditional players in finance, bringing democratization, inclusion and disruption. Companies engaged in social media, e-commerce, and telecommunications, as well as, companies and start-ups with large customer data pools, creative energies, and technical capacities, have brought competition to the existing financial infrastructure and are remaking the industry.

These transformations have not only created challenges but also unprecedented opportunities, building synergies with new business and regulatory models, particularly in emerging markets and developing countries. To meet these changes, 21st-century professionals and students must be equipped with up-to-date knowledge of the industry and its incredible evolution. This course – designed by HKU with the support of SuperCharger and the Centre for Finance, Technology and Education – is designed to enable learners with the necessary tools to understand the complex interaction of finance, technology and regulation.

In this course, through a series of video lectures, case studies, and assessments you will explore the major areas of FinTech including, beginning with What is FinTech before turning to Money, Payment and Emerging Technologies, Digital Finance and Alternative Finance, FinTech Regulation and RegTech, Data and Security, and the Future of Data Driven Finance, as well as, the core technologies driving FinTech including Blockchain, AI and Big Data. These will set the stage for understanding the FinTech landscape and ecosystem and grappling with the potential direction of future change.

What you’ll learn

Skip What you’ll learn

• The major areas in FinTech, includingMoney and Payment,Digital Finance and Alternative Finance
• Major technological trends, including cryptocurrencies, Blockchain, AI and Big Data
• FinTech Regulation and RegTech
• The fundamental role of Data and Security in data-driven finance
• Businessand regulatory implications of technology for the financial industry
• How regulations and RegTech are applied
• Ways to analyse and evaluate what is driving technology innovation in Finance
• Hownew technology impacts economies, markets, companies,and individuals

Syllabus

Module 1 What is FinTech?

• FinTech Transformation
• FinTech Evolution 1.0: Infrastructure
• FinTech Evolution 2.0: Banks
• FinTech Evolution 3.0 & 3.5: Startups and Emerging Markets
• Industry Showcase: Collaboration between Financial Institutions and Startups
• FinTech Typology
• Emerging Economics: Opportunities and Challenges
• From too-Small-To-Care to Too-Big-To-Fail
• Introduction to Regulation
• Industry Showcase: The Future of RegTech and 6 Technologies Impacting It

Module 2 Payments, Cryptocurrencies and Blockchain

• Individual Payments
• Developing Countries and DFS: The Story of Mobile Money
• Developing Countries and DFS: Regulation of Mobile Money
• RTGS Systems
• The ABCDs of Alternative Finance
• Building a New stack
• Cryptocurrencies
• Industry Showcase : Legal and Regulatory Implications of Cryptocurrencies
• What is Blockchain?
• Industry Showcase: The Benefits from New Payment Stacks (Applications of Ripple)

Module 3 Digital Finance and Alternative Finance

• A Brief History of Financial Innovation
• Digitization of Financial Services
• FinTech & Funds
• Industry Showcase: How AI is Transforming the Future of FinTech
• Industry Showcase: Ensuring Compliance from the Start: Suitability and Funds
• Crowdfunding – Regards, Charity and Equity
• P2P and Marketplace Lending
• The Rise of Chinese TechFins – New Models and New Products
• What is an ICO?

Module 4 FinTech Regulation and RegTech

• FinTech Regulations
• Evolution of RegTech
• RegTech Ecosystem: Financial Institutions
• RegTech Ecosystem: Startups
• RegTech Startups: Challenges
• RegTech Ecosystem: Regulators
• Industry Showcase: Use Case of AI in Smart Regulation and Fraud Detection
• Regulatory Sandboxes
• Smart Regulation
• Redesigning Better Financial Infrastructure

Module 5 Data & TechFin

• History of Data Regulation
• Data in Financial Services
• Industry Showcase : Application of Data Analytics in Finance
• European Big-Bang: PSD2 / GDPR / Mifid2
• Industry Showcase : PSD2: Open Banking API Will Help Startups
• Industry Showcase : Methods of Data Protection: GDPR Compliance and Personal Privacy
• Digital Identity
• Change in mindset: Regulation 1.0 to 2.0 (KYC to KYD)
• AI & Governance
• New Challenges of AI and Machine Learning
• Data, Metadata and Differential Privacy
• Data is the New Oil: Risk of Breach
• Industry Showcase : Cybersecurity Industry Update

Module 6 The Future of Data-Driven Finance

• Case Study 1: Revolut
• Case Study 2: Alibaba
• Case Study 3: Aadhaar
• Case Study 4: Credit Karma
• Case Study 5: Digibank
• Conclusion to Case Studies
• FinTech Big Trends – Looking Forward

Welcome and Course Administration

Welcome to Introduction of FinTech

1. FinTech involves the use of technology,
2. particularly information technology
3. to transform the way that finance is being done
4. in global markets, developing countries,
5. and across start-ups and tech firms.
6. 20 years ago, IBM spent $100 million
7. to build Deep Blue, the super computer
8. that beat Garry Kasparov.
9. This smartphone is more powerful than Deep Blue.
10. If you want to be in finance today,
11. you need to understand technology.
12. RegTech, short for regulatory technology
13. may be a game changer
14. as it will allow financial institutions
15. to deal with compliance and regulatory burdens,
16. not only more effectively,
17. but also more efficiently.
18. FinTech flourishes where the need is greatest.
19. China leads the world in many regards.
20. YueBao is a money market fund enabled by FinTech in China.
21. In 9 months, it became the fourth largest in the world.
22. Now 3 years later, it is the world’s largest.
23. FinTech has evolved over 3 eras,
24. from infrastructure to banks to start-ups,
25. entrepreneurs today are building the B2B solution
26. that will be powering the financial system tomorrow.
27. This course will be an illustration
28. of how this is happening today.
29. In the future, finance will be
30. about an experience, not a product.
31. That’s why it’s important for students today
32. to understand how the industry is changing
33. and that’s what this course will be about.

Course Outline and Syllabus

Introduction to FinTech Course  –  Course Outline

Introduction to FinTech is a six-week, six-module course. Each weekly module compiles 8-12 lesson units (or subsections). In addition to the main units of the lesson, there are also Industry Showcases highlighting examples and experiences. These include segments from the traditional financial services industry, startups, technology firms, and more.

The major learning activities within each lesson unit include: video discussions of major aspects, as well as continuous assessments in the form of Quick Check questions, Polling, and Word Cloud activities. In addition, there are a range of additional resources, including reports, studies, and useful links. There is a Conclusion Quiz at the end of each module to draw out the main messages.

Please click the link to view and download the Course Syllabus.

Please click the link to view and download the Course Syllabus.

Introduction to FinTech Course Syllabus 

Module 1 What is FinTech?

Welcome to Module 1

1.1 Module 1 Introduction

1. Welcome, my name is Douglas Arner
2. and this is an introduction to FinTech.
3. I am the Kerry Holdings Professor in Law
4. at the University of Hong Kong
5. and I have spent the past 25 years
6. studying the interaction
7. between finance, technology and regulation.
8. And in this course,
9. we are going to provide you
10. an introduction to the world of FinTech.
11. Financial technology transforming
12. the world of finance
13. and the wider world beyond
14. faster than we have ever seen before.
15. In this course,
16. I am joined with a group of my friends
17. from around the world,
18. Ross Buckley of the University of New South Wales in Australia,
19. Henri Arslanian of PwC,
20. Brian Tang of the Asia Capital Markets Institute,
21. Janos Barberis of SuperCharger
22. and Huy Nguyen Trieu of the Centre for Finance, Technology and Entrepreneurship.
23. In this course, we’re going to begin
24. by looking at the fundamental question.
25. What is FinTech?
26. And that is going to be module 1.
27. For module 2,
28. we’ll turn to the next question
29. which is money, payment
30. and the transformation of finance through technology,
31. looking at new things
32. like cryptocurrencies, Bitcoin, blockchain
33. as well as, mobile payments.
34. In module 3,
35. we’ll turn to the digitization of finance
36. and the development of new forms
37. of alternative finance, crowdfunding, ICOs,
38. new forms of lending and security settlement.
39. In module 4, we’ll turn to
40. some of the bigger challenges,
41. regulatory issues.
42. How do we balance the opportunities
43. and risks of FinTech
44. so that we can make not only FinTech better
45. but the financial system
46. and the wider economy?
47. In module 5, we’ll turn to
48. one of the biggest challenges
49. facing the world of finance today
50. and that is the interaction
51. between data and finance
52. and the emergence of an entirely new paradigm
53. of data-driven finance
54. which brings with it tremendous changes
55. but also tremendous risks.
56. And finally, in the last module,
57. module 6, we’ll look at
58. a number of case studies
59. to draw lessons from our experiences
60. and also look at
61. some of the big trends going forward.
62. So, we very much look forward to you joining this
63. in our journey across FinTech.
64. At the end of this course,
65. we very much hope you will have
66. an overall understanding of what is FinTech,
67. of some of the major technologies
68. that are driving FinTech transformation,
69. an understanding of what is happening
70. not only in developing markets
71. but in particular,
72. in exciting new emerging markets,
73. particularly in Asia.
74. And finally, that you will be able to
75. understand in your own life,
76. in your own career
77. how technology could continue
78. to transform finance in the future.

Module 1 Learning Objectives

Module 1 introduces the evolution, context, opportunities, and challenges of FinTech. It highlights to students that FinTech should be defined by the user of technology as opposed to simply the fact of using technology (the ‘who’, not the ‘what’) so as to better understand why this industry is growing ever more rapidly and what opportunities and risks it creates.

Key Learning Objectives:

• Understand how finance and technology have evolved and are transforming finance around the world.
• Discuss key interactions between finance and technology over time to better understand the developments which are taking place today and are likely to take place in the future.
• Consider the broad spectrum of the financial sector and the way that technology is changing it faster than ever before, particularly with the explosion of new entrants, including startups, tech firms and emerging markets.
• Consider both the opportunities as well as the potential risks of FinTech and the challenges it poses for policymakers.

1.2 FinTech Transformation

1. Hi there, very excited to be here.
2. My name is Henri Aslanian
3. and my passion and focus is the future
4. of the financial services industry.
5. And I’m very lucky to be able to
6. do this in my academic life
7. as an Adjunct Associate Professor
8. here at the University of Hong Kong,
9. where I teach the first
10. FinTech university course in Asia.
11. Also very lucky to be
12. doing this in my professional life
13. as the FinTech and RegTech leader
14. here for Hong Kong for PwC.
15. Very excited to be sharing about
16. the latest developments
17. going on in the broader FinTech space
18. throughout this course.
19. One question often pops up is that
20. how come FinTech became such a big reality?
21. What really caused the rise of FinTech?
22. Well it’s a very interesting question.
23. Traditionally… actually, as technology evolved
24. banks were pretty good at also
25. always keeping up with technology
26. and in many cases,
27. being some of the early adopters.
28. But all of this really changed
29. during the global financial crisis in 2008.
30. During that time,
31. banks and financial institutions
32. were busy dealing with regulations, compliance,
33. and other many regulatory enforcement situations
34. that were taking place.
35. Innovation became a very, very distant priority.
36. But at the same time,
37. some of the biggest game changing innovations
38. that took place
39. that have changed our lives took place.
40. Think about Uber, WhatsApp,
41. WeChat, or Airbnb,
42. and many others that really changed the way
43. customers ahead experience the services
44. they were receiving in many industries,
45. except financial services,
46. and this gap was created
47. between what financial institutions
48. were offering to their customers
49. and what customers came to expect.
50. And this gap is
51. what the FinTech industry wanted to tackle.
52. And the FinTech industry wanted to tackle
53. very many of the use cases;
54. that matched the pain points
55. that were in this industry.
56. However, it was not only the startups.
57. And actually what we realised
58. over the course of the years is actually
59. some of the biggest gamechanging
60. technological innovations took place
61. not only by FinTech startups
62. but by large technology firms.
63. Think about firms like
64. Amazon, or Tencent, or Ant Financial
65. and many others who have started now
66. looking at financial services.
67. And in the future
68. there’s actually a big chance that
69. some of the providers of financial services,
70. at least the interface
71. that clients will be using
72. may be these large technology firms.
73. So definitely an area to watch.
74. And what are some of the advantages
75. these large technology firms have
76. over some of these startups?
77. Not only do they have the funding,
78. they have the backing,
79. and the talent, and the pool, capital pool
80. to actually support these new businesses,
81. but to certain extent,
82. they have the trust of consumers.
83. Think about it,
84. if you’re happy to buy
85. all your daily necessities
86. on Amazon, or on Taobao,
87. wouldn’t you use them as well
88. to actually, you know,
89. buy insurance products?
90. If you’re actually using the Facebook Messenger
91. to actually talk to your friends and family
92. wouldn’t you use them as well to send money
93. to friends and family as well?
94. Well, as you can see,
95. it’s going to be a very interesting ecosystem
96. developing over the coming years
97. not only with FinTech,
98. but also by TechFin.
99. Definitely an area to watch.

1.3 FinTech Evolution 1.0: Infrastructure

1. Finance and technology
2. have been inextricably intertwined
3. since the very beginning.
4. If we look at the earliest days of finance
5. dating back thousands of years ago,
6. the initial impact of technology
7. was in the context of building systems
8. of keeping records of government finances
9. or payments for taxes
10. and agricultural production
11. or building facilities
12. and one of the first physical technologies
13. to develop was money
14. the simple coin
15. or thousands of years later,
16. not long after 1000 A.D.,
17. paper money.
18. Money is a form of technology
19. that allows us to physically handle
20. the ideas embedded in finance.
21. So, if we think about financial technology,
22. the history is very, very long indeed
23. and in addition to coins,
24. paper money, systems of writing
25. or accounting,
26. major points include the evolution
27. of the joint stock company
28. or the corporation,
29. forms of financing like banking,
30. or more recently, stocks, bonds,
31. things that we would call
32. securities or derivatives.
33. Derivatives are financial instruments
34. whose value derives
35. from some underlying financial instrument
36. but if we think of today’s fintech,
37. the modern period of fintech
38. and financial technology
39. begins around 150 years ago
40. and we generally mark the date as 1867.
41. Why 1867?
42. 1867 was the date of the establishment
43. of the first transatlantic telegraph cable.
44. That transatlantic telegraph cable
45. made instantaneous communication
46. between the major markets
47. of New York and London,
48. or London and Paris,
49. or even eventually several decades later,
50. Shanghai, or Hong Hong, and London possible.
51. This was the basic infrastructure
52. that underlies all of today’s
53. not only financial technology
54. but much of today’s communications
55. and media developments as well
56. and it’s somewhat ironic
57. that in the past five years
58. more undersea cable has been laid
59. than in the entire previous 150 years combined.
60. Why?
61. Because more physical cables are necessary
62. to handle the ever greater flows of data
63. speeding around the world
64. and underpinning
65. the development of finance.
66. Many would say
67. that the period from the 1860s
68. up to the start of the First World War
69. was a first period of
70. financial and economic globalisation
71. much like the past 30 years or so from today.
72. That period of
73. financial and economic globalisation
74. was underpinned by technological infrastructure
75. like the transatlantic telegraph cable
76. which in fact has been called
77. the Victorian internet.
78. Now, if we think about
79. technological developments
80. in financial services,
81. probably our next significant milestone
82. really comes during the Second War World.
83. During the Second World War,
84. significant effort spent particularly
85. in the context of developing codes
86. for secure communications
87. particularly of military and intelligence operations
88. as well as, significant efforts
89. to develop systems to break those codes
90. and it was this process of encoding
91. and breaking codes that led
92. to come of the groundbreaking thinking
93. in computer technology
94. and in fact,
95. eventually in artificial intelligence or AI
96. which is one of the most exciting developments
97. happening in financial technology today.
98. But it wasn’t until the period
99. after the Second War World
100. as the world economy is rebuilding
101. that we begin to see progressive development
102. of those early computer technologies
103. to eventually lay the ground work
104. for the sorts of fintech
105. and regtech developments
106. which we see today.

1.4 FinTech Evolution 2.0: Banks

1. The first era of modern fintech,
2. fintech 1.0 was about
3. building the underlying infrastructure
4. that supports today’s global financial markets.
5. The second major era
6. of the modern fintech evolution,
7. what we call fintech 2.0,
8. started in 1967.
9. 1967 marks two very important dates
10. in the evolution of finance
11. and also technology.
12. The first, is the establishment of the first ATM,
13. the first automated teller machine
14. by Barclays Bank in the UK.
15. That automated teller machine allowed,
16. over the next several decades,
17. a transformation in the relationship
18. that people had with money and with finance.
19. The second, just as significant,
20. is the launch of the first handheld calculator
21. by Texas Instruments.
22. The first handheld calculator
23. was transformational in the way
24. that finance, on a day-to-day basis operated
25. And, of course, the handheld calculator
26. is also the ancestor of today’s smartphone,
27. perhaps the transformative technology
28. in the context of fintech.
29. 1967 thus marks a period where we begin
30. to see a process of digitization.
31. Digitization is taking processes and systems,
32. which were formerly analogue,
33. analogue things like handwriting
34. or physical calculation of money,
35. and digitising them, transforming them
36. into a digital environment.
37. And from these early beginnings,
38. we can see in global financial markets,
39. three very significant trends
40. that come together
41. in today’s global financial markets.
42. The first, the late 1960s and early 1970s,
43. the establishment of a series of
44. domestic and international
45. electronic payment systems.
46. These payment systems allow
47. large value payments
48. to take place today on a real time basis,
49. which underpins massive volumes
50. of transactions around the world.
51. From across border standpoint,
52. perhaps the most significant of these
53. is an organisation,
54. which we’ll turn to in module two,
55. called SWIFT.
56. SWIFT is an organisation,
57. which provides protocols
58. to enable communications
59. between domestic digital payment systems.
60. In addition to these developments in payments,
61. we also see, in 1971,
62. the establishment of NASDAQ.
63. NASDAQ was the world’s 1st electronic stock exchange.
64. Today, there are almost no stock exchanges
65. or other financial exchanges,
66. which are not electronic.
67. Basically, in the context of both payments,
68. as well as, in stock and other securities markets,
69. the process of digitization,
70. which began in the late ’60s and early 1970s,
71. has fundamentally transformed
72. the way these markets work,
73. so much so that today, it is very difficult
74. to find a human being actually trading securities
75. with another human being in stock markets.
76. At another level, if we think of
77. today’s global foreign exchange markets,
78. markets in which people buy one currency,
79. like the dollar and sell another,
80. like the yen or the RMB,
81. these markets today
82. do approximately 5.5 trillion dollars
83. a day, every day of the year in transactions
84. and almost none of this
85. takes place in the form of cash.
86. It is almost entirely digital book entries
87. taking place between the computer systems
88. of major financial institutions.
89. This process, however,
90. is one that was in fact
91. well established by the late 1980s.
92. A major market crash occurred in 1987.
93. That market crash today,
94. our best explanation,
95. is what is called programme trading.
96. Programme trading involves preset computerised
97. buy and sell orders,
98. and so when stock prices
99. drop to a certain level,
100. this would trigger automatic selling
101. by computer programmes,
102. which would then trigger more price drops,
103. triggering more sales and eventually resulting
104. in our first major coordinated
105. global market crash.
106. Now, across the 1980s,
107. we began with the origins of online banking
108. in parallel to the emergence of the internet
109. and certainly by
110. the beginning of the 21st century,
111. a number of banks already had
112. over a million plus online banking customers,
113. but today, we are waiting to see
114. what will be the first financial institution
115. with over a billion online financial services customers.
116. If we think in terms of developments,
117. we can think that 1999 marked a previous high.
118. 1999 was the internet bubble,
119. the dotcom crash
120. and it highlights something
121. that’s very important
122. in the context of today’s fintech.
123. As human beings,
124. we tend to overestimate the short term impact
125. of new technologies
126. and underestimate the long term impact
127. of new technologies.
128. After all, if we think to
129. some of the 1999 internet bubble companies,
130. companies like Amazon or Google.
131. Certainly, at that time,
132. we overestimated their short term impact,
133. but looking back almost 20 years,
134. almost no one would have imagined
135. how significant
136. Google, Amazon, and other similar sorts
137. of technology companies have become.
138. This period of building the digitization
139. of the financial system
140. hit a major turning point
141. in 2008 with the global financial crisis.

1.5 FinTech Evolution 3.0 & 3.5: Startups & Emerging Markets

1. Fintech 3.0 and 3.5.
2. 2008 marks a major turning point
3. in the evolution of fintech.
4. The global financial crisis of 2008
5. started in the subprime real estate markets of the United States
6. and spread throughout the global financial system
7. to major developed markets around the world,
8. as well as impacting developing
9. and emerging market countries
10. through the economic slowdown
11. that from the standpoint of trade,
12. was just as severe as the slowdown
13. that we saw in the 1930s
14. in the aftermath of the 1929 crisis.
15. From the standpoint of fintech,
16. the global financial crisis had a number of
17. very important features.
18. The first, was that it resulted in large numbers
19. of job losses in the financial sector,
20. particularly amongst younger people.
21. This drove many of those people
22. who had been looking forward
23. to very good careers
24. in the context of financial sector
25. to seek to pursue other opportunities.
26. And it’s certainly the case today
27. that if one meets someone
28. who has just left a large financial institution,
29. it is very frequently the case
30. that they have gone to
31. start a new fintech startup company.
32. So, first impact of the global financial crisis,
33. job losses
34. forcing people in the financial sector
35. to look for new opportunities.
36. The second was that
37. a reaction to the global financial crisis
38. involved large numbers of
39. regulatory changes designed to prohibit
40. or prevent the sorts of problems
41. that emerged in 2008
42. from happening again.
43. These massive amounts of regulatory changes
44. resulted in a dramatic decrease in profitability
45. of financial institutions
46. as well as massive increases
47. in compliance and regulatory cost
48. for those institutions.
49. In many ways, the only way
50. that these new requirements
51. could be addressed was via technology.
52. The third impact of the global financial crisis
53. really was to speed up something,
54. which was already happening,
55. which was a loss or a drop in trust
56. in traditional financial institutions.
57. Since 2008,
58. certainly amongst people under 35,
59. it is now generally recognised
60. that they would be more comfortable
61. doing financial transactions
62. with a technology company,
63. whether Facebook or Alibaba
64. or Tencent or Google
65. than with a traditional financial institution
66. like HSBC, Barclays or Bank of America.
67. These features together
68. along with one other important point
69. and that important point
70. is marked by 2007.
71. 2007 was the launch of the first iPhone.
72. The iPhone, of course,
73. has now sold over a billion
74. around the world and the iPhone
75. and other forms of smartphones
76. combined with other factors resulting from
77. the global financial crisis set the stage
78. for the transformation in fintech,
79. which we’re seeing today.
80. Now, if we think about this combination,
81. the combination has led to
82. an explosion in startups.
83. One very high profile startup
84. is perhaps one of the most unique
85. and one that we’ll turn to in module two,
86. Bitcoin and other forms of cryptocurrency
87. based on blockchain
88. or distributed ledger technologies.
89. Others have involved various forms
90. of alternative finance like P2P lending, peer-to-peer lending,
91. or forms of crowdfunding,
92. a range of different payments.
93. But in fact,
94. startups in the context of fintech
95. are even not new.
96. If we think back to 1999,
97. one of those internet bubble startups
98. was a company called PayPal.
99. PayPal today is one of the world’s
100. most significant payment services providers
101. along with traditional firms
102. like Visa or MasterCard
103. or even before that, Bloomberg.
104. Bloomberg today
105. is the world’s most valuable
106. private information services firm.
107. Bloomberg founded by
108. the former mayor of New York City,
109. Michael Bloomberg, started in 1981.
110. Bloomberg started in technology
111. in an investment bank called Salomon Brothers.
112. The technology that he developed
113. was a secure communication service
114. that still underlies the vast majority
115. of cross border transactions around the world.
116. So, this period of fintech 3.0,
117. the explosion in startups
118. since the global financial crisis is new
119. in terms of numbers, volume, transformative potential
120. but we have seen fintech startups before.
121. The other area where the transformation
122. has been perhaps even more dramatic
123. is in the context of developing countries
124. and emerging markets.
125. 2007 marks the launch of M-Pesa.
126. M-Pesa is a mobile phone-based payment system,
127. which transformed access to finance
128. of a large portion of the population of Kenya
129. and it’s when we combine these ideas
130. of mobile payment with the smartphone
131. that we see the transformation
132. of financial services
133. that is taking place particularly in China
134. with Alibaba, Tencent and others.

Industry Showcase: Collaboration between Financial Institutions and Startups (The FinTech Association of Hong Kong)

1. Collaboration plays a very important role
2. in the way FinTech has developed in the last few years,
3. in particular, in Hong Kong.
4. Initially, we saw a lot of work done by FinTechs
5. trying to do it on themselves,
6. looking to disrupt financial services
7. and also the banks at one stage,
8. looking to be more guarded
9. about how they use technology,
10. especially FinTechs with them.
11. But as the reality dawned on the markets,
12. such as Hong Kong,
13. which is largely business-to-business,
14. people realised that
15. there needs to be a lot of collaboration.
16. Banks need a longer time for transformation,
17. but they also need to be able to be more agile
18. with regards to adopting new technologies,
19. and for FinTechs,
20. they don’t have a long runway,
21. and secondly, they also aren’t able
22. to have the required capital
23. if they want to face off with banks,
24. in particular,
25. where larger creations are impacted.
26. So, it’s quite important that
27. collaboration is done in this field.
28. Secondly, what we are seeing now is
29. banks are not just collaborating with FinTechs,
30. but they’re going a step ahead
31. and some of them are acquiring them
32. through strategic investments.
33. So, they’ll have a large investment,
34. and these FinTechs are solving
35. just the banks’ need for strategy
36. in Hong Kong or across the region.
37. Three, very importantly,
38. is cross-regional collaboration.
39. So, you see certain strands of different FinTechs
40. in different regions,
41. and what banks are trying to do
42. is try to find these FinTechs here.
43. If you have a FinTech which is very strong
44. in the B2B section of AI in Hong Kong,
45. they look to use that from Hong Kong,
46. and they might use another
47. coming in from Singapore.
48. So, it becomes very important for them
49. to have teams that can collaborate this.
50. Lastly, it is very important
51. that compliance plays a role
52. in making this effort of collaboration
53. between banks and FinTechs faster.
54. Onboarding is a very important factor
55. and of compliance,
56. time can be shortened.
57. It gives the start-ups
58. more time to present a POC
59. and be onboarded with the banks.
60. So, collaboration plays an important role,
61. and we should be aware that
62. banking is going to change
63. not by disruption,
64. but through collaboration.

1.6 FinTech Typology

1. As we’ve seen,
2. the evolution of fintech has impacted
3. every aspect of finance everywhere in the world
4. and I think
5. from the standpoint of looking at fintech,
6. it makes sense to look at
7. the main areas where fintech is focused on
8. in the literature, as well as in business.
9. And those can be summarised
10. as finance and investment,
11. operations and risk management,
12. payments and infrastructure,
13. data security and monetization,
14. and technology in the customer interface.
15. And in each of these areas,
16. technology has both created new areas,
17. as well as transformed
18. existing businesses and processes.
19. If we think of finance and investment,
20. often we’ll think of forms of alternative financing
21. like crowdfunding or P2P lending,
22. or most recently, ICOs.
23. ICOs are initial coin offerings
24. and are a topic that we’ll turn back to in module 3
25. but as we saw in discussing the evolution,
26. technology has not only
27. created new forms of financing
28. but via digitization,
29. it has also transformed
30. traditional forms of financing.
31. Think of stock market trading
32. and the fact that today,
33. in the world’s high frequency algorithmic stock markets,
34. that hundreds of thousands of transactions take place
35. every single second
36. of every day that the markets are open.
37. And this simply cannot happen without technology.
38. And of course,
39. areas like hedge funds and investment funds
40. are some of the biggest spenders on technology,
41. a constant arms race to gain a slight edge
42. in trading and investment
43. in order to drive profitability.
44. So, fintech has transformed
45. both new forms of finance
46. but it has also changed
47. traditional forms of finance.
48. If we look at operations
49. and risk management, pre-crisis,
50. much of operations and risk management
51. in the financial services industry
52. focused on quantitative risk modelling techniques
53. such as VAR or value at risk systems,
54. which depended upon sophisticated computer systems
55. developed across the 1990s
56. but in many ways,
57. the 2008 crisis showed the limitations
58. of many of these approaches.
59. Since 2008, financial institutions,
60. as well as regulators,
61. have continued to be amongst the largest spenders
62. of any industry in the world on IT,
63. focusing in particular,
64. on new regulatory requirements,
65. as well as risk management systems
66. but also competition from new entrants
67. whether those new entrants are startups,
68. or they are established technology,
69. media, or communications firms.
70. Payments and infrastructure is a very high profile area.
71. For many of us, electronic payments
72. will be one of our primary areas
73. of direct interaction with fintech.
74. Most of us have made payments
75. over the internet,
76. or using our mobile phone,
77. or using a QR code;
78. simple techniques,
79. which allow instantaneous payments
80. both in electronic form,
81. as well as increasingly using a variety of forms
82. of mobile and smart technology.
83. But in addition to this,
84. these 5.5 trillion dollar a day
85. global currency markets take place
86. in a completely digitised environment
87. and new technologies like blockchain,
88. or distributed ledger technology,
89. which we’ll turn to in module 2,
90. as well as in module 6,
91. are transforming
92. traditional large value digital payments.
93. All of this digitization
94. brings with it both opportunities,
95. as well as risks.
96. On the opportunity side,
97. digitization of ever increasing sources
98. and forms of data
99. has allowed a new process of datafication.
100. Datafication is the application of
101. sophisticated analytics systems,
102. big data, or artificial intelligence and the like,
103. in order to analyse large volumes of data
104. to come up with new approaches or new ways
105. to monetize those sources of data
106. but at the same time,
107. with data increasingly in digital-only form,
108. risks of security continue to increase.
109. If everything is digitised,
110. the risk of hacking,
111. the risks of cybersecurity
112. have moved from being a business risk
113. to a financial stability risk
114. to a national security risk today.
115. And these are areas
116. that are driving both technology,
117. as well as new entrants, new businesses,
118. new opportunities, and of course,
119. the customer interface.
120. How we interact with these forms of finance
121. provides not only
122. greater opportunities for individuals
123. in terms of convenience and access
124. but also, new business technologies.

1.7 Emerging Economics: Opportunities and Challenges

1. As we’ve seen,
2. technology over the past decade
3. has transformed finance around the world.
4. It brings with it massive opportunities,
5. and those opportunities
6. are perhaps nowhere greater than
7. in developing countries and emerging markets.
8. If we think of the story of Africa,
9. of M-Pesa In Kenya,
10. and mobile financial services,
11. the impact of mobile financial services
12. through old-style mobile phones
13. has been very significant.
14. But, there’s a big limitation
15. in terms of what you can do
16. with an old-style mobile phone,
17. compared to what can be done
18. with a modern smartphone.
19. The power of a modern smartphone
20. dwarfs the power
21. of a room-sized IBM mainframe from the 1970s.
22. The computing power that
23. we can hold in our hands today
24. is unprecedented in the history of the world,
25. and from the standpoint of
26. what one can do in finance
27. with that technology,
28. the transformation which is
29. already taking place in Asia
30. is nothing short of amazing.
31. Why?
32. Because throughout much of Asia,
33. we have two very significant features.
34. One, very often, high penetration rates,
35. high ownership rates of smartphones,
36. combined with availability of broadband internet access.
37. This combination of smartphones
38. with broadband internet access
39. combines with a feature of
40. many emerging markets around the world,
41. which is often inefficient
42. traditional banking and financial systems.
43. And this combination allows emerging markets
44. to leapfrog a hundred years of developments
45. which took place in western markets
46. in a short period of a few years.
47. And perhaps the best example we have
48. seen is in the context of China.
49. Today, if we think of the major internet
50. and e-commerce firms in China,
51. firms like Alibaba, Tencent, Baidu,
52. or even traditional financial institutions like Ping An,
53. today, the numbers of customers
54. using their financial services
55. are absolutely staggering.
56. It has transformed
57. the interaction of the individual
58. with technology in finance,
59. and at the same time
60. is transforming the financial systems
61. and the economies of emerging markets.
62. One that we’ll turn back to in Module 4,
63. we’ve seen in the context of India.
64. Using a variety of
65. technological infrastructure design elements
66. to support expansion of finance
67. to literally hundreds of millions of people
68. who did not previously have access
69. to financial services.
70. This is perhaps the most important story
71. that we’ve ever seen
72. in the context of financial inclusion,
73. economic growth,
74. and financial transformation.
75. And it’s exciting
76. because many of the developments
77. are being led for the first time in Asia.
78. At the same time,
79. these tremendous changes and opportunities
80. also bring with them new risks.
81. An idea that things can move faster
82. than we’ve ever seen before.
83. And if we look at the things
84. that have changed in fintech,
85. it is the combination of new entrants,
86. startups and technology companies
87. with speed of change
88. that is driving so much of the opportunities
89. and the transformations.
90. But, this combination of
91. new entrants and speed of technology
92. allows something else to happen as well,
93. and that is for risks
94. to grow ever more rapidly
95. than they have ever done before.
96. In an example,
97. a new banking startup
98. launched by a technology company
99. can acquire,
100. in a period of a weekend, millions of customers,
101. taking in one weekend
102. the amount that would have taken
103. in a traditional developed market decades
104. for a financial institution to achieve.
105. This is the risk that we call
106. moving from too small to care
107. to too big to fail,
108. and it can now occur in record time.

1.8 From Too-Small-To-Care to Too-Big-To-Fail

1. We are now going to be
2. talking about an important notion.
3. The notion of going from too small to care
4. to too big to fail.
5. This notion is important,
6. because it fits into
7. what you have been learning so far
8. in our first module.
9. Financial technology
10. is a 150-year-old industry
11. that has been divided
12. across 3 different eras.
13. The first era was a 100 years old,
14. the second era was 40 years old,
15. and the third era,
16. in which we are today,
17. will be about a decade old.
18. Now what you start noticing is that
19. each of these era
20. are shorter than the previous one.
21. And what this means,
22. is that technology is changing faster,
23. and is penetrating into the public
24. at a faster rate than ever before.
25. And that’s something that
26. you can actually notice
27. from your own perspective.
28. Let’s take the phone, for example.
29. It took many decades for land lines
30. to reach a million customers in the US.
31. However, it only took a few years
32. for mobile phones
33. to reach the same penetration
34. in that country.
35. Now let’s bring that to finance
36. and let’s think about banks.
37. Acquiring half a million customers
38. is a very big feet.
39. But KakaoTalk
40. has been able to do that in only 2 days.
41. Now if you take challenger banks
42. or regular banks,
43. it would typically take them many years
44. for them to acquire
45. the same number of customers.
46. Finally, I can also give you
47. the example of Bitcoin.
48. Most of you must have heard of Bitcoin,
49. if not already owned some Bitcoins.
50. And here the example is very clear.
51. As an asset class,
52. Bitcoin is becoming more valuable
53. faster than any other asset classes
54. that previously have led to a bubble.
55. What Bitcoin has done in only one year,
56. it took many more years
57. for other classes to do.
58. Therefore, those three examples
59. are an illustration
60. that technology is changing
61. more and more rapidly,
62. and therefore regulators
63. need to adapt themselves.
64. Let me show you a graph.
65. On the Y-axis,
66. you have the size of a company,
67. and on the X-axis,
68. you have the time it takes
69. for that company to grow.
70. Now, normally what we are used to understand,
71. is the notion of organic growth.
72. You will grow
73. because of the results of your business,
74. and every now and then,
75. you may grow from an acquisition.
76. And financial institutions that you may know,
77. such as tier one players like Citi, HSBC, etc.,
78. have grown as financial institution
79. over the last 100 plus years.
80. And therefore,
81. their path of growth is very predictable.
82. For regulators, that’s actually very useful,
83. because regulators don’t necessarily always regulate
84. and enforce action
85. against certain companies.
86. Indeed, what you will see now
87. on the X-axis,
88. is that you go from too small to care,
89. too large to ignore, to too big to fail.
90. What this means is that
91. if you are between too small to care
92. and too large to ignore,
93. regulators may or may not,
94. at their own discretion,
95. choose to enforce an action against you,
96. if you are breaching a rule.
97. The reason of that discretion
98. is because not everything
99. is worth suing for.
100. If you are only having
101. one or two consumers that you are hurting,
102. this is not worth the regulator’s time,
103. compared to a breach
104. that would impact over a million persons.
105. However, the second problem is
106. companies that become too big to fail.
107. The notion of too big to fail
108. is deeply rooted
109. into the financial crisis,
110. in the same way that the financial crisis
111. has led to the emergence of FinTech.
112. But in a similar fashion,
113. the emergence of mobile phone
114. has also favorized the emergence of FinTech,
115. and with it,
116. the mobile phone is a distribution channel
117. for financial technology companies.
118. Because now financial technology companies
119. can use that infrastructure
120. to more quickly reach you
121. as a consumer,
122. they can go to too small to care
123. to too big to fail overnight,
124. creating a regulatory blind spot for regulators.
125. This is the example that we take,
126. for example, in China with Yu’e Bao.
127. Yu’e Bao went from
128. zero to 90 billion US dollar
129. of assets under management
130. in only nine months.
131. They did in nine months
132. what it took over seven decades
133. for large tier-one asset managers to achieve.
134. Therefore, regulatory sandboxes
135. are one of the first tools for regulators
136. to resolve the risk created from startups
137. that go from too small to care to big to fail,
138. but that’s only the first step.
139. The second step will be
140. about building smart regulation
141. on top of regulatory sandboxes,
142. and we will cover that topic
143. in the RegTech module of this course.

1.9: Introduction to Regulation

1. Fintech is the intersection
2. of finance, technology, and regulation.
3. Financial services
4. even before the 2008 global financial crisis
5. was already one of the world’s
6. most heavily regulated industries.
7. And as a result,
8. when we think about fintech,
9. we have to also think about
10. regulation and the environment
11. in which finance and technology operate.
12. And fintech,
13. because of the changes in new entrants
14. as well as,
15. speed of technological development
16. poses major challenges for policy makers
17. in determining
18. how best to regulate markets
19. in order to best achieve the objectives,
20. the opportunities of financial inclusion,
21. of democratisation of finance,
22. of financial transformation,
23. while at the same time,
24. minimising the risks
25. of both financial fraud, misconduct,
26. as well as, financial crises.
27. And if we think back
28. to before the global financial crisis,
29. prior to the global financial crisis,
30. regulators and policymakers
31. tended to have a very positive attitude
32. towards financial innovation.
33. There’s a famous quote from Paul Volcker,
34. former Chairman of the U.S. Federal Reserve,
35. where he says that,
36. “the only important financial innovation
37. that he had seen in his lifetime was the ATM machine.”
38. Why?
39. The ATM machine fundamentally improved
40. people’s day-to-day lives,
41. and this was in contrast
42. to some of the financial innovations that we saw
43. prior to the global financial crisis,
44. many of which were central
45. to that crisis happening.
46. Things like credit derivatives,
47. or credit default obligations
48. or asset backed securities,
49. all of which were financial innovations,
50. but also innovations
51. which brought new risks.
52. Because of the global financial crisis,
53. for the past 10 years,
54. regulators and policymakers around the world
55. have taken a very cautious approach
56. to financial services regulation,
57. focusing on building
58. new costly regulatory frameworks
59. to prevent crises,
60. to prevent misconduct,
61. to protect customers,
62. but at the same time,
63. triggering developments in fintech,
64. but also making innovation
65. more challenging and more difficult.
66. And so, over the past several years,
67. as regulators have become more comfortable
68. with the opportunities
69. and potential transformative developments
70. taking place in fintech,
71. they have also become more friendly
72. from the standpoint of regulation.
73. But from the standpoint of regulation,
74. as we’ll see throughout the rest of the course,
75. there’s a continual process
76. of balancing objectives
77. like protecting consumers,
78. protecting the safety and soundness
79. of the financial sector,
80. protecting against financial crises
81. with objectives of financial inclusion,
82. competition, innovation, and development.
83. And it is this regulatory environment that
84. much of fintech takes place in today.

The Future of RegTech and 6 Technologies Impacting It (by Thomson Reuters)

1. Hello. My name is Julia Walker.
2. I’m the head of Market Development
3. for Regulatory Technology across Asia-Pacific.
4. So, what is RegTech?
5. Well, I like to think about RegTech
6. being FinTech’s best friend,
7. or at least the more sensible better half.
8. Perhaps we can think about it this way:
9. if FinTech is the rock star,
10. RegTech is the band member
11. happy to hang out in the background.
12. However, RegTech has more recently started
13. to take center-stage,
14. usually increasing regulatory challenges
15. in the financial sector,
16. and the need to apply technology to solve them.
17. As you’ll see in this module,
18. the future of RegTech
19. is one of positive financial innovation,
20. as well of benefits for financial regulation.
21. It’s the combination of both opening the door
22. for the automation of regulation.
23. In this module, we will show
24. six new emerging technologies,
25. and how these will redefine the future of RegTech.
26. In module one, we provided you with a macro-trend
27. of increased regulatory activity
28. and enforcement since 2008.
29. However now I wanted to help you
30. with three simple illustrations
31. to grasp the complexity behind regulatory adherence.
32. As you can see in this graph, regulation is complex,
33. voluminous and interconnected.
34. When you understand that large tier one universal banks
35. operate in over 60 jurisdictions,
36. it’s easier to picture the difficulty
37. to comply globally.
38. Especially with new rules
39. having cross-jurisdictional affect such as GDPR.
40. In addition, compliant obligations
41. are always in a state of flux.
42. Regulators’ proactivity around the world
43. can be seen by the number of regulatory changes.
44. Regulatory alerts increased from 8,000 in 2008
45. to 56,000 in 2017,
46. an average of 216 alerts per day.
47. The global financial crisis of 2008
48. highlighted the systemic risk
49. within the global financial system,
50. serious conduct issues and a push to
51. tighten anti-money laundering controls.
52. Regulators in the United States
53. and Europe have imposed 342 billion in fines
54. on banks for misconduct,
55. including the violation of anti-money laundering rules,
56. and it is likely to top 400 billion by 2020.
57. And it’s not just the fines causing headaches,
58. conduct issues are also leading to revenue loss.
59. A Hong Kong-based financial services company
60. has estimated that bad behaviour
61. has erased 850 billion in profits
62. for the top 50 global banks.
63. In New York, a 185 million dollar fine was issued
64. for failing to protect client assets,
65. and it’s just not finances getting fined.
66. RegTech can also help other industries
67. especially when we know that regulatory enforcement
68. is on the rise for corporates.
69. 18 billion has been imposed to a car manufacturer,
70. and 60 million to
71. a Japanese-based electronics company.
72. On the backdrop of
73. these macro changes in cost pressures
74. is a number of new emerging technologies.
75. In our discussion today,
76. we want to look at some of the underlying trends
77. that will shape the global financial system
78. over the next 10 to 20 years,
79. and remove the pain points associated
80. with compliance obligations.
81. Blockchain.
82. Immutable, consensus driven,
83. transparent, distributed, work flow enabled,
84. and trust being replaced with truth.
85. Blockchain could potentially
86. power the identity market place
87. and has the potential to modernise
88. or even replace existing trading,
89. clearing, and settlement operations.
90. Smart contracts and smart oracles will exist
91. to enable customers to use blockchain
92. to streamline post-trade life-cycle,
93. and other capital market use cases.
94. Digitised assets with blockchain
95. as a potential new way to digitise
96. and maintain records for government
97. and other relevant industries.
98. Cognitive computing and artificial intelligence.
99. We are just at the beginning of a revolution
100. that will touch every business,
101. and every life on this planet.
102. The data volumes are exploding.
103. More data has been created
104. in the past two years
105. than in the entire previous history of the human race.
106. At the moment however,
107. less than 0.5% of all data is ever analysed and used.
108. As this quantum of data grows
109. the need for standards,
110. structure and integration does also.
111. The need for smart machines
112. to synthesise and make sense of data
113. and support the human cognitive
114. and decision-making process is therefore paramount.
115. The internet of things.
116. Electronic sensors are showing up
117. in devices all around the world.
118. We now have self-driving cars that can navigate
119. their way through traffic.
120. Even regular cars track with AI
121. in how fast they’re going.
122. But how can this enormous world of information
123. generated by machines and sensors
124. be used for better financial investment,
125. trading decisions, and risk management?
126. How can this data be aggregated
127. and anonymized to protect individual privacy
128. while retaining its most useful, actual information?
129. Customers must have the confidence that
130. their data is collected, stored, and used
131. in a manner that benefits them,
132. and does not jeopardise their privacy.
133. Open source and API economy.
134. APIs are fueling
135. the customer-driven platform revolution.
136. They’re becoming a primary customer interface
137. for technology-driven products and services,
138. and a key channel for driving revenue
139. and brand engagement.
140. APIs are a set of rules
141. that govern how one type
142. of computer software communicates with another.
143. They enable bank customers to
144. share their personal financial information
145. with third parties to generate opportunities
146. for better deals on financial products
147. and to use transaction data to access
148. and compare products easily.
149. From the bank’s perspective,
150. the technology enables them to remain competitive
151. by providing them with opportunities
152. to provide improved customer-friendly services
153. and reach out to untapped markets.
154. The Cloud.
155. Everyone is looking at the Cloud,
156. and for good reason.
157. Cloud computing eliminates the capital expenditure
158. of buying hardware and software and setting up
159. and running on-site data centres.
160. Big data.
161. Firms need help organising
162. and collecting enterprise and third party data
163. to derive new insights.
164. Data tagging allows investors, regulators
165. and market participants
166. to organise and analyse massive amounts of data
167. and information more efficiently
168. by associating pieces of information
169. with keyword tags.
170. The rapid changes and maturation of technologies
171. from big data management to advanced analytics
172. to machine learning,
173. to artificial intelligence,
174. and robotic process automation are
175. fueling product innovation
176. and providing customers potential opportunities
177. to further transform operations.
178. So there you go,
179. six of the key technologies that you need to be aware of
180. as we look at the future of RegTech
181. but before I leave you,
182. I wanted to highlight the three critical considerations
183. to harness the value
184. of innovation brought by RegTech.
185. First, RegTech solutions need to be powered
186. by trusted, structured and unstructured data
187. that also has data mastering capability
188. for effective integration with existing solutions.
189. Second, advanced analytics
190. and artificial intelligence
191. will play a key role.
192. And lastly, digital identity.
193. Digital identity is a foundation
194. to all RegTech solutions
195. because identity of individual, organisation,
196. or a physical asset are atomic in governance,
197. regulatory compliance
198. and risk-management solutions.
199. We will cover this in more detail in module five.

Additional Resource Insights

References and Suggestions for Further Reading:

• The evolution of FinTech: A new post-crisis paradigm? (In-depth study – Arner, Barberis, Buckley)

• Big banks on notice as tech groups ramp up pressure (News article – FT)

• Bank of the Future (Industry report – Citi Bank)

Module 2 Payment, Cryptocurrencies and Blockchain

Welcome to Module 2

2.1 Module 2 Introduction

1. Welcome back to Hong Kong U FinTech Course.
2. We are now starting the second module
3. covering payments and money.
4. In this course,
5. you will learn about, first,
6. how payment has evolved over the years,
7. second, its importance in the context of FinTech,
8. and finally, how new technologies
9. such as distributed ledger technology
10. is building a brand new payment stack.
11. Payment is a critical part of finance.
12. Since the FinTech industry
13. caught the eyes of investors,
14. payment has consistently been
15. the largest sub-sector
16. in terms of VC investment.
17. Not only this,
18. but the media coverage has strongly covered
19. the impact of e-money
20. whether in Africa with M-Pesa
21. and Alipay in China,
22. two examples that
23. we will cover further in this module.
24. Whilst the majority of the FinTech industry
25. is represented by B2B companies,
26. payment represents an exception in many respect.
27. This industry has many layers
28. and therefore clients and users.
29. We will reveal and explain
30. how each are interrelated
31. and how technology has changed
32. their model of operation.
33. Payment is unique in that
34. we use it every day,
35. in Europe alone,
36. people are using their contactless card
37. over 10 times every day.
38. It also represents a very social element,
39. whether it’s gifting or requesting money,
40. technology is changing the way
41. we interact with people,
42. from WeChat red-envelope connecting families
43. thousands of miles apart
44. to Venmo bill splitting feature
45. which is changing the social stigma
46. over requesting for cash.
47. However, there is more than the eye can see.
48. Payment to function
49. correctly relies on a complex infrastructure
50. such as telco operators, banks
51. or international consortiums like Swift.
52. In this module,
53. we will put you at the centre of the industry.
54. We will be entering each layer one by one,
55. before showing you
56. the future of the industry
57. and how and why we believe
58. it’s now at a tipping point.
59. You can imagine
60. each of this course’s module as circle.
61. You will easily relate to the one closest to you
62. but you will also learn about
63. the importance of the underlying infrastructure
64. found in the more distant circles
65. which you may not use on a regular basis.
66. The first circle is the one closest to you
67. and you are in its centre.
68. We will introduce payment
69. from point of view of an individual
70. and how it has evolved
71. from barter to cash,
72. from checks to cards,
73. and more recently, QR codes and cryptocurrency.
74. The second circle looks at
75. non-banks and telecom operators
76. that have provided payment solution,
77. leveraging on mobile phones
78. and person-to-person networks they represent.
79. These new entrants are providing services
80. to a previously underserved market,
81. but with it, raises opportunities and risks.
82. The third circle is composed of your bank
83. and your government central bank.
84. Traditionally a place where
85. you have deposited your money,
86. recent mandated changes
87. such as real-time-gross-settlement, RTGS,
88. or PSD2 in Europe
89. are opening opportunities
90. for new business models
91. on how your money
92. can be received, sent, or spent.
93. The fourth and final circle looks at the world,
94. cross-border transaction and correspondent banking.
95. As individuals, you may have experienced
96. cross-border payments
97. in the context of remittance,
98. however, this only represents
99. a very small fraction
100. of the global financial transaction initiated
101. and settled through payment network such as Swift.
102. Finally, the payment module
103. will open by introducing the development
104. of a new payment stack
105. which has been made possible
106. by the advancement of a new technology
107. such as DLT, distributed ledger technology,
108. but also increasingly being justified
109. by recent risks identified in the payment rail system
110. that is now over 50 years old.
111. This final module will provide you
112. the basis of operation
113. of a decentralised system,
114. its difference with the current status quo
115. and its potential to complement
116. or replace the current infrastructure.

Module 2 Learning Objectives

Module 2 introduces the spectrum of electronic and other means of payment, from the traditional (cash) to the most recent (Bitcoin and cryptocurrencies). It highlights to learners the evolutionary context as well as the transformative role of new technologies in both traditional payments as well as alternative money and payment systems and the role of these in our daily lives and in our broader economies.

In Module 2, learners will:

• Consider the evolution of payment and money, from paper to digital to cryptocurrencies and beyond.
• Understand the underlying infrastructure of both traditional and new forms of payment.
• Understand how technology is transforming payment in developing countries and how it is changing payment in developed countries.
• Analyze the role of blockchain and cryptocurrencies in developing new means of money and payment.

2.2 Individual Payments

1. We will now be looking at
2. the evolution of payment
3. from the perspective of usage of an individual.
4. Most of us are using money
5. to make and receive payments.
6. However, technology has changed
7. both the form of money takes,
8. but also how it’s being transferred.
9. In short, you can think of four phases
10. that we will all discuss in more details.
11. This first phase was barter.
12. The second phase was commodity money.
13. The third phase was coinage.
14. And the fourth phase was dematerialized payments.
15. The evolution of money
16. as a mode of payment
17. is over 10,000 years old.
18. The first phase started in 9000 BC,
19. up until 600 BC.
20. It was the one of barter.
21. People directly exchanged goods and services.
22. There was no money as a standard
23. or medium of exchange.
24. This system, however, had limitations,
25. including the capacity of carrying goods,
26. and transporting it across long distances
27. to make exchanges
28. or standardise commerce.
29. This evolved into the second phase
30. of commodity money.
31. With certain items being selected
32. to perform transaction.
33. For example, in 1100 BC,
34. China used small cast replicas
35. of goods, token, made out of bronze.
36. However, you may be more familiar with
37. example of other commodities being used,
38. such as silver or gold.
39. Even the word salary
40. is actually related to that era.
41. Back then, Roman soldiers were paid in salt
42. and their salt was a salary.
43. From 600 B.C.,
44. coinage has been introduced in Lydia, today’s Turkey,
45. but it will take another 1000 to 2000 years
46. until paper money starts to be introduced,
47. first in China, in the 700s,
48. and then in Europe,
49. with Sweden leading the way in the 17th century.
50. Paper money represents an example of
51. how technology, the printing press,
52. allowed to store varying amounts,
53. from one US dollar to 100 US dollar,
54. on the same size of paper.
55. In addition, European banks started to guarantee
56. that the bearers of bank notes
57. had to be paid in gold equivalent.
58. One of the previous limitation of money,
59. that it was light,
60. and therefore flying away in the wind
61. when you do commerce,
62. became an advantage,
63. because now instead of paying cargos
64. with heavy bags of coins
65. that were inconvenient and risky,
66. you could pay with small bills
67. that were light and stored a lot of value.
68. The dematerialization of payment
69. increased in speed and method
70. from the 1950s onward,
71. as technology has become more commoditized.
72. Payment was increasingly digital,
73. and the volume of non-cash transaction
74. has been steadily rising ever since.
75. Here is a timeline of how
76. payment innovation has evolved,
77. and with it, your behaviour.
78. 1946, the first credit card is created
79. with it before being popularised by
80. card networks in the ’50s.
81. The chequebook is introduced
82. about the same period.
83. In 1980s,
84. the ATM network becomes
85. interconnected and global
86. with millions of withdrawal points available.
87. In the 1990s,
88. the EMV standard creation allows
89. to enhance security
90. and data storage on cards.
91. In 2000, mobile money
92. provides a payment solution in developing countries,
93. or banking services in developed nation.
94. The dot-com period
95. and the rise of internet
96. and e-Commerce companies
97. has started the trend of complete digitization
98. of cash transaction.
99. Plastic cards have been replaced
100. by e-wallets or virtual cards.
101. But it kept on going.
102. 2009, Bitcoin is created
103. as a decentralised currency,
104. stored across the internet.
105. 2010, introduction of
106. contactless cards and payments,
107. which seven years later,
108. are one of the most popular method of payment.
109. 2015 onward,
110. the popularisation of wearable devices,
111. mobile wallets and cryptocurrencies continues.
112. Payment methods have changed
113. and with it all behaviours.
114. From the Amazon supermarket without checkouts,
115. to Venmo true-value proposition
116. of not being a bill splitting app,
117. but instead addressing the social stigma
118. to request for money.
119. Predicting the future of payment is difficult,
120. and it is not anymore linked just to money,
121. but to technology itself,
122. that is changing the methods
123. available to you.
124. Indeed, cryptocurrencies
125. were not even considered
126. less then a decade ago.
127. And even today,
128. data is becoming the new oil
129. and allowing a new type of barter system
130. where people are giving
131. their personal information,
132. in returns of goods and services.
133. Therefore, payment and money
134. is constantly evolving,
135. even more rapidly today.
136. And we will point you toward
137. the further reading materials
138. for you to keep updated
139. your knowledge on that sector.

2.3 Developing Countries and DFS: The Story of Mobile Money

1. Hello, I’m Ross Buckley,
2. the King and Wood Mallesons Chair
3. of International Finance Law at UNSW Sydney,
4. and I’m here to talk to you about
5. the story of mobile money
6. and digital finance in developing countries.
7. I want to tell this story in terms of four questions.
8. What? Where? How? and Why?
9. So, let’s start with “What?”.
10. What is mobile money?
11. Well, it’s e-money.
12. It’s an electronic credit on a mobile device
13. that represents a unit of real money
14. that typically sits in a trust account
15. in a commercial bank somewhere.
16. So, it’s an electronic representation of paper money,
17. and that being electronic allows you
18. to do all sorts of useful things with it,
19. like save more readily,
20. make remittances,
21. send money back to your village,
22. pay bills,
23. do all sorts of things that
24. otherwise would take you time
25. and cost you more money.
26. Where was it developed?
27. Well, it came about because one day,
28. telecommunications companies realised
29. that their software tracked in real time airtime credits.
30. They knew exactly how many minutes
31. a prepaid customer still had in credit,
32. and if they knew that,
33. they knew how many currency credits the customer had.
34. They realised this software could well adapted
35. to do the same thing.
36. And so, mobile money was born.
37. Initially, in a in a few countries,
38. including the Philippines,
39. but it achieved lift off in Kenya a decade ago in 2007.
40. It was a Vodafone product, M-Pesa,
41. and within three or four years,
42. the majority of Kenya’s GDP was flowing
43. through M-Pesa every year.
44. The “How” question, how does it work?
45. Well, it’s based on cash-in and cash-out agents
46. who are the same small shopkeepers who sell airtime.
47. These are tiny stores,
48. maybe three metres by three metres,
49. by the side of the road
50. that sell tinned meat and soft drinks,
51. and cigarettes and airtime,
52. and is also act as agents for the mobile money service.
53. So, a customer can walk in,
54. pass some cash across the counter,
55. and get a credit
56. that shows up immediately on their phone
57. and they can walk away happy,
58. knowing they’ve got
59. some electronic money on their phone
60. that they can do things with,
61. that they couldn’t so readily do with the paper money.
62. That’s one way a credit comes about,
63. but the more often way is
64. the government makes a transfer payment,
65. a welfare payment directly to the phone,
66. because paper-based payments
67. have all sorts of problems for governments
68. in developing countries,
69. and electronic payments
70. are a much more efficient method.
71. Often, central banks will want
72. this service offered by their banks
73. because they trust the banks,
74. they know the banks,
75. they know how to regulate them.
76. But, banks around the world
77. are not typically good at providing services
78. to poor customers.
79. The entities that are already doing that
80. are the TELCOs.
81. They are very efficient at selling services
82. to very poor people and generally,
83. if you’re a government,
84. you’ll get the innovation
85. in the mobile money space
86. from your telecommunications companies
87. more than your banks.
88. The fourth question is,
89. why does it matter?
90. And it matters because without electronic money,
91. paying an electricity bill or a school bill
92. can require a parent to take the whole day off work,
93. travel for a few hours on a bus,
94. stand in a queue for a few hours,
95. travel a few hours home.
96. This is not typically transformative
97. for people who live in the capital city
98. or in the big cities,
99. it transforms the life of people
100. who live in the countryside
101. who don’t have access to bricks and mortar branches.
102. It enables them to send money home to a relative,
103. to save money safely,
104. to pay bills in their microbusiness,
105. whatever they need to do,
106. to do it quickly and safely and cheaply.
107. In some states in India,
108. before mobile money was introduced,
109. up to 45% of government welfare payments
110. would go missing
111. because you had a largely illiterate population
112. and a paper-based system.
113. The electronic auto trail of mobile money
114. gets around that problem.
115. In Papua New Guinea,
116. teachers are regularly taking off days off school
117. so they could cash their paychecks,
118. before mobile money systems allowed them
119. to get access to their pay without having to,
120. again, get on a bus for a few hours
121. to the nearest major town.
122. The buzzword is financial inclusion.
123. It’s about including these previously excluded people
124. in the financial services
125. and allowing them to do things more efficiently,
126. and thereby promote economic growth
127. and reduce poverty.
128. What are the challenges with it?
129. Well, it’s worked well in east Africa.
130. Kenya, Tanzania, Uganda,
131. it’s worked very well.
132. In other places, the record is more patchy.
133. In many countries,
134. governments transfer payments
135. to mobile money accounts,
136. people go to the cash-in and cash-out agent,
137. take the cash out, and then transact in cash.
138. That fails to realise most of the goals
139. of financial inclusion, you know,
140. they’re not getting the efficiency benefits,
141. you’re not getting the network effects,
142. you’re not getting the vibrant ecosystem,
143. and it also causes a real problem for agents
144. because agents are mainly handing out cash,
145. and unless the other part of their business
146. provides them with a ready inflow of cash,
147. they’re going to run out of cash often
148. and they’re not going to be able
149. to meet redemption requests,
150. and then people get frustrated with the system.
151. So, lots of people around the world
152. are working to try and solve this.
153. They’re working by developing
154. new technological products,
155. customer education programmes,
156. or in the case of the programme I lead at UNSW,
157. we work with central banks
158. in partnership with the UN Capital Development Fund around the world,
159. we work with poor country central banks,
160. helping them get their regulation more adapted,
161. more suitable to digital finance.
162. But, there are main roadblocks
163. to vibrant digital financial ecosystems
164. in many countries,
165. and one of the fundamental ones of these
166. is a failure to adapt products to local needs
167. and to understand local customer journeys,
168. and I’ll discuss this with you later.
169. Thank you.

2.4 Developing Countries and DFS: Regulation of Mobile Money

1. Hello I’m Ross Buckley,
2. the King and Wood Mallesons Chair
3. of International Finance Law at UNSW Sydney.
4. I’m here to talk to you about
5. the regulation of mobile money
6. and digital financial services in developing countries.
7. The first thing we need to do
8. with mobile money is keep it safe.
9. We need to protect the float.
10. The float being the body of actual money
11. that represents the electronic credits
12. on the mobile devices.
13. In Common Law countries,
14. this is relatively easy to do,
15. using the institution of a trust.
16. You have a trust deed which
17. we’ve given you a version of
18. in the publication that’s up on your slides.
19. There’s a trust deed,
20. either money is deposited
21. under that deed in a commercial bank,
22. and the deed provides for the role of a protector.
23. The protector will typically be the Central Bank,
24. although it could be somebody else.
25. They will have the duty of
26. inspecting the trust arrangements
27. and insuring, most importantly,
28. that there is a 1:1 ratio
29. between issued electronic money
30. and actual money sitting in the trust account,
31. various other rights of the protector as well.
32. And the protectee you need
33. because the beneficiaries of the trust
34. are the customers,
35. they’re not going to understand all this,
36. and they’re not going to enforce their own rights.
37. So as I said, in common law countries,
38. relatively easy to do.
39. In Civil Law countries, not so simple,
40. because usually the trust is not there.
41. But you can get to the same end
42. using a mix of mandates,
43. contracts, fiduciary contracts,
44. and sometimes direct regulation as needed.
45. There’s no one size fits all solution
46. for Civil Law countries,
47. you need to craft a solution for each jurisdiction.
48. But again on your slides,
49. there’s an article that we’ve written,
50. that you can easily draw down off SSRN,
51. that deals with all of those technical issues.
52. Once you’ve kept the float safe,
53. there’s only two other, in my view,
54. core pieces of regulation you need.
55. One is Consumer Protection Regulation
56. and the other is Money Laundering
57. and Terrorism Financing Regulation.
58. You need the latter because you need it.
59. There’s an international regime
60. that you eventually see a country on a blacklist
61. if it doesn’t have adequate AML/CTF regulation.
62. And the important thing to do in dealing with that,
63. is to use proportional risk-based assessment.
64. In most poor countries
65. you are not going to be able to comply,
66. you’re not going to be able to
67. reach the very highest standards of
68. Know-Your-Customer certification.
69. You’re going to have to, you know, cut some corners
70. and decisions are going to have to be made.
71. But the international regime allows for that.
72. The problem often is that regulators
73. try to enforce standards that are higher
74. than is required by the international regime
75. and are not appropriate for their own countries.
76. So we need a little bit of regulatory innovation
77. and courage often in that space.
78. Consumer Protection is
79. essential for the substantive reason
80. that without it,
81. people won’t trust the system.
82. If people are losing their money,
83. they won’t keep using it.
84. And mobile money and digital finance
85. needs network effects.
86. It needs a lot of people using it
87. so that it’s beneficial for everybody.
88. The easy part for consumer protection is rules.
89. It’s relatively easy to craft a good set of rules.
90. The difficult part is recourse mechanisms.
91. People have got to have some way
92. to get their problems solved.
93. And any effective recourse regime, in my view,
94. needs a free-to-call telephone number
95. that’s manned a good number of hours a day
96. by someone with authority
97. to resolve customer problems.
98. If people have to pay to make the call
99. and wait a long time online,
100. they’re going to hang up.
101. If it’s a free call
102. but it’s not answered for an hour,
103. they’re going to hang up.
104. They’re not going to get their problem solved.
105. And central banks need to police this.
106. Central banks actually need to
107. sort of play the role of mystery shopper, I think,
108. and pretend to be customers and find out
109. how well these recourse mechanisms work.
110. Because they’re really essential to consumer trust
111. in a digital financial ecosystem.
112. I also wanted to talk about the difference
113. between FinTech in rich countries
114. and digital finance in poor countries,
115. because they come from quite different places.
116. FinTechs in rich countries are typically startups.
117. They’re young entrepreneurs seeking to get rich.
118. Digital Financial Services in poor countries are partly,
119. occasionally driven by that, but not so often.
120. They’re mostly driven by government policy.
121. Governments have embraced
122. this idea of financial inclusion
123. and they’re encouraging their banks
124. and their telcos to provide it.
125. So rich country regulators
126. are trialling regulatory sandboxes,
127. safe places in which entrepreneurs can take risks
128. with reduced licencing obligations,
129. and they’re trialling other measures
130. to promote innovation.
131. And in some poor countries,
132. regulators are doing this,
133. but something much more is needed
134. of regulators in poor countries.
135. And that’s a major mindshift,
136. a major change of perspective.
137. So that they actually get out of the capital city,
138. they get into their own villages
139. where these innovations are needed,
140. and they talk to their own people and find out
141. what the customers in their countries really need.
142. Because this is what’s holding the development
143. of Digital Financial Ecosystems up in many countries.
144. It’s the offering of inappropriate products.
145. These countries are small.
146. The telecommunications companies
147. naturally want to roll out the same products
148. across multiple countries,
149. but the local Central Banks’ role in part
150. is to encourage the provider
151. to adapt the product for the local market.
152. And that’s a deeply different and innovative role
153. for a central bank
154. and one that they’re not accustomed to do.
155. But experience teaches us if they don’t do it,
156. it’s a real risk that the innovation will not thrive.
157. We’ve written about the customer journey,
158. we’ve written about building consumer demand
159. for Digital Finance.
160. You can find those references on the slides.
161. So I just want to conclude by emphasising
162. that for Digital Finance
163. to flourish in many countries,
164. a big change of mindset is required by the central bank.
165. They will typically be the primary regulator,
166. they’re typically very prudent,
167. because their job is to preserve the safety
168. and soundness of the entire system.
169. But mobile money doesn’t typically
170. raise systemic stability issues.
171. It’s not a risk on that scale.
172. It doesn’t need regulation of that weight.
173. It needs light and subtle regulation,
174. a maintenance of a watching brief
175. principally by the central bank,
176. and that requires a degree of regulatory courage.
177. Thank you.

Additional Resource Insights

Please click the link to download the presentation slides for Video 2.4 Developing Countries and DFS: The Regulation of Mobile Money.

2.5 RTGS Systems

1. We will now explain
2. how Real Time Gross Settlement has benefited
3. the development of FinTech Innovation.
4. We will do so by introducing two use cases,
5. one on the payment side,
6. and the other one on the lending side.
7. However, before we start,
8. what is RTGS, or real-time gross settlement?
9. In short, it allows for transaction between banks
10. to happen in real time
11. and settle on a one-to-one basis.
12. This is to be contrasted with batch transaction
13. where banks settle the net amount owed
14. at a pre-determined interval
15. such as the end of the day or the week.
16. Practically, you may have already
17. experienced this yourself.
18. For example, if you are in Hong Kong
19. and you wish to make a transfer
20. to a friend who has an account
21. in another bank as yours,
22. if you initiate the payment transaction in the afternoon
23. it will only arrive the following day.
24. This is because
25. the payments are processed in batch.
26. However, if you are in the UK
27. and viewing this course,
28. you will know that bank-to-bank transfers
29. are instant and free.
30. This is because Faster Payment,
31. or an RTGS equivalent,
32. has been introduced in 2014.
33. The necessity to move from
34. a batch to a real time world
35. is driven by two factors.
36. Firstly, technological capacities,
37. which have become more robust and scalable.
38. Secondly, customer expectation of instant delivery.
39. As we move to mail to e-mail,
40. we remove latency and cost to communicate.
41. The same was due to happen in payments.
42. Because RTGS systems
43. constitute a core component
44. of any national payment stack,
45. the reform process is slow
46. and once engaged,
47. takes decades to be fully implemented.
48. And whilst the majority of countries
49. have RTGS system in place,
50. a few more large players are still coming,
51. such as China and Australia.
52. Now the question really becomes:
53. How can RTGS support FinTech Innovation?
54. And here are two use cases
55. that we’ll now bring to you.
56. First, peer-to-peer payment.
57. The whole companies,
58. such as Venmo in the US,
59. that are facilitating payment transfer between individuals,
60. can only fully be successful
61. if real time payment actually happens.
62. Think about this,
63. if you were to split the bill with a friend,
64. however that bill splitting
65. and that request to a friend
66. would take one day or more to clear,
67. the gratification of being able
68. to receive the funds straightaway would not happen.
69. And therefore, the capacity of FinTech startups
70. to process real time payment,
71. either from within their account,
72. or between accounts,
73. becomes an important value proposition
74. for their capacity to deliver
75. a better user experience.
76. The second example is peer-to-peer lending.
77. RTGS is actually linked closely
78. to the development
79. of the peer-to-peer lending industry in the UK.
80. You may see peer-to-peer lending as a method
81. for people to borrow funds
82. when they’re not credit worthy,
83. and when banks do not want to lend them.
84. However, research has shown
85. that one of the core benefits
86. of peer-to-peer lending,
87. is not so much on the credit worthiness
88. as well as the interest charged on the loan,
89. but it’s the speed at which
90. the loan is being delivered on your bank account.
91. And this for example
92. has been clearly seen in the UK.
93. Some peer-to-peer lenders in the UK
94. charge high interest on the loans they provide,
95. and one of the questions was,
96. why do people in the UK
97. rather go on an online peer-to-peer lending platform
98. and pay a higher interest rate,
99. compared to what they would otherwise
100. qualify on a high street bank?
101. And the answer was speed and convenience.
102. Once you are authorised
103. to get a peer-to-peer loan in the UK,
104. you would be credited on your account
105. in the same second.
106. As a result, the funds would be available
107. for you to spend straightaway.
108. And for the capacity of the peer-to-peer lender
109. to make a bank-to-bank transfer instantly
110. as soon as the loan has been approved,
111. has only been made possible
112. because of real-time gross settlement.
113. In other words,
114. RTGS in the context of peer-to-peer lending,
115. allow for convenient and instant payment
116. of the loan into the account of the borrower.
117. Now if we go further,
118. we can look at the evolution of
119. payment mechanisms and options,
120. and this will continue to keep on growing.
121. For example, most recently
122. the Bank of England
123. will be opening the RTGS system
124. to non-bank Payment Service Provider.
125. This will further increase competition
126. and therefore consumer
127. will allow to have more innovation.
128. And as FinTech start-ups
129. will be able to deliver new payments methods.
130. Not only this,
131. but this schedule of reform
132. planned for the UK
133. will also include how Blockchain and API
134. can be interfaced with their RTGS systems.
135. In other words,
136. RTGS represent a critical infrastructure layer
137. supporting FinTech innovation
138. even though you may not directly be aware of it
139. as it operates in the background
140. and serves as a payment rail.

2.6.1 The ABCDs of Alternative Finance (Part 1)

1. In his 2014 letter to JP Morgan’s shareholders,
2. Jamie Dimon famously issued a warning
3. to its shareholders, employees
4. and even traditional competitors.
5. Silicon Valley is coming.
6. At the bank’s investor day
7. he added more colourfully,
8. when I go to Silicon Valley,
9. they all want to eat our lunch.
10. Every single one of them is going to try.
11. During the last few years,
12. alternative finance is slowly transforming
13. the offering of financial services
14. and the providers of such services
15. in two main ways.
16. New business models
17. and new technologies.
18. It’s critical to understand
19. the four key and interrelated technologies
20. that have allowed alternative finance to flourish.
21. These can be known as the ABCDs driving FinTech,
22. namely, artificial intelligence, or AI,
23. blockchain, cloud computing, and data.
24. Let’s deal with each of them in reverse order.
25. Banks for the longest time
26. have relied upon and generated
27. a tremendous amount of information.
28. These include information from and about customers,
29. their identity, their transactions,
30. their net worth
31. and even their relationships and location.
32. Yet a lot of this has been gathered
33. by using paper forms
34. filled by customers and bank staff
35. and not easily searchable
36. or manipulated for analysis.
37. The digitization of information
38. from paper into data,
39. from physical pulp to digital ones and “0”s
40. means that such information
41. can more easily stored,
42. transmitted, searched, processed,
43. analysed and displayed.
44. This digitization allows for
45. online capital marketplaces
46. to be more easily created and operated
47. where gatherers can more cost effectively
48. process and analyse the data
49. for those who need the capital
50. and then display the relevant information
51. on the new platforms
52. for the potential providers of capital
53. to make their own investment decisions.
54. At the same time,
55. digital form filling and tracking
56. of the online customer activity
57. allows both these online platforms
58. as well as, virtual banks and e-brokerages
59. to scale more quickly with less manual labour
60. and space resources
61. that would otherwise be required for,
62. for example, traditional bank branch networks.
63. Customer data includes online behaviour
64. such as the time and location of logging in
65. and transactions
66. as well as, other online activities
67. such as web browsing, e-commerce
68. and social media use.
69. Increasingly, offline behaviour
70. is also being tracked through data
71. from internet of things for IoT devices
72. such as wearable smart watches,
73. smart cars and smart home devices
74. such as Amazon Echo.
75. For example, in the world’s biggest retailer, Walmart,
76. 2.5 petabytes of data every hour is processed.
77. One petabyte is 10 bytes with 15 “0”s afterwards.
78. The other has been called the new oil
79. that is being bought and sold
80. by gatherers and users
81. and increasingly fueling the AI engine
82. that we will discuss subsequently.
83. In the past, businesses such as financial institutions
84. had to build their IT systems
85. using different enterprise level software
86. that was developed or licenced
87. at high cost over time
88. and hosted on large servers on premises.
89. With the advent of cloud computing,
90. software resides at data centres on servers
91. run by companies dedicated managing such servers
92. which also provide value-added services
93. such as cyber security protection.
94. This means that new businesses
95. such as alternative financial providers
96. no longer need to dedicate high capital expenditure
97. to expensive infrastructure
98. and can focus on improving client experience
99. and can dynamically scale their server usage
100. in accordance with their rates of growth.
101. Cloud computing also allowed
102. new business models to blossom.
103. Software as a service or SaaS businesses
104. bypass the traditional vendor model
105. of software development and sales
106. that require marketing software licences
107. at higher upfront fees
108. and then again each time a new version
109. or upgrade is introduced.
110. Software that resides in the cloud
111. can now be marketed at a lower upfront cost
112. based on a subscription model.
113. And software upgrades can be automatically
114. made on a continuous basis
115. which gives the client one less reason
116. to switch vendors.
117. This means that online capital marketplaces
118. as well as, startup virtual banks
119. like UK Starling Bank
120. require less upfront cost
121. to prototype new business models
122. and user interfaces
123. to roll out more quickly and cost effectively
124. and to do the same
125. when scaling to new jurisdictions.
126. In addition, the cloud
127. enables connected IoT devices
128. to gather data and stream more services
129. including financial services
130. to customers through new interfaces
131. like smart watches,
132. voice-activated speakers
133. and smart homes and smart cars.
134. Cloud computing effectively allows
135. for institutional level technology support
136. to retail businesses
137. whereby user customers can now transact
138. on their office computer on the road
139. via their smartphones or smart cars
140. or at home in their pyjamas.

2.6.2 The ABCDs of Alternative Finance (Part 2)

1. Distributed ledger technology or DLT
2. continues to have an evolving impact
3. on alternative finance.
4. The oldest example of double-entry bookkeeping
5. can be found in the publication in 1494
6. of Franciscan Friar Luca Pacioli
7. which allowed for reliable documentation
8. of both creditor and debtor
9. in a standardised manner.
10. The white paper on Bitcoin
11. by the mysterious Satoshi Nakamoto in 2008
12. was similarly revolutionary
13. in establishing a cryptocurrency that seeks to solve
14. the double spending problem
15. intrinsic in a currency
16. based on software without the need
17. of a trusted authority or central server.
18. Nakamoto postulated a ledger that is distributed
19. via a peer-to-peer network
20. which records transactions
21. by way of blocks.
22. Each block is validated
23. by different node computers in the network
24. through solving cryptographic mathematical puzzles,
25. or hashes, at which time a new block
26. with a new cryptographic hash,
27. timestamp, and data would be added to the chain
28. which is transparent to all users.
29. Data on the block is immutable
30. and effectively cannot be altered
31. unless all prior blocks in the chain
32. are altered by consensus
33. or agreement of the network majority.
34. Blockchain is the underlying technology
35. behind cryptocurrencies
36. that have expanded dramatically beyond Bitcoin.
37. In this way,
38. this technology has created
39. a new form of digital asset
40. as well as a new alternative finance method
41. to raise capital for new projects,
42. with the so-called crypto exchanges
43. comprising new forms of online capital marketplaces.
44. In addition, blockchain technology could form
45. the basis of new capital markets infrastructure.
46. NASDAQ is using blockchain technologies
47. to secure record keeping of ownership
48. of private companies and transfers.
49. In December 2017,
50. Australia’s ASX announced that it would replace
51. its stock exchange registry,
52. settlement and clearing system
53. with blockchain technology.
54. An even more ambitious use of blockchain technology
55. through the creation
56. of distributed autonomous organisations or DAOs
57. that allow for automatic execution
58. upon specific conditions
59. via smart contracts,
60. with innovative governance mechanisms
61. based on direct voting and consensus.
62. If implemented to its fullest extent,
63. DAOs and its efforts to disintermediate
64. could impact not only the venture capital market
65. but also the very concept of the joint stock company
66. and even some functions of government.
67. The term artificial intelligence was coined
68. at the now famous Dartmouth summer research workshop in 1955.
69. Two initial clarifications would be helpful.
70. First, it should be noted that
71. we refer to the narrow or weak AI
72. that relates to algorithm performing specific tasks,
73. as opposed to general or strong AI
74. that reflect broader human intelligence
75. and decision-making.
76. Second, there are different strands within AI,
77. including Natural Language Processing or NLP
78. which relates to language, often written,
79. and Machine Learning where
80. systems learn from experience
81. by being trained with data
82. as opposed to being rules-based.
83. There are many techniques within Machine Learning,
84. including neural networks which comprise
85. nodes of weighted interconnectedness
86. inspired by the human brain, and deep learning,
87. which refers to algorithms based on neural networks
88. arranged in deeper layers.
89. Computer vision for image recognition
90. is a good example of machine learning.
91. After a long so-called AI winter of lacklustre activity,
92. AI has blossomed due to
93. a confluence of events
94. that made both Fortune and Forbes
95. name 2017 the year of AI.
96. First, instead of expensive large supercomputers
97. required for the AI algorithmic processing,
98. researchers started using
99. relatively cheap graphical processing units or GPUs
100. originally developed for video games
101. with increased computational power
102. when used in parallel.
103. Second, data storage cost continues to fall
104. while data is being gathering at alarming rates
105. through online activity and connected devices,
106. thereby allowing for
107. more structured and unstructured data
108. to be gathered, stored, and used
109. to train the machines.
110. Third, most major cloud companies,
111. such as Amazon’s AWS, Google Cloud,
112. Microsoft’s Azure, IBM Cloud
113. and Alibaba’s Aliyun
114. incorporate AI into their services,
115. often including machine learning frameworks
116. on some open source basis
117. to allow their clients to experiment
118. and incorporate into their operations.
119. For example, AI is rapidly changing
120. Alternative Finance user interfaces,
121. from facial and voice recognition
122. for biometric identity management
123. to chatbots that can provide
124. personalised recommendations.
125. Algorithmic matching of needs,
126. pricing, and predictive analytics are also being used.
127. AI also allows some alternative finance companies
128. to create new business models
129. that focus on analytics of the customer data
130. rather than building platforms
131. to provide financial fund flow.
132. For example, some Chinese companies
133. which started primarily as P2P lending companies
134. have pivoted to provide credit analysis and scoring
135. that serve the marketplace lending
136. conducted by institutional investors and lenders.

2.7 Building A New Stack

1. In the 19th Century, we developed
2. the current payment stack
3. based upon physical money like gold,
4. paper money representing gold,
5. instruments like securities,
6. negotiable instruments, checks,
7. all cleared through a banking system
8. that collected fund transfers
9. and settled across the accounts of a central bank
10. which was responsible for the monetary supply.
11. Across the 20th Century,
12. we digitised this system.
13. We transformed it from a system
14. which was based on physical analogue elements
15. to a digital system of payments,
16. of eventually, mobile payments, RTGS systems,
17. and digital electronic payments
18. totalling over five trillion US dollars a day.
19. At the beginning of the 21st Century,
20. we are applying a process of datafication,
21. applying techniques of big data,
22. artificial intelligence and other mechanisms
23. to use the digitised data to transform
24. the payment experience to provide
25. a seamless mobile lifestyle experience.
26. We however are now going further.
27. We are looking at developing
28. an entirely new payment stack
29. through the use of technology.
30. Technology today is no longer a barrier
31. to redesigning a payment system.
32. Instead, our existing institutional frameworks
33. are the barrier and, looking forward,
34. we can easily see an increasing use of
35. real-time payments
36. which could either take place
37. across the banking system
38. or new entrants like tech companies
39. or directly eliminating the role of banks themselves,
40. the idea of disintermediation,
41. and we are actually seeing
42. these processes in real life in the context of China
43. with Alipay, with WeChat Pay,
44. in the context of the UK
45. and an increasing number of jurisdictions
46. with faster payment systems
47. allowing real-time, instantaneous payments
48. between individuals and companies
49. both through the banking system
50. or outside of the banking system,
51. and, looking forward,
52. we can imagine
53. how this fundamental payment infrastructure
54. can be the base of a new stack based on payment
55. supporting e-commerce,
56. supporting lending,
57. supporting investment.
58. If we think of e-commerce,
59. one of the fundamental killer apps to e-commerce
60. is simple, digital, and in particular,
61. mobile-based payment systems.
62. On the basis of those mobile-based payment systems,
63. one can also build digital lending frameworks
64. both for consumer lending for individuals,
65. as well as for small and medium-size enterprises
66. using data analytics technology to collate data
67. to do real-time cashflow analysis
68. to determine credit worthiness
69. and finally, pulling all of these pieces together,
70. we can build systems of investment,
71. systems which allow both individuals
72. as well as the wider economy
73. to better invest their funds
74. in order to support the development of the economy.
75. On the basis of this framework,
76. we are also seeing
77. an increasing number of jurisdictions
78. led by the European Union
79. developing what is called open banking.
80. Open banking allows access to banking data
81. and banking infrastructure by new entrants,
82. by tech firms, by startups,
83. and this poses a major challenge
84. to the traditional model of banking
85. and, at the same time as we look at digitising
86. and datafying the system,
87. we are also looking at new technologies like blockchain,
88. and new forms of money and payment
89. like digital currencies or cryptocurrencies.

Additional Video Resources: Cross-Border Payment

1. SWIFT Overview  (2.49 Mins)

2. SWIFT for Banks (2.45 Mins)

3. The Future of Cross-Border Payments (2.27 Mins)

4. Watch Traffic for Banking: BI that gives you the edge (2.01 Mins)    

2.8 Cryptocurrencies

1. Hi there, time to talk about
2. the very exciting topic of cryptocurrencies.
3. You’re probably hearing of the cryptocurrencies
4. in the news or the newspapers,
5. or your friends are talking about it.
6. And there’s definitely a lot of buzz around
7. the broader cryptocurrency space globally.
8. But first, what is a cryptocurrency?
9. Well, a cryptocurrency is a digital asset
10. that serves as a medium of exchange or store value
11. that is generally based on a blockchain
12. and you use cryptography as its security feature.
13. What makes it quite interesting
14. is that in many cases,
15. it is not issued by any central authority
16. rendering it in, let’s say,
17. immune to government interference or manipulation.
18. Well, what’s important to understand
19. is actually cryptocurrencies are nothing new.
20. People have been working on the topics
21. since 1980s or ’90s.
22. Many active groups were related to the military
23. or more crypto-focused groups, like one of the,
24. like the Cyberpunks, for example.
25. But really, the big game-changer took place
26. towards the end of 2008,
27. where an individual, or a group of individuals,
28. we don’t know yet, called Satoshi Nakamoto,
29. published a white paper called
30. “Bitcoin, A Peer-to-Peer Electronic Cash System”,
31. which was really the basis of Bitcoin.
32. And Bitcoin was born.
33. And a lot of things have happened since then,
34. yeah, more today,
35. more than 1,500 different cryptocurrencies in the market.
36. But what was really innovative with Bitcoin is
37. that it solved one of the big problems
38. that we had at that point,
39. which was the double-spending issue,
40. the risk that a digital currency can be spent twice.
41. Think about it, if I send you an email,
42. there’s a copy of that email on my computer,
43. and a copy on yours.
44. Well, that’s practical for emails,
45. that doesn’t go well
46. if you’re actually sending money to somebody else.
47. Or else, there’ll be an endless supply of money.
48. And the beauty of Bitcoin is it was finally able
49. to solve that double-spending problem.
50. And that was a big game-changer.
51. Over the years, as obviously Bitcoin has gathered
52. increasingly more traction,
53. it has its ups and downs,
54. from a volatility perspective,
55. or even government and public’s attention to focus on.
56. But many would argue that the last year, 2017,
57. was really the year that Bitcoin
58. and other cryptocurrencies
59. aimed to enter the mainstream and generate
60. the really large amount of public awareness
61. And many would say that
62. we probably passed now the point of no return
63. when it comes to cryptocurrencies like Bitcoin.
64. And what is really exciting, people,
65. is some of it’s features, for example,
66. the Bitcoin is decentralised,
67. has no central authority,
68. it’s instantaneous, generally low-cost,
69. it’s borderless,
70. and you know, what’s quite interesting,
71. has only a fixed supply.
72. There will only be 21 million Bitcoin ever mined.
73. While it has a lot of attractive features,
74. it also has some challenges;
75. for example, it’s still not very user-friendly to use
76. for a general public.
77. For example, if I have a bank account
78. and I forget my pin, or I forget my password,
79. I can always go back to the bank
80. and try to get access to my account
81. by showing them different pieces of ID.
82. But if you’re trading cryptocurrencies,
83. and you lose your private keys,
84. well, they’re gone forever.
85. There’re other reasons as well.
86. For example, the electricity cost for Bitcoin
87. is often heard to discuss
88. that is actually not very environmentally friendly
89. to actually mine Bitcoins.
90. Well, a lot of people are working on the solution,
91. and there’s different ways actually manage
92. mining cryptocurrencies.
93. Yes, this may be actually an issue for Bitcoins, per se.
94. And the other more market-driven issues as well.
95. For example, the volatility.
96. Very difficult to pay for goods
97. or argue for a value for goods in Bitcoin
98. if the value is actually very volatile.
99. What’s very, very important to understand
100. is that each cryptocurrency out there
101. has different characteristics and has different features,
102. making them each one appropriate
103. for certain type of transactions that you have.
104. Whether it’s payment or as a store value.
105. But what’s definitely clear is
106. that the industry is really booming.
107. As the beginning of 2018,
108. there was more than 300 billion dollars
109. in market cap in cryptocurrencies.
110. And a lot of interesting developments
111. were taking place as well.
112. For example, we were seeing institutional investors
113. enter the space,
114. which is very interesting.
115. Many of them are saying that
116. this is actually the birth of a new asset class.
117. We’re also seeing a lot of new crypto products.
118. For example, asset-back crypto,
119. where you have a crypto asset backed by
120. real life assets like gold, cash,
121. or securities, for example.
122. And also, it’s becoming very interesting
123. when we’re seeing a lot of central banks
124. look at launching their own
125. central-bank-backed digital currencies.
126. So definitely an area to watch,
127. and a lot of movement in this space.
128. One thing we often say is
129. whoever tells you they’re an expert in cryptocurrencies,
130. you’ve got to run away.
131. The space is moving so quick,
132. that it’s very, very difficult to keep up.
133. But, it’s definitely a very exciting area to be in.
134. Hope this was a useful presentation
135. and we’ll be back soon.

Industry Showcase (NEW*): Introduction to Digital Asset Market – Gatecoin

1. Hi, everyone.
2. I’m Brad, the Chief Operating Officer of Gatecoin.
3. Gatecoin is a a Bitcoin and Ethereum token exchange
4. designed for professional and retail investors.
5. Today, I wanted to spend some time delving
6. into a few topics around cryptocurrency exchanges.
7. You might be wondering to yourself,
8. why do cryptocurrency exchanges exist?
9. So, for me, similar to stock exchanges,
10. which issue in primary marketplaces securities
11. to buy and sell,
12. a crypto-marketplace is a place
13. for people to buy and sell digital assets.
14. Likewise, similar to a traditional exchange,
15. where companies have the ability to raise new money
16. through issuing securities or debt,
17. a digital market exchange is a place where,
18. through using instruments such as ICOs,
19. companies can also raise money
20. through pre-selling their revenue.
21. Essentially, providing early stage companies
22. and start-ups, a framework to raise money
23. while avoiding regulatory compliance
24. and other intermediaries, such as venture capitalists,
25. banks, or stock exchanges.
26. The regulatory attitudes and frameworks
27. on both exchanges and ICOs
28. vary wildly around the world.
29. However, each exchange also has its own specific rules
30. and regulations for trading and listing.
31. While these standards often vary wildly
32. from exchange to exchange,
33. projects will need to meet specific criteria
34. to foot the individual exchange
35. before they actually list their tokens.
36. ICOs of companies are done in a primary market,
37. directly between projects and their investors,
38. whereas subsequent trading in tokens
39. and other digital assets, such as Bitcoin and Ethereum
40. are executed in a secondary market
41. directly between traders.
42. The secondary market is
43. often the most crucial component of the market,
44. as the supply and demand in these markets
45. drives the liquidity and the pricing of the tokens
46. and other digital assets.
47. There are different types of digital assets.
48. So, from my perspective,
49. there are two types of exchanges:
50. a decentralised exchange and a centralised exchange.
51. At Gatecoin, we’re a centralised exchange.
52. That means everyone’s together.
53. We have one central authority
54. where your users will come on-board and trade with.
55. A decentralised exchange is where users
56. are actually generally working peer-to-peer,
57. and there is no one central authority creating the rules
58. or managing the system.
59. To put it simply, while there’s a decentralised exchange
60. and a centralised exchange,
61. there’s also one differentiating facet.
62. There’s the crypto to crypto and the fiat to crypto.
63. In a crypto to crypto exchange,
64. people credit their crypto onto the exchange,
65. and they can trade between each other, crypto assets.
66. In a fiat to crypto, people credit their fiat,
67. or their real-world money such as Euros,
68. Australian dollars, Hedge KD, or USD onto the exchange,
69. and then they convert it
70. or they buy and sell the digital assets.
71. And they can also do it to crypto to crypto trading.
72. So, how does a digital asset exchange differ
73. from a traditional stock exchange?
74. Here, we’ll have to look at it
75. into three main characteristics.
76. Custody, settlement, and trading-outs.
77. For custody and settlement,
78. a traditional stock exchange will act as the executor
79. when the trade happens.
80. However, custody and clearing are dependent
81. on a broad network of trust partners, such as banks
82. and other custodians and clearing houses,
83. who will hold the assets on behalf of the traders.
84. At this point, there are no regulatory requirements,
85. and the fact that the industry’s still in
86. it’s stage of development,
87. digital exchange act more as a marketplace
88. than an exchange, doing all three elements of execution,
89. custodian, and clearing on each and every transaction.
90. When considering trading-outs,
91. traditional stock exchanges often begin
92. at 9:30 in the morning
93. and end at 4:00 p.m. at the end of the day.
94. Digital asset exchanges trade for 24 hours,
95. 7 days a week.
96. Time in clearing is also a major difference,
97. with the traditional exchanges often clearing
98. on a T-plus-one or a T-plus-three cycle.
99. Now, what that means is today plus three days,
100. or today plus one day.
101. Clearing, in a digital exchange,
102. can nearly be instantaneous.
103. There are different types of tokens.
104. At the moment, there is no unified
105. classification for tokens.
106. However, we can still broadly classify tokens into several types:
107. security, utility, real cryptocurrencies,
108. which we could also call payment tokens,
109. and potentially also, asset-backed.
110. Simply put, securities tokens represent assets such as
111. participation in real physical underlying companies,
112. assets, earning streams, or an entitlement to dividends
113. or interest payments.
114. In terms of their economic function,
115. the tokens are similar to equities, bonds or derivatives.
116. The issuance of a security token is often called an SEO.
117. When considering if a token is either a security
118. or a utility, the key test will often be tax.
119. Consider the token if it pays dividends, interest,
120. or allows the claim of rights of ownership
121. in the company or an underlying asset.
122. If so, it’s likely to be a security
123. and regulated in Hong Kong
124. with a regulator such as the SFC.
125. On the other hand, a utility token gives holders
126. the access to services provided by the project,
127. essentially prepaying
128. or pre-purchasing the future project
129. or service the company creates or delivers.
130. Unlike securities tokens, utility tokens are not actually
131. designed as investments,
132. and this is why they do not currently fall under
133. any regulatory restrictions yet.
134. Other key questions is do the projects pay tax
135. on the revenue of the funds raised on the projects
136. or the projects to be delivered or services rendered?
137. If so, it’s also likely to be a utility token.
138. Cryptocurrencies or payment tokens.
139. These are based on fundamental blockchains
140. such as Bitcoin and Ethereum,
141. and is often considered as a means of payment.
142. Usually the tokens of these categories
143. have no further functions or links
144. to other developmental projects.
145. Speaking broadly, the purpose of cryptocurrency
146. is to be an item of inherent value.
147. For instance, to cash or gold.
148. They are simply designed to enable an exchange,
149. be it a purchase, sales, or other financial transaction.
150. They are intended to provide
151. many of the same functions
152. as long established currencies
153. such as the USD, Euro or Yen.
154. They do not have the backing of any government
155. or any other other body.
156. What makes a good exchange?
157. There are many elements to look out for
158. before establishing an account
159. on a digital asset exchange.
160. However, there are key elements I’d consider
161. you should pay careful attention to first.
162. We fundamentally believe
163. there are two kinds of exchanges,
164. those that have been hacked
165. and those that will be hacked in the future.
166. By the very nature of the industry that we’re part of,
167. the people will keep trying
168. to take advantage of security weaknesses.
169. So don’t be surprised, be prepared.
170. It’s very important to understand the security
171. of the company and ask questions like,
172. do you have a dedicated security team?
173. How do you manage a platform?
174. What are the security procedures or SOPs
175. in your company to prevent you from being hacked?
176. How can I remove my holdings off the exchange
177. and back onto my own wallet?
178. A higher liquidity in the marketplace is preferred
179. since it brings about the following advantages,
180. better and fairer prices for everyone.
181. Market stability, quicker transactions,
182. an increased accuracy for technical analysis.
183. Also be aware that recent developments have shown
184. that it’s possible for an exchange
185. to take advantage or fake their liquidity.
186. So also be cautious, and if it’s an exchange
187. that’s gone from being a very low liquidity
188. to one of the deepest markets in the world overnight,
189. then ask yourself, does it all make sense?
190. Finally, it’s clear that Bitcoin and Ethereum
191. and many other cryptocurrencies are opening the doors
192. to a new world of digital asset which we think
193. has the potential to someday become
194. a leading currency around the world.
195. At the moment, even the oldest of cryptocurrencies
196. are still maturing and only time will tell
197. where this new asset class is heading.
198. From what we can tell, there’s plenty of room
199. for advancement both as an asset class
200. and the market infrastructure needed to exchange it.
201. Regardless of your predictions for the future,
202. it’s hard to ignore that Bitcoin
203. has already revolutionised the digital world.

Industry Showcase (NEW): Stablecoins (Feron Labs)

1. Hi everyone, my name is Dmitri Senchenko
2. and I’m the founder of Feron Labs.
3. Today I am going to talk about cryptocurrencies
4. with price stabilisation mechanisms,
5. also known as stablecoins.
6. Before we get into price stabilisation,
7. let’s have a look at what makes for good money.
8. The classic answer to this question
9. is that money needs to satisfy three core functions,
10. it needs to perform well as a medium of exchange,
11. store of value and unit of account.
12. So how do cryptocurrencies measure up?
13. When talking about “medium of exchange”,
14. we refer primarily to the ability to transact.
15. Existing blockchains provide this functionality
16. at a basic level, and the challenge today
17. is to achieve commercial-grade speed
18. and scalability without sacrificing decentralisation.
19. A lot of talent and capital is being deployed
20. at this problem, and significant progress
21. is expected in the very near future.
22. In terms of store of value, current technology by
23. and large already allows cryptographically secure storage
24. and retrieval of assets within a robust
25. and durable distributed architecture.
26. Ability to serve as a unit of account is linked directly
27. to price stability, and this is arguably
28. where cryptocurrencies are at their worst.
29. Here, we enter the domain of monetary policy.
30. All cryptocurrencies have one by definition,
31. but they are quite primitive and obviously fail
32. at their task.
33. This is where stablecoins come in.
34. They seek to achieve price stability
35. through sophisticated monetary policy,
36. and to implement it on blockchain protocols
37. that fulfil the “medium of exchange”
38. and “store of value” functions.
39. This combination has the potential
40. to become truly usable money,
41. and to compete against conventional currencies
42. in practically every facet of the economy.
43. This goal is extremely ambitious,
44. but there is no shortage of tech talent
45. or venture capital ready to back it.
46. Stablecoins are an extremely young and diverse field
47. of research, but the majority of approaches
48. to date can be divided into three categories.
49. First, we have the fiat-collateralised models.
50. You place fiat currency on deposit
51. at a conventional financial institutions,
52. issue a corresponding amount of stablecoins
53. and institute a fixed exchange ratio
54. between the two at the level of your target price.
55. Stability is achieved through direct arbitrage
56. between the market price and the exchange ratio.
57. Such coins are, indeed, extremely stable,
58. but they give up all pretence of decentralisation.
59. They are completely hostage to the institution
60. that holds their collateral and are little more
61. than a technological extension to fiat money,
62. much like a debit card.
63. Next, we have the crypto-collateralised models.
64. Instead of keeping fiat in a bank,
65. you lock other cryptocurrencies in a smart contract.
66. Now, you are dealing with volatile collateral
67. that is no longer the same as the asset
68. against which you’re stabilising.
69. This has two major consequences.
70. First, you can no longer have a fixed exchange ratio
71. between your collateral and your stablecoin.
72. Instead, you need to know how much your collateral
73. is worth at any given time
74. and to adjust the ratio accordingly.
75. This is done by means of a price feed,
76. which is a tool that delivers external market data
77. into the blockchain.
78. Secondly, you need to hold a substantial amount
79. of excess collateral as protection against a decline
80. in its value.
81. Having to hold these risky assets
82. through all market conditions carries a cost,
83. which has to be levied somewhere within the system.
84. Early results suggest that crypto-collateralized models
85. can achieve stability under some conditions,
86. but the key question is whether the cost
87. of this stability can be made low enough
88. for large-scale issuance and adoption.
89. Finally, we have the uncollateralised models.
90. Most of them build on the theory that a change in price
91. can be counteracted by an appropriate change
92. in money supply.
93. For instance, if price declines by 10% and money supply
94. is then shrunk by the same 10%,
95. price should eventually revert to its original level.
96. A simplified example of such a mechanism involves a pair
97. of internally generated assets, a stablecoin
98. and a volatile coin.
99. The latter is an asset
100. that confers some sort of a financial benefit,
101. on its holder like interest or dividends,
102. but is not price-stable.
103. You then have a smart contract that receives signals
104. from a price feed and offers to exchange appropriate amounts
105. of stablecoins for volatile coins and vice versa,
106. thereby shrinking or expanding money supply.
107. While avoiding use of external assets
108. can bring significant benefits, the trade-off here
109. is reliance on very strong behavioural assumptions,
110. leading to questions about stability
111. and proneness to death spirals.
112. In December of 2018,
113. US regulators placed severe restrictions
114. on algorithmic issuance of volatile coin-like securities,
115. forcing a number of projects to rethink their mechanism.
116. No stablecoin of this type has been launched to date.
117. Feron Labs works on distinct approach
118. within the uncollateralised category.
119. We do not define stability relative to an external asset,
120. or set an absolute price target.
121. It is a single-coin model that consists
122. of a native algorithmic central bank
123. that offers users a range of riskless deposits.
124. This opportunity to earn a riskless return attracts
125. a significant portion of the system’s speculative liquidity.
126. When price expectations decline
127. and users want to sell their coins,
128. they will first need to withdraw them from deposits.
129. As the central bank detects increased outflows of capital,
130. it sharply raised interest rates,
131. offering a strong incentive to keep coins on deposit.
132. Thus, liquidity is prevented from reaching exchanges
133. and turning into sell orders, alleviating price pressure.
134. In effect, price volatility
135. is turned into the more benign interest rate volatility.
136. So what is the ultimate goal of stablecoins?
137. Arguably, it is creating a model that can function
138. as fully self-sovereign money
139. – money that is just as usable as conventional currency,
140. but one that you, as the holder of the encryption key,
141. truly own and control.
142. It would be money that no institution
143. can take away from you.
144. Every transfer from your account would occur only if
145. and when you give it your consent.
146. In a way, it is the original Bitcoin dream,
147. and Bitcoin’s early popularity
148. has shown that it is a widely shared one.

Legal and Regulatory Implications of Cryptocurrencies (King & Wood Mallesons)

1. Cryptocurrency is
2. one of the most over-hyped terms of our generation.
3. Cryptocurrency is also a bit of a misnomer.
4. Very few cryptocurrencies
5. operate in any way that resembles
6. fiat or real central bank-backed currency.
7. None are recognised in Hong Kong
8. as currency or money.
9. So some people like to call them virtual commodities,
10. cryptographic tokens or digital assets,
11. which are far more neutral,
12. but we’ll stick with cryptocurrencies today.
13. Let’s take a step back.
14. What we typically mean
15. when we talk about cryptocurrencies
16. is a record of some kind of right,
17. typically on a blockchain.
18. That right can be transferred peer-to-peer,
19. or via an exchange.
20. It’s incredibly secure,
21. but generally it’s not anonymous.
22. It’s pseudonymous.
23. So what does a cryptocurrency do?
24. What is it?
25. It entirely depends on
26. what right travels along that blockchain
27. as ownership passes from one person to another.
28. In some cases, that right is really limited,
29. particularly for cryptocurrencies like Bitcoin.
30. In other cases, it could give you a profit,
31. or even represent a share in a company,
32. could be a loyalty point or help you
33. make payments across the world.
34. The combination of blockchain
35. and smart contract technology,
36. on platforms like Ethereum,
37. as well as many others,
38. has made the creation and trading of these rights
39. incredibly efficient and lucrative
40. as an early stage funding tool,
41. a bit like what Kickstarter was
42. for physical products.
43. However, there is often a misconception
44. that new technology,
45. especially when it lives and breathes online,
46. and particularly when it is decentralised,
47. is not subject to any laws.
48. It lives in the cloud, so no laws apply.
49. This couldn’t be further from the truth.
50. In fact, it typically means
51. that much more law applies,
52. and it often overlaps and sometimes even conflicts.
53. At the crux is what is the right
54. that I am recording on the blockchain?
55. And this can have
56. a number of legal and regulatory implications.
57. However, the key things you need to look at
58. are financial regulatory laws,
59. such as restrictions on selling securities.
60. In Hong Kong,
61. an important part of the definition of securities
62. includes collective investment schemes,
63. which is a very broad concept
64. and exists in many jurisdictions.
65. It can capture a wide range of arrangements,
66. but in essence, it generally refers
67. to where you draw money in
68. to generate profit for participants.
69. In some countries, the securities definitions
70. are so broad and flexible
71. that they can adapt
72. based on market behaviour and intent.
73. The United States is a great example of that.
74. In others, more law is emerging
75. that expands the securities regimes.
76. And in others such as Mainland China,
77. total bans are in place for ICOs,
78. but not necessarily blockchain-based shares
79. and other instruments.
80. Certain cryptocurrencies are regulated in other ways.
81. For example, a gambling chip on a blockchain
82. is still a gambling chip.
83. An exchange selling cryptocurrencies that are securities
84. is still a securities exchange that requires a licence.
85. A blockchain that records
86. and transmits personal data,
87. is still regulated by privacy laws.
88. In certain countries,
89. cryptocurrencies are also treated like currency,
90. which carries a lot of other consequences.
91. But there are numerous other laws applied,
92. such as contract and fraud.
93. So if someone lies to you in an offer document,
94. or over-promises on something
95. that they cannot deliver,
96. you could potentially sue them.
97. And we are already seeing a number private actions,
98. and in some countries even class actions in this space.
99. Tax and anti-money laundering laws also apply.
100. The greater issue is how these laws interact.
101. Blockchains typically exist in multiple countries,
102. because their records are
103. duplicated in different servers
104. in different parts of the world.
105. So extreme care is required in creating them,
106. and we’ll see a lot more interesting law
107. develop to resolve laws that collide.

Industry Showcase (NEW): Behaviour Analysis and Valuation of Cryptocurrencies (Santiment)

1. Hello, my name is Maksim,
2. and I’m a Founder and CEO of Santiment.
3. Our goal as a company is
4. to give our users 360 degree overview
5. of the entire crypto market
6. and its biggest driving forces.
7. Now, since crypto markets are so novel,
8. and the technology behind it so unique,
9. I believe we can no longer rely
10. just on the traditional metrics and fundamental data.
11. So what do we do at Santiment?
12. We supply our users with terabytes of
13. related data
14. for the cryptocurrency from various sources.
15. What are the sources?
16. For instance, we gather data
17. directly from the blockchains,
18. like Bitcoin, Ethereum, and so on.
19. Or we get social data about the project
20. taken from Reddit, Twitter, telegram channels
21. or even from some specific forums
22. like Bitcoin Dock.
23. We also gather developer activity
24. data for crypto projects,
25. from say, GitHub repositories.
26. And then, we don’t stop here.
27. We also build custom metrics from this data,
28. to visualise different market behaviours.
29. Today, I’ll show you a few of these metrics
30. that probably no one else has shown you before.
31. And first, for the quick disclaimer,
32. I’m not an financial advisor,
33. and nothing I share with you today
34. should be taken as direct investment advice.
35. It is just to give you real-life data
36. to show the case.
37. The crypto market has been in a long term,
38. like more than one year,
39. bear market, or a correction.
40. Some people call it correction.
41. Valuing crypto assets is a very challenging task.
42. For, such as most tokens or coins,
43. are supposed to have a primary purpose,
44. more than just trading,
45. like to have to be some utility.
46. Unfortunately, as it’s still not the case,
47. majority of the projects struggle in this mass adoption,
48. and it is very focused on the crypto community,
49. and the use of the tokens are still mostly speculative,
50. and this situation can be very hard to accurately
51. valuate a crypto asset.
52. From market projections or valuations,
53. you can see more clearly,
54. and in the lifetime, what’s happening to the project.
55. Just like in traditional markets,
56. when humans deal with things of value,
57. they become greedy or they can experience fear,
58. like in crypto we call it FOMO,
59. fear of missing out,
60. but they rarely stay put
61. and act rationally.
62. In the crypto, as interactions
63. get recorded on the blockchain,
64. so, whenever people act,
65. everything’s recorded on blockchain,
66. and it’s a unique chance, the first time in history,
67. then we can analyse,
68. and this data is available to everyone.
69. It’s just a question how you
70. gather and package together.
71. So let’s start with some examples,
72. and the first example will be
73. of how metric is so-called MVRV Ratio.
74. MVRV Ratio, it’s calculated by dividing
75. Total Market Cap by so-called Realised Cap.
76. And the Realised Cap, it’s a very unique measurement.
77. It’s total acquisition cost,
78. or the total amount of money
79. that all token holders paid
80. for the tokens they currently hold in their wallets.
81. And the ratio between current market value
82. and acquisition cost is MVRV Ratio.
83. So here is a MVRV Ratio for Bitcoin.
84. The ratio itself is in yellow,
85. and the price is in green.
86. As you see, in the moment,
87. the MVRV is less than one,
88. actually around zero, comma, 85,
89. which means there’s a current valuation,
90. of the entire network,
91. is less than the amount the token holders paid for it.
92. Think for a moment.
93. It’s kind of irrational.
94. People paid more what market now values as the price,
95. but this is the reality,
96. and this is not the first time.
97. Looking back in the history,
98. you can see on the chart,
99. and we saw MVRV fell below one
100. at the end of 2014,
101. when the Bitcoin dived below 300,
102. and stayed there for actually quite long time,
103. almost one year,
104. and in the range of
105. between 200 and 300 dollar per Bitcoin.
106. As we know now,
107. that time was perhaps
108. one of the best accumulation periods.
109. So if you believe, and we do believe,
110. that crypto markets are in a cyclical mode,
111. similar to traditional markets,
112. here again, we need to remember
113. the cycles in cryptos are much faster and tighter,
114. MVRV right now, dived below one,
115. somewhere back in November,
116. 2018, when the Bitcoin went below,
117. all the way down to three and a half thousand.
118. If we believe market cycles,
119. and we see the cycle appearing,
120. alone, this metric can give you
121. much deeper insight and understanding
122. of behaviour of the crypto currency,
123. token like Bitcoin.
124. And they have this metric, actually,
125. for other coins too.
126. Now, let’s look at some other metric.
127. We call it Ethereum Miners Statistics.
128. It’s a completely new way
129. to measure the behaviour of network participants.
130. You will never find it in traditional finance.
131. This chart illustrates activity
132. of Miners of the Ethereum network.
133. The green line is the price, again,
134. is newest dollar per Ethereum token,
135. and the red line is a total balance
136. of all Ethereum Miners.
137. It means how much Ethereum tokens
138. they hold in their balances.
139. Now, if you look carefully, you will see that,
140. after year of stagnation in a long bear market,
141. the market changed,
142. and the price of Ethereum started to increasing
143. back in 2017.
144. Now, typically, when that happens,
145. a rational person would think,
146. “Oh. price is increasing, of course,
147. so I’ll keep it; I will become rich,”
148. but this is not how the human mind works.
149. You’ve experienced one year of depression,
150. and one year of suffering,
151. and you’ve seen your money,
152. like, decreasing in value,
153. so the first direction,
154. how you emotionally do,
155. emotion like irrational,
156. and this describes your behaviour,
157. you’ll start selling, and dumping,
158. like to get some money back.
159. And you see it on the chart
160. directly how it happens.
161. The price starts increasing,
162. but the Ethereum Miners holdings are decreasing,
163. and it happens for some time, actually,
164. for three or four months.
165. Well I call it,
166. and it is actually a quite known term,
167. there is so-called Wall of Worry.
168. Wall of Worry, where market grows in value,
169. but people still don’t believe in it.
170. But few months later,
171. the price still keeps rising,
172. and you see, the Miners were like,
173. “Wow, now I guess it’s something for real,”
174. and their holdings start increasing,
175. from some specific point of time.
176. If you’ll very carefully look at the chart,
177. you’ll see that’s exactly the time when
178. the price of Ethereum coin
179. has some kind of lost and dropped.
180. And after this, when it start increasing,
181. their holdings for Ethereum Miners were increasing.
182. This is the moment of recognitions.
183. The whole market recognised
184. there is something really big going on,
185. and ever since I see the chart,
186. the holding of Ethereum Miners only increasing.
187. So, as you can see,
188. Santiment data can be used by anyone
189. who wants to understand
190. how crypto markets work,
191. how human natural participants
192. react to market changes,
193. and it’s both educational and pragmatic.

2.9A What is Blockchain? (Part 1)

1. Cryptocurrencies, blockchain, ICOs.
2. These are three terms
3. that are in the headlines daily all over the world.
4. Blockchain is the underlying technology
5. which came to prominence with
6. the launch of Bitcoin in 2009,
7. but what is blockchain?
8. Blockchain combines two long-standing
9. technological developments.
10. On one side, distributed ledger technology,
11. and on the other, cryptography.
12. If we look at Bitcoin, if we look at cryptocurrencies,
13. cryptocurrencies at their base
14. are blockchain systems combining
15. distributed ledger systems and cryptography.
16. Distributed ledger system,
17. what is a distributed ledger system?
18. For a system like Bitcoin,
19. the distributed ledger
20. means that the information in the system
21. are not stored in one single place.
22. Rather, they exist in multiple locations,
23. multiple identical ledgers
24. throughout the users of the system.
25. So, if we think about this idea of ledgers,
26. the traditional example is to think
27. of something like a bank.
28. A bank is a place where
29. a certain amount of money is stored,
30. it is a single place,
31. it is a silo, it is a single ledger.
32. At the other extreme, are distributed ledgers.
33. Distributed ledgers mean that there is no single place
34. where the information, the valuables,
35. the data are stored,
36. rather they are stored
37. across a variety of identical locations.
38. In between these structures of
39. centralised and distributed,
40. we also have network-based structures
41. where perhaps you have a single centralised structure
42. and a variety of spokes,
43. a hub and spoke structure
44. whereby the individual spokes connect to the hub.
45. So, distributed ledger technology
46. combined with cryptography.
47. Cryptography is a technology that involves
48. the secure storage,
49. the encryption of information.
50. It has a very long history with important points
51. going back to code breaking,
52. particularly in the Second World War.
53. If we combine distributed ledger technology
54. with cryptography, we have a system
55. of secure distributed ledgers
56. where entries have to be proven,
57. proven through the use of a variety of structures
58. which then encrypt the data into blocks.
59. So, transactions 1 through 50,
60. packaged in a block, encrypted together.
61. The next set of transactions build on that first block,
62. transactions 51 through 100
63. encrypted as a second block.
64. This structure provides
65. a number of very important attributes
66. to a blockchain-based system.
67. In particular, it provides for security.
68. The layers of cryptography across multiple blocks
69. make it very hard, but importantly not impossible,
70. to necessarily break those blocks
71. making blockchain potentially a highly secure system.
72. Second, it’s a permanent system.
73. In other words, each of those transactions
74. is recorded permanently in each of those blocks.
75. That means that there is always a traceable history
76. of all of the financial transactions
77. going back to the very beginning.
78. So, with each Bitcoin,
79. you can trace back the life of that Bitcoin
80. from it’s creation and into each account
81. that it has been transferred to over time.
82. And finally, transparency.
83. Transparency means that the combination of visibility
84. allows you to see what is happening in the blockchain.
85. This combination of security, permanence,
86. transparency, makes blockchain a potentially
87. very powerful platform technology
88. across a number of areas.

2.9B What is Blockchain? (Part 2)

1. Now, if we look at blockchains,
2. within this general structure
3. we will often have a third level added.
4. So, DLT plus cryptography plus smart contracts.
5. What are smart contracts?
6. Smart contracts are automated systems
7. that on the occurrence of pre-determined actions
8. something else happens.
9. If I provide A, you provide B
10. we pre-agree that A and B will be added together
11. to create a new C,
12. and this occurs on an automatic basis,
13. this is a smart contract.
14. There is an old joke that smart contracts
15. are neither smart nor contracts,
16. they are not smart because they are automated,
17. they happen automatically,
18. on the occurrence of something / events.
19. And they are not necessarily contracts,
20. but that is a more complicated legal question for later.
21. Within this idea of blockchain,
22. we can also add in a second important determination.
23. Blockchains can either be
24. permissionless, or permissioned.
25. A permissionless blockchain, like bitcoin,
26. means that it is open,
27. anyone can participate that downloads the software.
28. You download the software, you become a node,
29. you’ll have a full picture of the ledger,
30. that distributed ledger is distributed to your node,
31. anyone can enter.
32. But, we also have what are called
33. permissioned blockchains.
34. A permissioned blockchain,
35. involves requirements or governance structures
36. or restrictions on entry.
37. In other words, only individuals or organisations
38. or computers or devices which have been pre-approved
39. can join into the network,
40. can access the information
41. and can potentially contribute transactions.
42. Now, when we think about blockchain,
43. it may or may not involve cryptocurrencies.
44. A cryptocurrency will involve a blockchain,
45. but a blockchain does not necessarily
46. involve a cryptocurrency.
47. In other words if we think of a blockchain based system
48. at its base, it is a distributed ledger
49. which is encrypted, maybe with an additional layer
50. of smart contracts on top.
51. Those individual data entries, can be anything.
52. The communications between those data entries
53. do not necessarily involve any sort of currency.
54. One of the most interesting and powerful applications
55. for this sort of thing,
56. is in production processes,
57. the food market where the providence of a chicken,
58. or a bottle of whiskey
59. can be proven by the blockchain system
60. from its creation, its history, its movements
61. documented throughout that system.
62. So, any eventual possessor
63. can document both the origin
64. as well as the lifespan of that particular chicken,
65. bottle of whiskey, diamond, artwork,
66. whatever it may be.
67. And that is the real power of blockchain.
68. To build systems
69. which are potentially highly secure,
70. permanent and highly transparent.
71. But, blockchain is not the solution
72. for every problem, why?
73. Because not every blockchain is created equally.
74. not every blockchain is necessarily secure.
75. Big blockchain systems like Ethereum or Hyperledger
76. or R3’s quarter, or bitcoin,
77. these are highly secure.
78. But if I create a blockchain in my basement,
79. probably not that secure.
80. Just because it’s a blockchain, doesn’t mean it’s secure.
81. Second, from the standpoint of
82. permanence and transparency,
83. this raises two problems.
84. One, is the garbage in, garbage out problem
85. in other words if you put that information in,
86. it’s in there forever, and that is a big problem
87. in the context of building histories,
88. building information, the permanence problem.
89. And finally, privacy concerns.
90. If information goes into,
91. a permissionless public blockchain,
92. that information may be permanently
93. on public display and access,
94. and this can create all sorts of problems
95. in that not necessarily do we want
96. every piece of information permanently on view.
97. So, looking at blockchain,
98. and this is something that we talk about
99. a great deal throughout this course,
100. and in other courses.
101. Blockchain is a very important technology,
102. being used across all aspects
103. of the financial sector and beyond.
104. But it’s not the solution for every problem,
105. but it is giving us an excuse to re-look,
106. to reconsider many of our existing systems
107. and infrastructure to build better systems.

Additional Video Resources: Blockchain

1. Meet Corda: DLT with a difference (www.corda.net)  (2.1 Mins)

2. Corda Overview (Richard Gendal Brown, Chief Technology Officer of R3) (2.5 Mins)

3. Bridging the FinTech Gap – An Update on R3 and Blockchain Developments (Tim Grant, CEO of R3 Lab and Research Centre) (27.2 Mins)

Industry Showcase: The Benefits from New Payment Stacks – Applications of Ripple for Standard Chartered Bank

1. Standard Chartered Bank
2. believes in using new and advanced technologies
3. to bring a better experience to our clients.
4. Since our first collaboration with Ripple
5. in December 2015,
6. we have made significant progress
7. in enhancing the overall security
8. of trade finance invoicing through the adoption of
9. distributed ledger technology.
10. We, together with Axis Bank,
11. launched a cross-border payments platform in 2017
12. which connects corporates
13. between Singapore and India.
14. Ripple allows Standard Chartered
15. to provide our clients real-time payment services
16. with visibility, traceability and full transparency.
17. With all transacting parties
18. connecting to the same blockchain network,
19. customers are able to process payments in real-time
20. with end-to-end tracking,
21. pre-validated transaction,
22. and see all the fees upfront.
23. It helps reduce the risk of late payment
24. as well as to provide certainty
25. as to when and how much of the money
26. would arrive at the beneficiary.
27. As blockchain records cannot be altered
28. once they are created,
29. the technology helps
30. financial institutions’ reconciliations of payments,
31. improve working capital allocations
32. and reduce the amount of time
33. back-office staff spent handling errors.
34. Standard Chartered has been using Ripple’s solution
35. in many parts of its business,
36. including global trade payments,
37. e-commerce payments,
38. international payroll and pensions,
39. and international corporate dividends.
40. Whether it is a global supply chain
41. doing real-time cross border transactions,
42. a corporate selling goods globally over the Internet
43. or an international firm paying salaries
44. to its overseas employees,
45. Ripple makes payment easier, faster,
46. and more efficient than ever before.

Additional Resource Insights

A. References and Suggestions for Further Reading

1. FinTech and Financial Services: Initial Considerations (Industry Report – IMF)  
2. Blockchain Beyond the Hype – A Practical Framework for Business Leaders (Industry Report – WEF)    
3. Bank of Russia suggests FinTech’s ethereum blockchain as single system for EAEU (News Article – Tass Russian News Agency)
4. The Distributed Liability of Distributed Ledgers: Legal Risks of Blockchain (Academic Paper: Zetzsche, Buckley, Arner)

B. Additional Resource Insights for Video 2.4 Regulation of Mobile Money

1. FinTech in Developing Countries: Charting New Customer Journeys (Academic Paper: Buckley, Webster, 2016)
2. Building Consumer Demand for Digital Financial Services – The New Regulatory Frontier (Academic Paper: Malady, Buckley, 2014)
3. Using Trusts to Protect Mobile Money Customers (Academic Paper: Greenacre, Buckley, 2015)
4. Protecting Mobile Money Customer Funds in Civil Law Jurisdictions (Academic Paper: Muñoz, Solana, Buckley, Greenacre, 2015)

Module 3 Alternative Finance

Welcome to Module 3

3.1 Module 3 Introduction

1. Hi, my name is Brian Tang,
2. and I’m the founder of
3. Asia Capital Markets Institute based in Hong Kong.
4. I’ve been a corporate finance lawyer for nearly 20 years,
5. having worked in New York and California
6. during the dotcom period
7. at Wall Street firm Sullivan & Cromwell,
8. as well as, at Credit Suisse
9. where I worked on some of the largest
10. and first-of-its-kind transactions.
11. These included the IPOs of CCB and ICBC,
12. the privatisation of alibaba.com
13. and the setting up Credit Suisse’s investment banking
14. joint venture in China.
15. And since I was in Silicon Valley,
16. and now at a FinTech-focused startup,
17. I think I can just lose the tie.
18. Alternative finance, according to the
19. Cambridge Centre for Alternative Finance,
20. can broadly be described as
21. comprising financial channels and instruments
22. that emerge outside the traditional financial system.
23. In my chapter in The Fintech Book,
24. which has recently been translated
25. and published in China,
26. I have called some of these emerging
27. financial channels, online capital marketplaces.
28. Alternative finance can also refer
29. to the new investment classes
30. being sought to be created,
31. including equity and loans to SMEs,
32. and more recently, crypto assets.
33. In this module, we will discuss the following.
34. First, a brief history of finance and its innovations.
35. Second, the digitization of financial services.
36. Third, the opportunities and challenges
37. of distributed peer-to-peer models of finance,
38. such as crowdfunding,
39. marketplace lending and token sales.
40. Fourth, the rise of the Chinese TechFins
41. in its new models and products.
42. And five, how the banks are now positioning themselves
43. as technology companies.

Module 3 Learning Objectives

Module 3 addresses the digitization of finance and investment and the development of alternative finance and investment mechanisms, including P2P lending, crowdfunding and initial coin offerings (ICOs).

In Module 3, learners will:

• Understand the digital transformation of traditional securities and investment markets over the past 30 years.
• Consider the major forms of technology impacting finance today.
• Analyze the evolution of major forms of alternative finance, including P2P and marketplace lending, crowdfunding and initial coin offerings (ICOs).
• Learn about new business models, particularly the impact of technology firms entering into finance.

3.2 A Brief History of Financial Innovation

1. Finance can and should be
2. an enabler of commerce and investment
3. in growing the real economy
4. as well as to provide individuals
5. with more personal security
6. against life’s vicissitudes.
7. Money or currency consists of
8. a stored value instrument that is scarce.
9. Throughout the ages,
10. these have ranged from cowry shells
11. to gold and minted metal coinage.
12. In the west,
13. money lenders have existed since the Roman Empire
14. where individuals have made
15. private loans to those who needed it.
16. There has long been widespread
17. religious and moral condemnation against usury.
18. The charging of interest for loans
19. with different religions taking different stances
20. on the permissible extent of such interest.
21. For example, the Islamic faith prohibits
22. any charging of interest whereas
23. the Judaic faith permits charging interest to non-Jews.
24. Modern legislation focuses more on setting limits
25. on the amount of permissible interest set.
26. Florence sat at the centre of the Renaissance
27. due in part to the extensive trade
28. through the Italian city
29. leading to over 100 banks being there
30. by the end of the 14th Century.
31. The Medici banking empire
32. was one such example
33. and was the banker for the Catholic Church.
34. Its expansion was aided by the invention
35. of double-entry bookkeeping by
36. Franciscan friar, Luca Pacioli
37. which allowed for reliable documentation
38. for both creditor and debtor.
39. The important role of ledgers
40. will be revisited with the advent
41. of blockchain technology in this century.
42. The Tang and Song Dynasty emperors
43. in the seventh century started using paper
44. which their forefathers in China invented
45. as bank notes or jiaozi,
46. that were originally used as promissory notes
47. and became a lightweight alternative
48. to heavy and metallic coinage.
49. To address counterfeiting,
50. a variety of techniques involving different inks,
51. papers and seals were used.
52. Property and being able to prove ownership
53. is critical as sources of collateral for finance.
54. Pawn shops such as the medieval practise
55. of so-called Lombard banking
56. dealt in the delivery of goods and custody
57. and many legal jurisdictions developed
58. centralised land record registries
59. that enabled more lending to take place.
60. As international trade grew,
61. the financing of those ocean expeditions
62. of vast durations and distances
63. involved substantial risk.
64. With the invention of the joint stock company
65. shares and bonds could be
66. issued to the general public to fund projects
67. and the Dutch East India Company
68. listing in the Amsterdam Stock Exchange
69. paved the way in the 17th Century.
70. Similar venues were set up across the ocean
71. at coffee shops along London’s exchange alley,
72. and under a buttonwood tree on Wall Street,
73. and sea captains and merchants also met
74. at Lloyd’s Coffee House at London’s Tower Street.
75. These soon evolved into powerful institutions,
76. today’s London Stock Exchange,
77. New York Stock Exchange
78. and Lloyd’s of London
79. with impressive architecture to reflect their influence.
80. Within these buildings,
81. trading runners or deer would dash to
82. nearby brokerage offices
83. to deliver stock quotes
84. from the brokers on the exchange floor.
85. With the invention of electricity,
86. technologies like the telegraph
87. and then the telephone soon meant
88. proximity to the exchanges proved less critical.
89. In 1971, Nasdaq became the first electronic exchange
90. with many other securities and
91. commodities exchanges following suit.
92. A new electronic and digital era was dawning.

3.3 Digitization of Financial Services

1. Financial investment and trading
2. can best be understood as
3. comprising of two groups.
4. First, retail investment and trading
5. of public companies is conducted
6. by the general public on exchanges
7. through brokers and dealers.
8. Second, institutional investment and trading
9. involves large financial institutions
10. who buy and sell publicly listed securities
11. between each other.
12. In the meantime,
13. the investment into private companies
14. has been the remit of specialised investors,
15. such as venture capital and private equity firms,
16. with so called exit or liquidity events
17. being an initial public offering
18. into the public markets
19. or trade sale of the business.
20. The venture capital firms
21. on Sand Hill Road in Menlo Park, California,
22. were likely instrumental in investing and growing
23. what become known as Silicon Valley.
24. Including their successes in hardware
25. being turned into software and the internet
26. that gave rise to the dot com boom.
27. One major development at that time
28. was when online brokerage firm E*Trade
29. was able to get allocations
30. to some of the hot tech IPOs.
31. Electronic banking also started expanding
32. as major banks extended services to consumers
33. who were increasingly coming online
34. with the lowering costs
35. and increasing ease of access.
36. At the same time,
37. institutional trading expanded dramatically,
38. with alternative trading systems and dark pools
39. allowing financial institutions to trade
40. large blocks of securities at one time
41. to minimise pricing impact.
42. At the same time,
43. proprietary trading at desks invested and develop
44. automated algorithmic trading programmes,
45. as well as high frequency trading programmes
46. that use computational power
47. to devise trading strategies
48. and automate trading in ways no human could.
49. The global financial crisis in 2007
50. changed the landscape dramatically.
51. After the bursting of the sub prime mortgage bubble,
52. and the rapid devaluation of financial instruments,
53. such as mortgage backed securities
54. and credit default swaps,
55. many major financial institutions collapsed,
56. or needed to be bailed out by their governments.
57. Lending then dried up by many traditional lenders,
58. and many governments sought to encourage
59. the emergence of new players and business models
60. that provided alternative finance
61. to individuals and businesses.
62. At the same time,
63. 2010’s flash crash
64. saw the Dow Jones Index drop
65. nine percent within minutes
66. and was subsequently attributed
67. to high frequency traders initialling,
68. spoofing algorithms
69. that placed thousands of orders
70. with intention of cancelling them.
71. The automatic shutting down
72. of many automated computerised traders
73. due to the extreme drop
74. also led to a rapid loss of liquidity.
75. In the European Union,
76. challenger banks were encouraged
77. and has culminated
78. in open banking policies such as
79. the payment services directive,
80. which forces banks to produce customer data
81. to make it easier for customers
82. to switch financial providers.
83. Some of these banks were also virtual banks,
84. with no branches at all.
85. In the United States,
86. a stark reminder that
87. it was not business as usual
88. can be seen in the before and after pictures
89. of UBS’s famed trading floor in Stanford, Connecticut.
90. This was once the largest in the world
91. with 5,000 stock, bond and currency traders.
92. The global financial crisis resulted,
93. amongst other things,
94. in the passing of Dodd-Frank,
95. which prohibited proprietary trading by banks,
96. and the Jump Start Our Business Startups Act,
97. or JOBS Act in 2012,
98. which legitimised the concept
99. of equity crowdfunding in law.
100. The era of distributed peer-to-peer models
101. of finance was born.

3.4 FinTech and Funds

1. As we all know, FinTech is really disrupting
2. many verticals of the financial services industry,
3. from investment banking,
4. asset management, retail banking.
5. But one area that it’s also affecting as well
6. is the hedge fund industry.
7. For many years, the hedge fund industry
8. was the most entrepreneurial,
9. at the cutting edge of technology.
10. And obviously, a lot of Fintech innovations
11. are benefiting the broader hedge fund industry as well.
12. There’s many examples.
13. Think about it.
14. Imagine I’m a fund manager.
15. Normally I try to access data
16. that is available publicly
17. and I’m trying to use.
18. But what if I can use some of the big data analytics
19. and artificial intelligence solutions
20. to try to really generate insights?
21. Imagine using satellite imagery to try to look at
22. what’s happening on, let’s say, on oil containers
23. and how much oil there are on the ships.
24. Or actually looking from satellite imagery
25. how many cars are in the parking lot
26. and use that to try to actually forecast
27. a company’s actually earnings.
28. Or imagine being able to use
29. some of the latest technology to read,
30. go through all the news articles
31. around the world available online
32. or all the tweets and Facebook messages
33. and be able to come up with a sentiment analysis
34. of what are people really seeing
35. and thinking around the world.
36. Well, what’s really interesting as well,
37. that’s one example
38. but there are many other examples.
39. For example, today a lot of people
40. want to get access to research.
41. A normal hedge fund manager would actually try
42. to work with an investment bank,
43. will actually execute some of their traits
44. via an investment bank to get access
45. to some of their research analysts.
46. But if you think about it,
47. it’s not very efficient.
48. It’s a bit like buying a CD if you like one song.
49. What now we’re seeing the emergence
50. of independent platforms.
51. If you think about the Spotify of research
52. where investment analysts can actually go there,
53. put your own research.
54. And if customers like them,
55. they just go pay for the research and pay
56. for that specific investment analyst.
57. A bit like if there is a particular song or artist
58. that you like on Spotify and
59. you actually want to listen to their music.
60. But in many cases we are seeing
61. really the FinTech industry transform
62. how business was currently done.
63. Let me give you an example.
64. Let’s say I want to launch a quant fund,
65. a quantitative trading fund.
66. Today I have to rent the office space,
67. hire a couple of PhDs who’ll do research
68. and build my team together with me in one location.
69. That is a great way but doesn’t really give you access
70. to the best talent in the world.
71. What if you can actually crowd source
72. and actually crowd fund
73. and be able to get access
74. to talent from all around the world?
75. Some of the best PhDs or quant traders
76. from around the world and try to get their models
77. that you can actually use.
78. Well, we are seeing some players do exactly just that.
79. Well now you can launch a quant fund
80. where you going to get some of the best people
81. from all around the world
82. to actually submit models.
83. And if the model is quite successful,
84. give them portions of the revenues made.
85. Doesn’t matter if you are in Santiago, Chile,
86. in Moscow, Russia or in Singapore, Hong Kong.
87. You can have as much of a chance of
88. being discovered from a talent perspective.
89. But also it’s affecting,
90. FinTech is affecting the way business is done.
91. Today, anybody launches a hedge fund or a fund,
92. will generally try to go raise money from investors.
93. That service is now offered by investment banks
94. who will try to match hedge fund managers
95. and hedge fund investors.
96. The way that process works is very inefficient.
97. Often via conferences and
98. personal meetings or emails,
99. it’s actually not very efficient.
100. We are now seeing the emergence of online platforms
101. where these two branches can actually connect.
102. And actually you have analytics
103. and data on who can be a good fit for each other.
104. So as you can see there’s a lot of,
105. really lots of really exciting and interesting innovations
106. taking place in the FinTech world
107. that are also affecting, impacting positively,
108. in certain cases negatively the hedge fund industry.
109. Definitely an area to watch.

Industry Showcase: How AI is Transforming the Future of FinTech (Microsoft)

1. Hi, everyone. This is Delon.
2. I’m a Technical Evangelist
3. from the Commercial Software Engineering team,
4. from Microsoft.
5. Today, I’m here to present to you
6. how AI technologies
7. and big data analytics could integrate
8. with your FinTech technologies.
9. Smarter computers, algorithms,
10. and dedicated AI systems
11. enable smarter decision-making,
12. deeper learning.
13. For example, recognise predictors
14. of financial turbulence.
15. And the combination of artificial intelligence
16. and big data,
17. allow us to understand better how people,
18. how they spend the money, their health,
19. as well as the lifestyle.
20. For example, intelligent banking.
21. It is all based on the “always on” customer,
22. and predicting his or her financial needs
23. at a certain point of time.
24. Thus, it’s not just about the bank,
25. but providing products and services
26. through one channel,
27. a single interface that can maximise
28. your customer experience,
29. and hence centricity.
30. However, building those trusts from your customers
31. is still one of the biggest challenges for FinTech.
32. And in Microsoft, we are trying our best
33. to gain and build lots and lots of trust
34. from our customers.
35. And here are a few examples:
36. If P&C Insurance is a world-leading
37. property and casualty insurance company
38. that serves over 3 millions of customers
39. in the Nordic region,
40. if actually leveraging our Cortana Analytics Suite
41. to perform Churn analytics.
42. In other words, predicting whether their customers
43. will cancel the policy in a 40-day window
44. surrounding the renewal dates.
45. Another example is that,
46. actually they’re doing upsell prediction.
47. Basically, finding the probability of success
48. of upsell communication to a given customer.
49. Last but not least,
50. they are applying text analytics algorithms
51. on their inbound emails from their customers.
52. So, they could now better understand their customers,
53. classify those emails,
54. and better serve their customers.
55. Another example is Novum Bank.
56. Novum Bank will like to
57. assess the credit-worthiness of their customers.
58. Especially in the poor credit information markets.
59. With Microsoft, they actually built
60. an automated psychographic credit-scoring engine,
61. running on Azure, for onboarding.
62. In return, the acceptance rate was increased by 18%,
63. and they actually rejected
64. bad customers.
65. Finally, I will like to share with you one more example.
66. CallCredit, one of the UK’s largest
67. credit reference agencies.
68. They’re actually leveraging Azure machine learning
69. to identify criminals who pretend people
70. to access credit reports, and borrow money.
71. With all these machine learning and AI tools,
72. CallCredit can now proactively spot people
73. who will actually fail to pay back their loans.
74. Most importantly, our machine learning model
75. could advise their lenders
76. on how to make much more accurate decisions.
77. So, these are some of the examples how we integrate
78. big data analytics, AI technologies,
79. with FinTech solutions.
80. Hope you get some insights from this session,
81. and hope you enjoyed it.

Industry Showcase (NEW): How Will AI Transform Financial Analysis? (MioTech)

1. Today, we will be discovering how artificial intelligence
2. will transform financial analysis.
3. I am Tao,
4. I am the co-founder and CTO of MioTech.
5. MioTech is a startup that provides intelligence analysis
6. for financial institutions.
7. Artificial intelligence will dramatically
8. change the way financial institutions analyse risk
9. and investment opportunities.
10. Firstly, thanks to the breakthrough of deep learning,
11. multiple basic artificial intelligence algorithms
12. have greatly improved,
13. including natural language processing,
14. image processing, and speech recognition, etc.
15. Natural language processing
16. is one of the most important topics.
17. Nowadays, computers can understand the syntax
18. and extract entities more accurately.
19. There has also been huge progress
20. in relationship extractions and sentiment analysis.
21. Let’s take one sentence as an example.
22. We can see that the algorithm can understand
23. both the syntax and semantics.
24. Google and Mountain View are defined
25. as an organisation and a city.
26. MioTech used our in-house model to extract topics.
27. By analysing daily online narratives,
28. we can extract different kind of topics,
29. like product release, buyback behaviours, etc.
30. Also we can analyse the impact
31. of each event in real time.
32. Image processing has also greatly improved.
33. Problems like classification,
34. feature extractions, and pattern recognition,
35. are reaching to new levels.
36. By using this technology,
37. we can easily process the satellite image
38. and know the progress
39. of 5G infrastructure construction.
40. MioTech has been using this technology
41. to understand the operation
42. of harbour and oil rig activities.
43. Secondly, with more and more data accumulated,
44. analysis based on a small sample
45. will change to a full set analysis.
46. The most obvious example
47. is the development of anti-fraud.
48. Currently, there are thousands of people
49. in large banks who are responsible
50. for checking the legality of transactions.
51. Although it is one of the biggest departments in a bank,
52. only a small proportion
53. of the transactions can be analysed.
54. However, AI can learn the way criminals commit fraud
55. in a short period of time,
56. with all the transactional data,
57. and be able to make real-time decisions.
58. Humans only need to review the results
59. and make a final decision afterwards.
60. In the meantime,
61. the algorithm can find the new pattern much faster.
62. Paypal and Alipay are already using this technology
63. to prevent financial fraud.
64. To commit financial fraud online
65. will only get harder and harder from now on.
66. Individuals and companies are
67. generating a huge amount of data every day,
68. so relying on humans for analysis
69. will no longer be feasible
70. and the ability to process the data
71. will determine how well financial institutions
72. can provide their services.
73. Take MioTech as one example.
74. We are processing over 100 gigabytes of data every day.
75. And we maintain a knowledge graph
76. of over one billion level entities
77. and their relationships.
78. Companies are using us
79. to predict risk in real time.
80. To give one example,
81. when Huawei releases a new product,
82. we can instantly know their suppliers will be affected.
83. And the inventory, it will influence your portfolio.
84. For a company like us,
85. knowing that more employees will be engaged
86. in data collection and data processing
87. instead of making rule-based models.
88. Although AI is being
89. increasingly adopted in real-world contexts,
90. there are still many challenges that we need to solve.
91. Explaining AI behaviour has often been difficult
92. and it is crucial for financial institutions
93. and the regulatory authorities.
94. Imagine if the algorithm is using a biased attribute
95. to make judgement on races or sexuality.
96. Humans will need to spend
97. a huge amount of time to justify it and solve it.
98. At the same time, the security of the AI algorithm
99. is still not well resolved.
100. If some crucial task is judged by AI,
101. then the hacker’s invasion
102. is likely to lead to a big financial disaster.
103. Data sharing and data security is also a big problem.
104. Data is the base for most financial applications.
105. However, a large proportion of data
106. is processed by international companies
107. like Google and Facebook.
108. How we can share the data and protect data privacy
109. is a big challenge as well.
110. It’s just the beginning,
111. and I hope you enjoyed the video
112. enough to be part of this growing trend.
113. Come join us.

Industry Showcase (NEW): AI in Financial Services (Huawei)

1. Hello there, my name is Bill Genovese.
2. I’m with Huawei.
3. I am Vice President of corporate strategy planning
4. for banking and financial markets,
5. and based out of Shenzhen, China.
6. Prior to Huawei, I was with IBM for over a decade
7. and before that, with KPMG,
8. and I came into both of those companies from banking,
9. so I have 25 years of industry
10. global experience in this sector.
11. So when we talk about artificial intelligence,
12. it’s often thrown about
13. and tried to be positioned into a corner,
14. robotics or natural language processing,
15. but it’s really a basket term of technologies
16. that are being applied in financial services
17. as well as other sectors
18. and really, five key buckets; pattern detection,
19. so looking for common patterns of reference
20. in terms of behaviours, as well as, anti-patterns
21. and outliers, foresights, so leveraging that information
22. to train artificial intelligence
23. to augment humans to make the right decision.
24. Customization and personalization,
25. very relevant in financial services
26. for the customer experience.
27. Then, we get into machine learning,
28. unsupervised and supervised machine learning.
29. So looking for patterns and unsupervised.
30. Once those patterns
31. and clusters are identified,
32. that can be used for supervised machine learning.
33. That will become reinforced machine learning
34. in terms of recommendations
35. and decision engines, and optimizations.
36. And that leads to self-learning.
37. It also leverages another key requirement,
38. especially in financial services,
39. is structured and unstructured data.
40. For it to work properly
41. and in an optimised fashion,
42. you need a lot of data. You need big data.
43. You need to leverage your investments in big data,
44. okay, so that deep learning neural nets can be trained,
45. overall machine learning,
46. which deep learning neural nets are a subset of,
47. and then, you can further develop and
48. industries can further develop banks, capital markets,
49. insurers, artificial intelligent applications.
50. So, in terms of intelligent society
51. and financial services, AI with IoT,
52. AI with blockchain, AI with IoT and blockchain,
53. So these are all inputs into faster digital transformation
54. for the banks and the insurers.
55. The convergence of those technologies
56. to solve the traditional financial service functions
57. and problems that need to be digitalized today
58. and going forward.
59. So it doesn’t exist in a vacuum, okay?
60. AI, in terms of traditional financial services,
61. is not being explored in isolation in a vacuum either.
62. So deposits and lending, okay,
63. insurance, payments, investment management,
64. capital markets, market infrastructure,
65. It’s being applied across the board,
66. If you look the three basic things that we need
67. as human beings, in terms of a consumption model:
68. (1) We need to pay our bills.
69. If we don’t have enough money to pay our bills,
70. we borrow, and we take out credit and lending.
71. And then, (2) if we have excess money
72. and aspirationally, we all want and need to do this,
73. we have to put money away to save.
74. (3) And if we have extra money beyond that, we invest.
75. AI is impacting across the board
76. all three of those needs as human beings
77. and making it easier for us.
78. And companies that are providing that linkage,
79. so they know where you’re paying your money to.
80. They can offer you lending products
81. when you need it on demand,
82. and if they see you have extra money,
83. they’re going to offer you savings accounts,
84. cash accounts, or even investment products
85. right from your mobile device, all AI-enabled.
86. So, AI is moving the industry from silos,
87. exclusivity of relationships, high switching costs
88. between providers to the human,
89. and it’s the value of not replacing your thinking,
90. but augmenting you to free you up
91. to do what you want to do in your life
92. and supporting your decision process.
93. So on the provider side, it allows them to cut costs,
94. leaner, faster operations, tailored products
95. and advice, less product overlapping,
96. competing product overlap,
97. providing ubiquitous presence in the consumer’s life
98. that’s personalised and they can offer
99. new business models, new collaborations
100. outside their industry vertical,
101. a bank with a retailer and new value propositions.
102. So, in terms of streamlining processes,
103. there’s a number of companies, deposits and lending,
104. insurance payments, investment management,
105. and from a back-office perspective,
106. I would say this is more “digitization” than digitalization
107. so taking paper and automating it
108. through robotic process automation, onboarding,
109. filling in applications for loans and mortgages.
110. So, that’s one area where
111. FinTech startups are disrupting
112. and offering the traditional players
113. capabilities to partner with them to do that.
114. Another is, really do we want to try to maintain costs?
115. but how much can we personalise for our customers?
116. So, intelligent chatbots,
117. Allstate from the insurance sector,
118. is a good good example of this.
119. So harnessing the data that they have on you
120. and really applying it to your personal experience,
121. so you can get through that a lot easier,
122. without humans or augmenting humans,
123. Expanding, I talked about expanding business models,
124. So, Amazon Go is a great example.
125. I’ve seen these in China.
126. So these are humanless stores, or cashless stores,
127. where you essentially go in,
128. you pick up the grocery items you want,
129. and then, you wave your palm at the device
130. and you will walk out,
131. and everything is billed to your bank account.
132. The most important thing is insights, okay?
133. Everything that I’ve kind of described up to this point
134. can’t really happen until the industry harnesses
135. that treasure trove of information they have on you
136. to give you the personalised experience you want,
137. Over time, it’s going to allow the industry
138. to kind of shape new products,
139. shelve some old products that are no longer traditional,
140. that are not working anymore.
141. But it’s going to right size or right fit the product mix
142. and the solutions in the industry
143. to fit the lives of the consumer,
144. which opens up new revenue opportunities.
145. So finally, in conclusion,
146. where does this all kind of lead?
147. The next step, in terms of the future,
148. is more of ambient banking,
149. or next generation financial services, as we’re calling it,
150. with AI is part of the centre of that, where it’s cash-free,
151. anytime, anyplace, anywhere,
152. in your 360-degree environment around you.
153. And then, I would even go so far to say that
154. it will come off the device potentially at some point.
155. Okay, and you’re interacting with financial services
156. through your glasses, your watch, your ring,
157. or projected on a wall that you have control over.
158. And that’s really kind of where we see things going.
159. So once again, thank you for your time.
160. I’ve had a pleasure coming here.
161. I hope this was useful, but keep in mind
162. that AI is here to stay.
163. The industry needs
164. and relies upon it to make things easier
165. as you consume financial services,
166. now and in the future.

Industry Showcase: Ensuring Compliance From the Start: Suitability & Funds (Investment Navigator)

1. Over the last few years we have seen
2. and experienced a wave of regulations
3. in the financial services industry
4. all around the world.
5. Typically, new regulations strive
6. for an increase of investor protection.
7. Because of this wave of regulations,
8. it is increasingly difficult
9. for financial service providers
10. to stay compliance
11. when conducting investment advice
12. whether it is in person or via robo-advisory.
13. Having pre- and post-trade checks in place
14. is not optional for banks,
15. it’s mandatory to stay in business.
16. FinTech can help to establish such robust processes
17. by replacing error-prone
18. and inefficient manual compliance checks
19. with automated solution along the investment
20. and advisory value chain.
21. In our case of investmentnavigator.com,
22. technology enables
23. the entanglement of client context,
24. regulatory rules and product data
25. to assess suitability on the individual instrument level.
26. By acting upon suitability feedbacks,
27. banks can not only significantly reduce regulatory risks
28. and save time through the automation,
29. but also level up the client experience.
30. They get enabled to offer
31. the most cost-efficient suitable investment instrument
32. for the respective client context.
33. A very tangible benefit also for the client.
34. Behind the scenes,
35. the cloud-based rule engine
36. is the technological heart of Investment Navigator,
37. which allows us to deliver coherent suitability feedbacks
38. into every application along the investment
39. and advisory value chain.
40. It is therefore strategic for us
41. to provide our clients the complete freedom
42. to consume our Suitability Service
43. via one or several channels.
44. We currently maintain customised webpages,
45. an API to integrate into proprietary advisory tools
46. a core-banking adapter and an Excel add-in.
47. To sum-up, as a B2B FinTech company,
48. we believe that by pairing technology
49. with subject matter intelligence,
50. we simplify financial advice.
51. That’s how FinTech creates a “win-win” situation
52. for financial service providers, as well as, customers.

3.5 Crowdfunding – Rewards, Charity and Equity

1. The concept of crowdfunding
2. is not as new as many may think.
3. The Statue of Liberty was famously known as
4. a gift from the French people
5. to commemorate the American Revolution.
6. What is less known is that there was
7. not enough funding for the base of the statue
8. and thus was actually crowdfunded by
9. Joseph Pulitzer by placing appeals
10. in the New York World newspaper in 1885
11. seeking contributions.
12. The rest, as they say, is history.
13. Crowdfunding’s modern incarnation gained popularity
14. when Kickstarter launched in 2009
15. as an online platform to fund
16. creative projects campaigns
17. in exchange for rewards.
18. Although not its’ initial main target audience,
19. Kickstarter became a favourite amongst
20. hardware enthusiasts who wanted to
21. fund minimum-batch-order production runs
22. of electronics in Shenzhen
23. and sought other enthusiasts to help with funding
24. and receive part of the batch run as rewards.
25. Gradually it became used more for pre-marketing
26. and product validation of
27. prototype consumer electronic, and other products,
28. and even incorporated by hardware accelerators
29. and venture capitalists.
30. Some of the most funded Kickstarter campaigns
31. were to fund smartwatch Pebble,
32. the Connected Coolest Cooler,
33. a Baubax, the travel jacket
34. made for electronic accessories.
35. Crowdfunding has been used
36. to benefit charities as well.
37. With sites like gofundme
38. having raised three billion U.S. Dollars
39. from over 25 million donors
40. across two million campaigns.
41. In China, Tencent’s ’99 Charity Day’ in 2017
42. raised approximately 930 Million Yuan
43. or 126 Million U.S. Dollars from
44. over 12 million Wechat users
45. for charities running 6700 programmes
46. over a three-day period.
47. Many other crowdfunding platforms
48. have since emerged with different levels of curation.
49. For example, IndieGoGo does not have
50. a minimum all-or-nothing funding goal,
51. and does not require a working prototype.
52. More specialised platforms around sectors
53. or themes have also emerged.
54. Yet, before too long,
55. some backers began to question
56. this rewards approach.
57. In late 2012 Oculus Rift’s 19 year-old founder
58. raised 2.4 million U.S. Dollars
59. offering it’s virtual reality
60. head-mounted display as rewards.
61. Yet, less than two years later,
62. he sold the company to Facebook for two billion dollars.
63. Were rewards backers chumps?
64. If they could have received substantial upside
65. by receiving equity in Oculus Rift,
66. rather than V.R. Headgear?
67. In 2012 Congress passed the JOBS Act
68. which amongst other things legitimised
69. the concept of equity crowdfunding.
70. And in 2015, the SEC passed the Title IV regulations.
71. Many other countries around the world followed suit
72. to pass crowdfunding laws to encourage innovation,
73. and to allow direct retail investment into
74. early stage companies to augment current reliance
75. on private placement exemptions from
76. professional investors like venture capital firms,
77. and high-net-worth individuals.
78. The World Bank has predicted that
79. crowdfunding investments will be
80. a US$96 billion a year market
81. in developing countries alone by 2025.
82. And Goldman Sachs’ analysts have heralded
83. crowdfunding as potentially the most disruptive
84. of all the new models of finance.
85. In essence, online capital marketplaces
86. have three main facets.
87. First, digital access by the general public
88. to learn more about,
89. and for the information to be posted by projects online.
90. Second, easy to use and secure fund flow
91. from the general public to support these projects.
92. And third, marketplaces where there is
93. sufficiency of information for decisions to be made
94. about the project and its’ promoters that
95. enable matchmaking of projects
96. to the potential supporters.
97. So unlike traditional stock markets which
98. relied upon brokers and dealers as intermediaries,
99. individual investors could transact directly
100. which lead to many to describe this as
101. disintermediation and democratisation of finance.
102. Entrepreneurship and SMEs are well recognised as
103. important drivers of employment and innovation.
104. And television shows like Shark Tank in the U.S.
105. And Dragon’s Den in the U.K. popularised
106. and encouraged the notion of entrepreneurs
107. seeking such early stage funding for their projects
108. and the general public’s willingness and ability
109. to participate in these kinds of investment decisions
110. from their living room chairs.
111. If securities in the form of equities
112. or investment products are being offered
113. existing securities
114. and collective investment scheme laws and regulations
115. require perspectives to be prepared for
116. public offers unless they are private placements
117. made to sophisticated investors.
118. Crowdfunding legislation introduced specifically
119. recognised such limitations of existing laws
120. and are designed to allow SMEs and entrepreneurs
121. to be able to more cost-effectively tap
122. funding from the general public
123. with specific consumer protection elements built in.
124. Examples of these elements include
125. limiting the size of qualified companies,
126. capping investor, investment amounts,
127. and requiring investor cooling-off periods.
128. Minimum disclosure and lockups
129. as well as licensing the marketplace portals.
130. Yet, equity was just the first financial instrument
131. to utilise this new distributed
132. peer-to-peer model of finance.
133. More was to come.

3.6 P2P and Marketplace Lending

1. Crowdfunding for debt emerged
2. almost in parallel with crowdfunding in equity.
3. Known as peer-to-peer lending or P2P lending
4. or crowdlending, the size of this market
5. was perceived to be even bigger,
6. as it encompasses not just unsecured business
7. and SME loans but the personal finance sector.
8. In the aftermath of the global financial crisis,
9. many governments became very supportive
10. of this form of alternative finance
11. after the loss of trust in traditional banks.
12. The basic concept is simple.
13. In a low-interest-rate environment,
14. many individual savers
15. sought alternative avenues for investment
16. at a time when banks had reduced their lending.
17. Through an online platform,
18. borrowers are listed to be matched by lenders
19. who benefit from a higher return
20. due to the lower overhead costs.
21. It seems like a win-win situation
22. for borrower and lender.
23. The concept can be traced back to Kiva,
24. a micro-lending platform inspired
25. by microfinance founder Muhammad Yunus,
26. which allowed loans to be made to individuals
27. in rural communities within developing countries.
28. For example, you can help a farmer in Africa
29. by lending him money to buy a particular cow.
30. In the United Kingdom,
31. platforms such as Zopa
32. and Funding Circle expanded P2P lending rapidly.
33. In the United States,
34. companies like Prosper
35. and LendingClub grew exponentially,
36. with the latter being the first
37. P2P lending company to IPO in 2014.
38. Credit analysis is critical in this sector
39. of unsecured loans
40. which do not enjoy government guarantees.
41. How do you know the individuals
42. or businesses will repay the loan?
43. To address the risks, loans often have
44. short tenors, and some platforms
45. introduced secured loans and trust accounts.
46. There was also a regulatory lacuna as loans
47. are not on their face securities.
48. This was a situation that changed
49. in the United States in 2008
50. when the SEC extended jurisdiction
51. over such P2P-lending platforms.
52. Two trends began emerging.
53. First, many categories of loans emerged
54. on specialised platforms,
55. from consumer lending to business lending,
56. real-estate lending, student loans
57. and payday loans linked to wages paid.
58. Second, individual lenders started getting dwarfed
59. by institutional lenders and investors,
60. so that instead of being called peer-to-peer lending,
61. the sector became known as marketplace lending.
62. In the meantime, the combination
63. of a lighter regulatory touch,
64. rising middle class
65. and the lack of investment alternatives
66. led the P2P-lending market in China to explode.
67. It was primarily when CreditEase listed
68. its Yirendai unit in 2015 that the West realised
69. the size of loans originated
70. and the number of borrowers in China dwarfed that
71. of the largest US platform lenders.
72. However, problems emerged in this area
73. of China’s shadow banking,
74. and the 2016 Blue Book of Internet Finance found
75. 1,263 namely 1/3 of China’s P2P platforms problematic.
76. For example, in 2017, a Chinese court concluded
77. that P2P-lender Ezubo defrauded
78. more than 900,000 investors of 50 billion yuan,
79. or US $7.6 billion, under a Ponzi scheme,
80. and two of its founders were
81. sentenced to life imprisonment
82. and 24 executives were jailed for three to 15 years.
83. China’s regulators have since been tightening
84. P2P-lending rules,
85. such as requiring custodian banks to be appointed,
86. imposing borrowing and interest caps, and recently
87. preventing microfinance lending companies and banks
88. from respectively raising and funding P2P loans.
89. The new generation of P2P-lending companies
90. appear to be veering away as lending platforms
91. to become innovative credit analysis services
92. that incorporate analysis of social media usage
93. and online purchase patterns that can be used
94. by traditional banks and bank syndicates.
95. Similarly, P2P insurance has evolved
96. and has been described as evolving from
97. a distribution model to a carrier model
98. and now a self-governing model.
99. The evolution of P2P lending
100. provides useful lessons
101. for the development of the current darling of
102. distributed peer-to-peer models of finance,
103. namely, cryptocurrencies and token sales.

3.7 The Rise of Chinese TechFins

1. In December 2016, Alibaba’s founder Jack Ma,
2. coined the phrase “TechFin”,
3. “FinTech takes the original financial system
4. and improves its technology”,
5. Ma Yun told South China Morning Post’s
6. China Conference in Hong Kong.
7. “TechFin is to rebuild the system with technology.”
8. Another way to think about it is that
9. where financial institutions
10. and FinTech startups seek to improve
11. or upend the existing financial system in FinTech,
12. tech companies approach this issue
13. from a different and more consumer and
14. technology centric perspective in TechFin.
15. It is instructive to compare the rise of
16. American tech giants to those from China,
17. to better understand their difference
18. in origins and approaches.
19. China’s tech giants are commonly known as
20. the BATs: Baidu, Alibaba and Tencent.
21. In the United States, a commonly known acronym
22. is the GAFAs: Google, Apple, Facebook and Amazon.
23. During the dotcom boom and web 2.0,
24. today’s Silicon Valley tech giants grew
25. mainly using advertising or “eyeball” models
26. that relied on generating more viewers.
27. Examples of these include
28. search engines like Google
29. and social media portals like Facebook.
30. Apple was then primarily a hardware manufacturer,
31. and e-commerce pioneers like
32. marketplace platform eBay,
33. which acquired PayPal in 2002
34. to power it’s transactions,
35. and online bookseller Amazon booked the majority
36. of its transactions via credit cards.
37. In contrast, in China
38. where credit card penetration remained low,
39. the tech giants incorporated transactions
40. into their platforms from the very beginning.
41. Hangzhou based Alibaba started as
42. a business-to-business or B2B platform,
43. and when it transitioned more
44. to a business-to-consumer or B2C platform,
45. with the introduction of online retailer Taobao,
46. it extended its sister company’s payment system,
47. now known as Alipay, to consumer transactions.
48. Instead of Amazon’s money-back guarantee,
49. Alibaba provides comfort to its retail consumers
50. by keeping payments of goods in a deposit account
51. that is not released until receipt
52. and approval of the goods by the customer.
53. Yu’eBao or “leftover treasure” was born
54. when Alibaba started offering interest
55. to customers who kept their funds in this account
56. at rates higher than bank deposits.
57. The Wall Street Journal reported that in just four years,
58. Yu’eBao had accrued 370 million account holders
59. and 211 billion dollars in US assets
60. to be twice the size of the next largest
61. money market fund JP Morgan Asset Management.
62. Shenzhen-based online gaming company Tencent
63. built in micropayments early because
64. its freemium business model was based on
65. gamers making in-game payments for
66. its free-to-play games,
67. to buy say, awesome virtual swords.
68. When the company transitioned into mobile
69. and introduced instant messaging
70. through QQ for youth and then WeChat,
71. they captured an amazing userbase
72. of nearly one billion active users
73. who learned to transact online through inventions
74. like hongbao where users can give
75. and receive traditional red packets for mere cents.
76. WeChat now also allows users to use
77. and transact via third party mini-apps,
78. including financial ones,
79. without even exiting the instant messaging ecosystem
80. to open new apps.
81. In 2015, Tencent launched WeBank,
82. China’s first online only bank,
83. using sophisticated credit analysis
84. based on WeChat social media usage
85. and online purchase patterns,
86. that is also offered to service traditional lenders.
87. Quick Response codes, or QR codes,
88. are also rapidly changing China into a cashless society.
89. Being built into WeChat and many other apps,
90. China’s smartphone users can use scannable codes
91. to facilitate offline-to-online,
92. or O2O transactions, connect with others
93. to replace the venerable business card,
94. as well as to make payments.
95. Financial supermarkets are also proliferating.
96. For example, Alibaba’s Zhao Cai Bao
97. offers fixed term deposit products
98. from third-party financial institutions or individuals,
99. mutual funds, and stock market information.
100. These compare with distribution platforms
101. traditionally accessible only to
102. to institutional fund managers
103. and to existing retail sales distributions
104. via banks or retail fund managers.
105. In the meantime, in the West,
106. the GAFAs are not sitting idly by.
107. Facebook’s messaging app WhatsApp
108. is incorporating a lot of
109. WeChat’s innovative features.
110. Apple has since developed a tremendous
111. and very sticky online ecosystem
112. with App Store and iTunes.
113. And Amazon’s Prime has paved the way
114. for subscription based models,
115. for content such as its competitor Netflix,
116. to show that users are willing to pay
117. for quality movie, television and music content.
118. Most importantly, they are also investing heavily
119. in the next generation
120. of ABCD technologies and infrastructure, namely,
121. artificial intelligence, blockchain, cloud, and data.
122. How long will it be before GAFA are inspired
123. by their Chinese BATs counterparts to use
124. their digital nous, consumer-centric mindsets
125. and broad user-base clout to directly
126. participate and compete in finance?
127. Tech giants have brands that are trusted
128. especially amongst younger financial consumers
129. at a time when banks have lost trust
130. after the global financial crisis.
131. Yet, traditional finance and banks are used to
132. working within highly regulated environments
133. that many tech companies have not yet
134. fully come to grips with.
135. The Silicon Valley ethos that
136. “it is easier to ask for forgiveness
137. than to seek permission”
138. works just fine in the internet industry,
139. where lines of code can be corrected
140. and changed overnight on a website.
141. It works less well
142. in a highly regulated industry like finance.

Additional Video Resources: Chinese TechFin

1. What is Alipay? (2.30 Mins) 

3.8 ICOs

1. Well, let’s talk now about a very exciting topic of ICOs.
2. ICOs, ICOs, ICOs, you’ve probably heard this term a lot
3. in the media or from friends.
4. Well, there was actually a lot of buzz in the media
5. in recent months about this topic.
6. Believe it or not, only in 2017,
7. more than $6 billion were raised by ICOs.
8. But what is an ICO?
9. An ICO is short for Initial Coin Offering,
10. often referred to as a token sale.
11. It’s a limited period of time in which
12. a company sells a predefined number of
13. digital tokens to the public.
14. But what is this really?
15. You know to really simplify things
16. a good analogy is, well if we make a comparison
17. to what happens in real life?
18. Let’s take a private club,
19. let’s say tomorrow I want to build a private club
20. and I come to you and I say,
21. hey, I want to build a private club.
22. Here’s where the swimming pool’s going to be,
23. this is where the restaurant is going to be
24. and these are where the tennis courts are going to be
25. and it’s going to be the best private club in the world.
26. But in order to enjoy the facilities,
27. you need to be a member.
28. If you want to…
29. you have to be a member to be able
30. to enjoy the facilities.
31. Yes, you still need to pay for your breakfast,
32. or when you’re at the tennis club,
33. but to join the club, you need to be a member.
34. And that is really if we really generalise what ICOs are.
35. They are selling these memberships
36. to this ecosystem that people can use.
37. But you would say,
38. why is somebody doing this?
39. Why wouldn’t they simply issue shares
40. in the company for capital?
41. Well, there’s a couple differences.
42. In most ICOs, the tokens that you’re issuing
43. have no economic rights, no voting rights
44. and they’re generally outside the scope
45. or the traditional regulatory framework.
46. This is different from when you issues shares
47. in exchange of equity for your business
48. where you often get a calmer exposure
49. to your business,
50. you have voting rights
51. and there’s a pretty well clear and established path
52. of how you can raise money in that way.
53. And this is actually a very interesting way
54. of actually generating value where people
55. are trying to build their ecosystems
56. and actually doing ICOs for doing so.
57. But why do you think
58. a lot of entrepreneurs are doing this?
59. But one of the big advantage of an ICO
60. is it doesn’t dilute you.
61. When I’m issuing shares for capital
62. I actually kind of giving away
63. part of my business to my investors.
64. The beauty of an ICO is actually you’re issuing
65. these tokens that allow these purchasers
66. of these tokens to access the ecosystem,
67. but without really diluting your equity.
68. And this has been pretty big game-changer
69. because many believe this actually can enable us
70. to actually democratise capital in fund raising.
71. In a traditional world if you’re launching a business
72. you hope you have some friends or contacts
73. who have money who are happy
74. to invest in your business.
75. The beauty of an ICO allows individuals
76. from all around the world to raise money
77. if they have a good idea and a good project.
78. Whether you’re in Santiago, Chile,
79. Moscow, Russia,
80. Johannesburg, South Africa,
81. or Hong Kong, China,
82. doesn’t really matter.
83. The world is actually where you can go raise money.
84. Obviously there’s a lot of regulatory requirements
85. and restrictions, but I think you get my point.
86. And what’s been really interesting
87. is over the last 12 to 18 months
88. since the beginning of the ICO craze,
89. we have really seen the industry turn swarming off.
90. Initially it was a lot of young entrepreneurs
91. who had an idea, wrote a white paper,
92. and were able to raise quite a bit of money.
93. What we have seen since then is the industry
94. becoming definitely more institutional.
95. We have seen the emergence of best practises
96. like in the space of KYC and the AML
97. Know Your Client and Anti Money Laundering.
98. We have seen the emergence of best practises
99. when it comes to the government and transparency.
100. For example how these ICO companies are being run.
101. What is a transparency that has been given
102. to people who own these tokens?
103. So really there’s a lot of exciting space
104. going on in this space.
105. There will be definitely more
106. regulatory enforcement cases moving forward.
107. Tax authorities will look at it.
108. And actually the regulatory space,
109. this entire space may become
110. more regulated as well.
111. But this is definitely an area to watch
112. if you’re interested in the broader startup,
113. blockchain and cryptospace.

Industry Showcase (NEW) – Collaborative and Contextual Banking (WeBank)

1. Hello, today I’ll be talking about
2. how finance is becoming far more intuitive
3. and customer-oriented, but just as importantly,
4. how technology is informing new types
5. of financial business models and services.
6. Finance is becoming contextualised,
7. brought into the business scenarios where it is needed
8. and it is being provided by both traditional
9. and non-traditional players collaborating together.
10. My name is Tyler Aveni and I serve as
11. the Head of International Partnerships for WeBank.
12. WeBank is the Tencent-affiliated digital bank
13. based in Shenzhen, China.
14. We are the first privately-owned bank
15. as well as, the first internet bank here in China as well.
16. This is to say that
17. since receiving our banking licence in 2014,
18. we have never opened a physical bank branch
19. to serve our customers.
20. Instead, we leverage on an intelligent technology stack,
21. digital channels, and a host of
22. different business partners and their resources,
23. to offer retail banking solutions.
24. These are both business-to-consumer products,
25. like savings accounts and credit to individuals,
26. as well as, white-labeled products
27. and other technological solutions
28. we offer to institutions.
29. Our most popular product, called Weilidai,
30. is a micro-credit product which we offer exclusively
31. through the texting and social media platforms
32. WeChat and QQ to Chinese users.
33. In the case of credit,
34. we are using our technology to understand
35. the behavioural and financial interactions of users
36. to reduce fraud and build a more complete picture
37. of someone’s credit worthiness.
38. This helps improve access to financial services
39. for underbanked customers
40. who may not have conventional credit bureau data.
41. On the funding side, we can do this
42. through a loan syndication model
43. wherein dozens of bank partners contribute
44. the majority of funding for each micro loan
45. using new methods like blockchain technology.
46. And what this equates to, essentially,
47. is this complex array of collaborating institutions
48. in cutting-edge technology, operating behind the scenes,
49. all so that we can effectively provide
50. this extremely easy to understand
51. and accessible product.
52. And so too, around the world,
53. we see that technology
54. is the driving factor behind the changes
55. we are seeing in banking and finance.
56. It then holds that financial institutions need to learn
57. from their large IT counterparts and their development.
58. More than just bolstering in-house core competency
59. in some of these new technologies though,
60. this really also means embracing
61. an ideology of collaboration,
62. the same kind of collaboration we have seen
63. in open-source software projects
64. and how they have brought long-term benefits
65. to IT industry leaders and their users alike.
66. Banks, as a full-service model,
67. are very sticky institutions by design.
68. You, as a customer of the bank,
69. face a lot of obstacles in changing providers,
70. and may even lack information
71. to know on what grounds
72. to make that selection to begin with.
73. This is quickly changing,
74. and giving way to several new models of banking
75. which are much more collaboration focused.
76. The first model simply reduces banks
77. to a risk management function
78. and provides security of your money
79. as a kind of public utility.
80. This may be used in the case of retail businesses
81. that decides to offer financial services
82. and open accounts for customers.
83. Behind the scenes, any funds that might be held
84. would be protected and managed by a partner bank
85. in exchange for a fee.
86. The second, is a type of marketplace banking.
87. With the advent of Open Banking frameworks
88. such as what is being rolled out in the UK now,
89. or the Second Payment Services Directive
90. or PSD2 across Europe,
91. users are gaining more explicit control
92. over their digital information,
93. meaning customers can more easily transfer their data
94. from one institution to another.
95. This data can be standardised
96. and offered as functionality
97. in the form of tools like APIs and SDKs.
98. So in marketplace banking,
99. the banks still remained a single channel for banking,
100. but many other FinTechs and financial institutions
101. can offer their particular financial product,
102. whether it be a loan, a payment tool,
103. a rewards mechanism and so on,
104. through this channel or marketplace.
105. This allows users to compare and then easily
106. swap in-and-out comparable services,
107. all linked to their bank account
108. in a Lego building like manner.
109. And then, third, in contextual banking,
110. you have financial products
111. that are still being designed,
112. managed, and provided by a bank
113. or another financial institution.
114. However, they are being provided
115. in the business scenario that they are required.
116. For instance, we see this when we are offered a credit
117. or loan product during an online purchase.
118. In this sense, finance is seen as an enabler
119. of the transactions within our lives.
120. Making a trip to a bank,
121. or in the digital equivalent, moving to another app,
122. is not an activity that really offers the user
123. some inherent benefit necessarily.
124. And so, this poses a direct challenge
125. to a long-held belief in banking,
126. that banks’ strongest asset
127. is its relationship to customers.
128. Wherein marketplace banking sees
129. an unbundling of the full-service bank,
130. to allow FinTechs to specialise in specific products
131. or financial services and plug-in to the platform,
132. contextual banking sees a separation of value
133. along different lines.
134. Digital services, businesses that are a part
135. of the shared economy, e-commerce and so on,
136. these companies provide access to data,
137. understanding of their customer,
138. and massive distribution.
139. By embedding the financial products into these
140. business scenarios with some of the additional data,
141. banks and supporting technology intermediaries
142. can create unique products that are tailored
143. to the specific situation.
144. In fact, at WeBank, our mobile application,
145. a combination of a savings account
146. and wealth management products,
147. remains the only direct channel for servicing customers.
148. All of our other products, including the Weilidai,
149. the micro-credit product mentioned earlier,
150. are offered through partner platforms.
151. And so, it is not just BigTechs and FinTechs
152. that become part of the future financial landscape,
153. but in fact, most businesses will
154. increasingly become participatory
155. in some of these business models
156. because finance is a big part of our lives.

Additional Resource Insights

A. References and Suggestions for Further Reading

1.   IOSCO Research Report on Financial Technologies (FinTech) (Industry Report – IOSCO) 
2.  Understanding Alternative Finance: The UK Alternative Finance Industry Report 2014 (Industry Report – Nesta)
3.  The ICO Gold Rush: It’s a Scam, It’s a Bubble, It’s a Super Challenge for Regulators (Academic Paper: Zetzsche, Buckley, Arner, Fohr)
4.  Regulation of Digital Financial Services in China: Last Mover Advantage (Academic paper: Zhou, Arner, Buckley) 

B. Additional Resource Insights for Module 3.4.1: How AI is Transforming the Future of FinTech 

1. Microsoft Professional Program in AI – From an Introduction to AI to Mastery of Skills Needed to Build Deep Learning Models for AI Solutions

Mid-Point Message from Course Director Douglas Arner

1. Hello, and welcome to the mid-point
2. of Introduction to FinTech.
3. We very much hope that you’ve enjoyed
4. our first three modules so far.
5. Looking back, in our first module,
6. we looked at what is FinTech?
7. And since that module came out
8. the World Bank has released the 2018 Global Findex
9. which highlights how over a billion people
10. over the past six years
11. have opened new bank accounts,
12. much of this as a result of FinTech.
13. In module 2, we looked at payment,
14. cryptocurrencies and blockchain
15. and over the past six months
16. the idea of cryptocurrencies of blockchain
17. has continued to dominate
18. the news media about finance.
19. Countries such as Venezuela
20. have launched the first sovereign cryptocurrencies
21. and others, including China, Russia
22. and a range of others
23. are considering similar proud programmes.
24. In module 3, we looked at the digitization of finance
25. and at alternative finance.
26. In the context of digitization of finance,
27. we’re seeing an increasing presence of AI, the launch of
28. an increasing number of Independent funds
29. which choose their own investments via AI
30. and run themselves.
31. In the context of alternative finance,
32. the use of blockchain and crowdfunding,
33. the idea behind ICOs continues to grow and grow
34. but with evermore regulatory attention.
35. So far, over 50 regulators around the world
36. have made warnings and announcements about ICOs
37. but at the same time,
38. even though there are dangers
39. there are huge opportunities
40. for funding new ideas and early-stage companies.
41. Looking into the second half of the course,
42. we’re going to move into issues of regulation
43. but also one of the most exciting areas
44. of opportunity in FinTech
45. and that is the entire RegTech ecosystem in module 4.
46. In module 5, we’ll turn to
47. some of the biggest challenges,
48. some of the challenges very much highlighted
49. by recent issues with data companies
50. such as Facebook, Equifax and others.
51. The question of data, monetization of data,
52. cybersecurity and TechFins
53. and finally, in module 6,
54. we’ll look at a number of specific case studies
55. using these to pull together
56. the things that we’ve learned
57. over the previous five modules and look forward a bit
58. to see what the future of FinTech may hold.
59. For those of you
60. who haven’t quite finished module three yet,
61. we encourage you to please continue
62. going with the course.
63. After all, you have plenty of time
64. and can do this at your own pace
65. but once you’ve started it,
66. you might as well keep going because the more you do,
67. the more you learn
68. and the more you’re likely to understand
69. this world of financial technology around us.
70. And for those of you who still haven’t quite started,
71. now is the best time.

Module 4 FinTech Regulation and RegTech

Welcome to Module 4

4.1 Module 4 Introduction

1. In Module 4, we turn to regulation of FinTech,
2. and a new development,
3. what is called RegTech or regulatory technology,
4. and if we look at this module,
5. we’re going to begin by looking at
6. why do we regulate financial markets
7. before turning to the particular challenges
8. of regulating FinTech.
9. From there we’ll move on
10. to what we think is one of the most exciting areas
11. of interaction between finance technology
12. and regulation, and that is RegTech.
13. We’ll look at the RegTech ecosystem
14. and also ideas of smart regulation
15. and the outlook for future design of financial systems.

Module 4 Learning Objectives

Module 4 addresses the range of regulatory considerations and approaches in the context of FinTech. It highlights the core regulatory objectives and the relationship between the post-2008 financial regulatory reform process and FinTech. It focuses in particular on the concept of RegTech – “regulatory technology” – and the RegTech ecosystem comprising financial institutions, startups, and regulators, and introduces “Smart Regulation” as the redesigning financial infrastructure and regulatory systems on the basis of new technologies, including Big Data, cloud, AI and blockchain.

In Module 4, learners will:

• Understand major financial policy and regulatory objectives and their implications for FinTech.
• Explore RegTech and the RegTech ecosystem, in order to understand one of the key trends in financial and regulatory transformation.
• Consider how regulatory systems and financial infrastructure could be redesigned on the basis of new technologies to deliver better results both from the standpoint of efficiency as well as resilience
• Think about new regulatory approaches such as regulatory sandboxes, India Stack and Smart Regulation.

4.2A FinTech Regulation (Part 1)

1. The first question is really
2. why do we regulate financial markets in the first place?
3. In fact,
4. even why do we regulate financial markets at all?
5. And as we’ve seen
6. with fintech’s evolution generally,
7. the 2008 global financial crisis
8. was a game changer
9. for financial regulation.
10. Prior to the 2008 global financial crisis,
11. there was a general consensus
12. in favour of largely market-based approaches
13. to financial market regulation.
14. Many of these derived from
15. the ideas of what is called
16. the efficient markets hypothesis.
17. The idea of the efficient markets hypothesis
18. is that markets will price in
19. all available information
20. with prices of financial assets
21. providing for efficient allocation
22. of financial resources.
23. The idea is that market mechanisms provided
24. there is sufficient information
25. available to markets
26. will function to
27. both price, financial assets,
28. as well as, allocate financial resources
29. to their most valuable uses.
30. That idea was based on
31. a number of assumptions.
32. First, that there is
33. perfect information available in markets,
34. second, that there are
35. no transaction costs in markets
36. third, that there is
37. perfect competition in markets,
38. and fourth, that there were
39. rational market participants.
40. All of these ideas together
41. would lead towards
42. efficiently functioning financial markets
43. which would properly
44. support the functioning
45. of the overall economy.
46. The problem was that
47. certainly even prior to 2008,
48. we already knew that
49. information was not perfect,
50. that there are transaction costs
51. in acquiring information
52. or enforcing transactions in markets,
53. and that competition
54. is by no means perfect.
55. And much of law and regulation
56. prior to the global financial crisis
57. focused on improving information quality,
58. on enhancing competition,
59. on reducing transaction costs
60. to reduce what are called market failures.
61. The idea is that law and regulation
62. would be used
63. to reduce problems in markets
64. to help those markets
65. function in a better way.
66. 2008 global financial crisis
67. fundamentally changed the way
68. that we think about
69. finance and its regulation.
70. In particular, the 2008 global crisis
71. and the hundreds of billions of dollars spent
72. on bailing out large banks around the world
73. highlighted a problem
74. which is called systemic risk.
75. Systemic risk is the risk that
76. the collapse of an individual financial institution
77. will cause the collapse of
78. the entire financial system,
79. which will in turn
80. cause the collapse of the economy.
81. This is exactly what we saw in 1929
82. and the 1930s Great Depression.
83. It’s also what we saw in 2008.
84. As a result, since 2008,
85. there has been a massive amount of attention
86. on building new regulatory frameworks
87. to prevent financial crises,
88. to build confidence,
89. and to make markets function properly.
90. So, if we think of regulation today,
91. its function continues to be
92. on improving market functioning and efficiency.
93. It is also about
94. preventing systemic risks,
95. maintaining financial stability,
96. and importantly,
97. as we’ve already seen,
98. it is about fairness
99. to market participants.

4.2B FinTech Regulation (Part 2)

1. As we just discussed,
2. the 2008 financial crisis was a game changer
3. in the way that we look at
4. regulation of financial markets.
5. And for the eight or so years after 2008,
6. policy makers globally,
7. as well as, regulators around the world
8. spent much of their time and efforts
9. on developing new regulatory systems
10. to prevent the sorts of crisis
11. that we saw in 2008,
12. but this 2008 crisis
13. also triggered an explosion
14. in the development of fintech.
15. And that explosion
16. in the development of fintech
17. has been a major challenge for regulators,
18. after all, one element of fintech
19. is the idea of
20. disrupting traditional institutions,
21. traditional industries,
22. traditional finance,
23. but a major object of financial regulation
24. after the 2008 crisis
25. has been preventing disruption
26. in financial markets,
27. financial institutions,
28. and the financial system.
29. The same time,
30. there has been a strong focus on regulation
31. to support innovation and development
32. in the financial system,
33. and so regulators have been forced to
34. come to terms with the explosion
35. in new technologies and new participants
36. in the financial sector,
37. and to come to grips with
38. how to regulate the opportunities
39. as well as, the challenges.
40. And so far what we have seen
41. are four major approaches
42. amongst regulators.
43. The first approach has largely been
44. one of doing nothing,
45. in many ways,
46. this idea of doing nothing
47. can be seen as
48. either a positive or a negative approach.
49. It can be either permissive or restrictive.
50. China, prior to the middle of 2015
51. is usually seen as the major example
52. of a country taking a permissive approach
53. through deciding
54. not to put in place new regulations.
55. And in many ways,
56. it was this decision,
57. which has allowed the explosion of fintech
58. in the context of China.
59. But, as we’ve seen before,
60. that explosion of fintech in China
61. also brought with it new risks.
62. The evolution from
63. too small to care to too big to fail,
64. that we’ve seen
65. in the context of payments,
66. money market,
67. mutual funds,
68. and other areas.
69. As a result, even in the context of China,
70. the decision over the past several years
71. since 2015 has been increasingly to build
72. a new regulatory framework
73. for digital financial services.
74. Other jurisdictions
75. have taken an approach
76. of not doing anything,
77. which has largely been restrictive,
78. requiring new entrants into financial services
79. with new business models,
80. new technologies,
81. and new approaches
82. to comply with existing regulatory requirements,
83. which would typically develop
84. for a very different type of
85. established financial institution,
86. banks,
87. insurance companies,
88. mutual funds,
89. and the like.
90. The end result of this is
91. often a very restrictive approach.
92. Coming into the past several years,
93. regulators have been trying
94. to balance the objectives
95. of innovation and growth
96. with considerations of financial stability
97. and consumer protection,
98. and as a result,
99. they are developing an increasing number
100. of experimentation-based approaches.
101. Some involve regulators
102. establishing contact points
103. to meet with new entrants,
104. to learn about technologies
105. in order to be able to
106. develop appropriate regulatory responses.
107. Others have developed
108. what are called sandboxes,
109. these are areas for experimentation
110. in a limited market context
111. with limited regulation,
112. in order for both the new company
113. as well as the regulator,
114. to learn how best to move forward.
115. And finally,
116. an increasing number of jurisdictions
117. developing new regulatory frameworks,
118. particularly for the sorts of things
119. that we’ve seen in Modules 2 and 3.
120. Things like P2P lending or
121. alternative payment systems
122. or forms of crowdfunding.
123. But jurisdictions like China, India and others
124. are also looking at
125. developing entirely new regulatory approaches.

4.3 Evolution of RegTech

1. The 2008 financial crisis
2. was one of the key triggers
3. for the massive acceleration
4. in the development of FinTech worldwide.
5. But in addition,
6. it was the catalyst for the development of
7. RegTech, or regulatory technology.
8. And the ideas of RegTech relate to FinTech
9. but are much more broader.
10. In other words,
11. RegTech is the idea of using technology
12. for regulatory compliance,
13. regulatory monitoring,
14. but also, regulatory design.
15. It is the idea of using technology
16. to make financial markets
17. and their regulation more effective.
18. Now, if we think of RegTech in that way,
19. the key aspect is that
20. it is beyond FinTech.
21. RegTech can apply
22. in any segment of the economy,
23. not just in the context of financial regulation.
24. One can imagine
25. the application of technology
26. to environmental regulation,
27. or traffic regulation,
28. or airline regulation.
29. Any area of the economy with regulation,
30. the application of technology
31. offers the potential
32. to transform the effectiveness
33. of that particular regulatory system.
34. However, in the context of finance,
35. RegTech is so far,
36. the most developed.
37. In particular, we see RegTech
38. across traditional financial institutions,
39. across new startups,
40. and also across regulators, themselves.
41. And the global financial crisis
42. really made this a necessity.
43. Since 2008,
44. we have seen an absolute explosion
45. in new regulations around the world.
46. New regulations are released
47. by a major jurisdiction
48. approximately once every hour.
49. The end result is that,
50. every year,
51. thousands of new regulations come out.
52. And, for a financial institution
53. doing business on a cross-boarder basis,
54. this is one of the most complex influences
55. on their operations
56. as well as on their profitability
57. because, not only is regulation a challenge,
58. but it is also a cost.
59. As a result,
60. the global financial crisis
61. and its explosion of regulation
62. has driven the established financial industry
63. into applying technology
64. to address their compliance burdens
65. and their compliance costs.
66. At the same time,
67. we have seen an explosion
68. in new startups, new firms,
69. which are offering technologies
70. to help both startups
71. as well as traditional financial institutions
72. and even regulators
73. to better address
74. their regulatory and compliance burdens.
75. Finally, regulators themselves
76. are increasingly using technology
77. for a range of purposes
78. not only to do a better job
79. in their regulatory functions,
80. but also to increase market efficiencies
81. and reduce cost in the industry.

4.4 RegTech Eco-system: Financial Institutions

1. The RegTech ecosystem encompasses
2. both industry and regulators.
3. It encompasses
4. the traditional incumbent financial institutions
5. like banks,
6. insurance companies,
7. and investment banks.
8. It also encompasses startups
9. of an increasing range
10. and it also encompasses regulators.
11. However, most of the development
12. that we’ve seen in the area
13. of RegTech over the past decade
14. following the global financial crisis
15. has been focused
16. in the traditional financial services industry,
17. in particular, in the banking industry.
18. And we can see this obviously simply
19. from the cost of regulation.
20. Not only have we had thousands of
21. new regulations in the US,
22. in Europe,
23. in Hong Kong,
24. in Singapore,
25. and Australia,
26. in economies all over the world
27. as a result of the global financial crisis.
28. But large financial institutions around the world
29. have paid to date over $300 billion US dollars
30. in fines for regulatory failures
31. both resulting from and also in the aftermath
32. of the global financial crisis.
33. Compliance has become a major challenge
34. from the standpoint of the industry
35. both from the standpoint of
36. simply keeping up with regulatory changes
37. and their implications,
38. but also from the standpoint of
39. the very, very large fines
40. that we have seen
41. coming out of major regulators
42. since the global financial crisis.
43. And if we look today at
44. traditional financial institutions,
45. if we look at RegTech in banks,
46. probably two areas highlight best
47. the necessity of technology.
48. First, are what are called
49. know your customer requirements.
50. Know your customer requirements
51. are something that every financial institution
52. everywhere in the world must comply with.
53. The origin of
54. know your customer requirements
55. comes from a series of regulations
56. that focus on preventing criminal use
57. of the financial system,
58. in particular,
59. things such a money laundering
60. or the financing of terrorism.
61. Internationally, we have an organisation
62. which is called the FATF.
63. The FATF is the Financial Action Task Force
64. on Money Laundering
65. and it establishes
66. internationally agreed minimum standards
67. for regulation in financial systems
68. with which every financial institution
69. around the world must comply.
70. Now, the challenge is that
71. these are simply agreements.
72. They then have to be implemented
73. into the individual regulatory systems
74. of jurisdictions of countries around the world.
75. The end result is that the AML,
76. Anti-Money Laundering requirements,
77. the KYC, Know Your Customer requirements
78. in the United States,
79. or Europe,
80. or Singapore,
81. or Hong Kong,
82. or Japan,
83. Mainland China
84. are all very similar but not identical.
85. Now, if you are a large financial institution
86. which is doing business
87. across these major economies,
88. part of your regulatory requirements
89. are to comply with the requirements
90. for KYC and AML
91. in each jurisdiction in which you operate.
92. And the number of regulators,
93. particularly those in the United States
94. have put in place some very large fines,
95. multiple billions of US dollars
96. against large financial institutions
97. like HSBC,
98. Standard Chartered,
99. BNP Paribas
100. for failures to
101. properly have global systems
102. to know their customers
103. and prevent money laundering.
104. As a result,
105. financial institutions have had to
106. implement systems
107. whereby they can at a moment’s notice
108. know who all of their,
109. in many cases,
110. tens of millions of customers all over the world are,
111. and where they’ve gotten their money,
112. and whether they raise any risks
113. of criminal use of the financial system
114. or terrorist financing.
115. And the only way
116. the financial institutions
117. have been able to do this
118. is spending large amounts of money
119. on employing people
120. and building technological systems
121. to standardise account opening processes
122. and the various reporting requirements
123. that money laundering
124. and KYC regulations
125. around the world apply.
126. Another area that we’ll see
127. is what is called MiFID II.
128. MiFID II is the Markets in Financial Instruments Directive
129. in the European Union.
130. And MiFID II requires transparency.
131. It requires disclosure of
132. massive amounts of information
133. in particular about financial institutions,
134. securities and derivatives trading activities.
135. A very good example,
136. Merrill Lynch in 2017 was fined
137. almost 45 million British pounds
138. for failing to report
139. almost 75 million transactions
140. over a two year period.
141. Now, that is
142. roughly 150,000 transactions a day
143. for every business day
144. over that two year period.
145. And the only way that
146. a financial institution
147. can possibly keep track of
148. that amount of trading activity is through
149. building automated compliance systems
150. to package and report
151. the information to regulators.
152. So, from the standpoint of regulators,
153. the incumbent financial industry,
154. particularly banks have so far been
155. a major driving force.

4.5 RegTech Eco-system: Start-ups

1. Predicted to be one of the fastest growing sector
2. of 2018, the RegTech startup ecosystem
3. has grown rapidly to match that expectation.
4. Entrepreneurs are driven
5. by the US$100 billion market opportunity
6. that represent compliance spending.
7. This has created a market of over 300 startups
8. which is fueled by
9. cumulative US$100 billion of investments
10. by VCs since 2012.
11. To better understand the RegTech startup ecosystem,
12. let’s start with some context.
13. With the USA setting the tempo
14. of global regulatory changes
15. and characterised by a fragmentation
16. of supervisory bodies,
17. most of compliance spending will occur there.
18. However, whilst the USA represents
19. a strong natural client,
20. the startup creation activity
21. is predominantly based in Europe.
22. As for Asia, the region represents
23. 1/3 of global compliance spending
24. but is underserved by home-grown RegTech startups.
25. The 2008 financial crisis
26. has represented a strong catalyst
27. for regulatory changes across the world.
28. The combination of fines, over 321 billion,
29. regulatory changes which have tripled
30. in the last three years
31. and post-crisis reform implementation
32. such as Dodd-Frank or Basel III
33. has forced banks to increase their operating costs
34. as a response to their new regulatory obligation.
35. To just give you a sense of scale,
36. a financial institution like JPMorgan has added
37. another 14,000 legal and compliance staff since 2012.
38. It is not unusual for banks
39. to have 20 to 30% of their employees
40. working in compliance-related function.
41. This means that a tier one universal bank
42. has more compliance officers and lawyers
43. than Facebook has total employees.
44. However, the number of recurring fines
45. occurring post crisis is challenging the effectiveness.
46. However, the numbers of recurring fines
47. occurring post-crisis is challenging
48. the effectiveness of simply adding up
49. human resources to meet compliance obligation.
50. Indeed, for each one dollar spent on compliance,
51. three are being spent on regulatory fine.
52. It seems that the compliance industry
53. has difficulty to learn from its mistake.
54. This is what RegTech startups
55. are trying to address.
56. A decade has passed since the crisis
57. and since then most regulatory changes
58. have been implemented.
59. Financial institution are therefore now starting
60. to look at how to automate compliance obligation
61. and decrease the added recurring cost
62. that has built up post crisis.
63. RegTech startups are answering these demands.
64. RegTech companies can be classified
65. in three broad categories.
66. Each time I will quickly illustrate them.
67. First, regulatory compliance.
68. Here we are going to find companies
69. that are learning about regulatory changes
70. and telling banks how this is going to impact
71. their business logic.
72. Second, risk management.
73. It’s about identifying, for example,
74. conduct risk to prevent another Libor scandal.
75. Third, financial crime.
76. How can we understand the ultimate beneficiary
77. behind a shell company to avoid money laundering
78. or terrorism financing?
79. Within these three categories,
80. the vast majority of startups
81. are found in the regulatory compliance space.
82. This reflects the fact
83. that this represents a low hanging fruit for success
84. mainly because data is available,
85. it requires limited integration
86. and it has a lower risk factor
87. in case of error by a RegTech company.
88. Similarly to FinTech companies,
89. the majority of RegTech companies
90. are B2B providers selling to financial institutions.
91. Whilst demand from this client base is strong,
92. it appears that the sales cycle remains long.
93. On average, we’re talking about 12 months.
94. Certain exceptions are noted
95. especially in the context of
96. upcoming regulatory deadline
97. such as MiFID II or GDPR
98. which therefore fast track the sales cycles
99. and the procurement process.
100. Additionally, I would like to mention
101. that RegTech startups can also be found
102. in two other areas worth mentioning.
103. Firstly, regulators.
104. The B2G or business-to-government space is growing.
105. Regulators globally are engaging RegTech startups
106. via various channels from hackathons
107. to accelerators to find solution
108. to enhance the supervisory and regulatory function.
109. Similarly to financial institution,
110. regulators are driven by the cost benefit
111. provided by RegTech startups
112. that can reach a factor of up to 10 times.
113. These savings are actually especially important
114. when considering the fact that tax payers’ money
115. is used to finance regulators
116. and their operating costs
117. making it a strong public policy case.
118. However, whilst having regulators as a client
119. brings a lot of legitimacy,
120. the lengthy procurement process
121. is extended by additional tendering rules
122. relative to sourcing supplies
123. from the public sector.
124. Secondly, certain FinTech companies
125. are directly adding regulatory compliance process
126. into their product.
127. For example, in the context
128. of wealth management space,
129. funds products are now being sold
130. and marketed only to pre-qualified investors
131. by leveraging on their data
132. to determine suitability, location and investment profile.
133. Whilst for consumers, this provides
134. a level of personalization of services;
135. for financial institutions,
136. this embeds regulatory compliance
137. into the sales process
138. and that’s important
139. because it allows to avoid fines relative to mis-selling.
140. Previously what the financial crisis has highlighted
141. was that compliant and sales function
142. were operating in silos.
143. This overview concludes
144. the RegTech startups ecosystem of Module 4.

4.6 RegTech Start-ups: Challenges

1. Welcome back.
2. Let’s talk about the very exciting topic of RegTech,
3. RegTech, short for regulatory technology.
4. But first, what is RegTech?
5. RegTech is the use of new technologies
6. to solve regulatory and compliance burdens
7. not only more effectively but also more efficiently,
8. and this has been an area that has been
9. really booming in recent months and years.
10. Why is that?
11. Well, since the financial crisis,
12. banks and other financial institutions
13. have hired thousands of compliance officers
14. or risk officers to try to help them comply with
15. the various regulatory requirements around the world.
16. Well, the good news now is we could use
17. some of the latest technology,
18. from artificial intelligence to big data analytics,
19. to try to tackle some of these issues
20. in many ways better than humans can.
21. Let me give you a good example,
22. anti-money laundering.
23. Today, trying to stop the proceeds
24. from criminal organisations or rogue nations
25. from entering the global financial ecosystem
26. is a big challenge.
27. And, despite all our efforts,
28. of all the different AML procedures
29. and prophecies that we have in place,
30. the success has not always been there.
31. According to a recent study,
32. we’re only able to capture
33. less than 1% to 2% of laundered transactions
34. around the world from entering the financial ecosystem.
35. Well, the good news is this is hopefully
36. an area that RegTech can help.
37. We can use artificial intelligence
38. and actually try to actually spark
39. and actually improve the process of how we filter
40. and actually monitor these transactions.
41. And this is happening across
42. various, various, various verticals
43. of the broader regulatory space,
44. from KYC, know your customer,
45. and onboarding to regulatory reporting.
46. But although RegTech sounds very interesting,
47. that has also a lot of challenges.
48. For example, if you’re a RegTech startup
49. and you’re trying to sell to a bank,
50. the sale cycles can be very, very long.
51. Think about it.
52. You know you’re dealing with
53. a lot of sensitive information
54. and actually a lot of regulatory information,
55. where the downside for a bank for getting
56. it wrong is actually very big.
57. So, we actually are seeing these long sale cycles
58. that are common when you’re trying to sell to a bank
59. actually be even longer when it comes to RegTech.
60. Also, not everybody,
61. when it comes to in risk or compliance functions
62. are as familiar with RegTech.
63. While a lot of the business functions of a bank
64. got familiar with FinTech in the last couple of years,
65. we’re still in the early stages when it comes to RegTech
66. with people in risk, compliance, or legal functions.
67. But also probably more importantly,
68. if a bank wants to use this new technology
69. they need to be able to integrate this
70. inside of the spaghetti of their legacy systems,
71. all these different systems that the bank has been
72. implementing over the years and now try to find a way
73. to use this new technology to come in
74. and actually be able to use it.
75. So, there are still a lot of challenges,
76. but the good news is we finally
77. have a lot of the solutions available
78. to help financial institutions,
79. not only be more effective, but also be more efficient
80. when it comes to regulations.

4.7 RegTech Ecosystem: Regulators

1. The RegTech Ecosystem,
2. in addition to traditional financial institutions
3. and startups,
4. also extends to regulators themselves.
5. Think about it for a moment.
6. In the context of KYC requirements,
7. one of the major elements
8. of a compliance framework,
9. of the regulatory framework,
10. is filing of what are called
11. suspicious transaction reports.
12. Any time a transaction,
13. in most jurisdictions,
14. over 10,000 US dollars is done in cash,
15. that financial institution will have to
16. file a report with the regulator.
17. Likewise, any time
18. any unusual transaction takes place
19. with any of a bank’s millions of clients,
20. a suspicious transaction report must be filed.
21. Now, think about this
22. from the standpoint of regulators
23. that are receiving
24. thousands of suspicious transaction reports
25. from banks every single day.
26. What do they do with these?
27. Is it simply pieces of paper
28. that they store in a warehouse?
29. And historically,
30. that is very often been the case.
31. If an event would happen,
32. a terrorist attack
33. or a criminal conspiracy of some sort,
34. regulators would then
35. trawl back through those records
36. to see if they could identify
37. any additional information.
38. But a better system would be
39. regulators putting those reports
40. in a digital format,
41. which can be immediately
42. subjected to data analytics,
43. which would not only be useful
44. after a terrorist attack occurs,
45. in the context of tracing the financial flow,
46. but it could potentially be used
47. to prevent attacks
48. or a criminal use
49. of the financial system.
50. And that is the idea of RegTech.
51. Regulators themselves applying technology
52. to achieve better regulatory outcomes.
53. After all, anti-money laundering rules
54. are not about
55. producing suspicious transaction reports.
56. They are about
57. reducing the criminal or terrorist use
58. of the financial system.
59. And so,
60. if technology can be applied
61. by both the financial institutions themselves,
62. as well as regulators,
63. to better achieve that objective
64. that is a very important development,
65. and one of the biggest trends
66. that we’re seeing in the context of
67. today’s financial markets.
68. Now, if we look at regulators,
69. it is, in fact, not new for them
70. to use technology in regulation.
71. One of the longer-standing uses of technology
72. by regulators in the context of regulation
73. occurs in the context of insider trader,
74. insider dealing.
75. Insider dealing takes place
76. when an insider of a company
77. listed on a stock exchange
78. buys or sells shares of that company
79. on the basis of information,
80. which is not available to the public.
81. Remember we saw
82. with the efficient market’s hypothesis
83. that the idea of market’s functioning
84. is based upon availability
85. and if someone is using information
86. to profit in markets,
87. which is not more widely available,
88. one, that is not good
89. for market functioning
90. and market trust,
91. but it’s also unfair to other participants.
92. One of the most common places or times
93. that insider dealing takes place
94. is in the context of
95. the announcement of a merger or acquisition.
96. That will typically take place
97. at a certain day,
98. a certain time,
99. and regulators will use
100. the electronic trading records
101. of the stock exchange,
102. and will look back
103. through six months of data
104. to see if there were
105. any unusual transactions by insiders,
106. like corporate directors or their families,
107. during the period in the run-up
108. to that announcement.
109. That could then trigger an investigation
110. and potentially an enforcement action.
111. That is RegTech.
112. Today if we’re looking at areas of
113. regulators using RegTech,
114. probably the three biggest that we see are,
115. first, in the context of
116. applying big data analytics techniques
117. to the massive amounts of regulatory filings,
118. which have exploded
119. since the 2008 global financial crisis.
120. Like a large financial institution
121. is having to make several thousand reports
122. to regulators around the world every day,
123. regulators likewise
124. are receiving thousands of reports,
125. and are increasingly using that information,
126. subjecting it to data analytics,
127. in order to identify potential market risks
128. or market violations.
129. A related idea is
130. what is called macroprudential policy.
131. Prior to the global financial crisis,
132. regulators tended to focus on
133. the safety and soundness
134. of individual financial institutions.
135. The idea was that if you prevented
136. each individual bank from failing
137. that would prevent a financial crisis.
138. What the 2008 crisis showed is that
139. sometimes it is the interlinkages
140. between participants in a financial system
141. that causes the crisis.
142. It is not what one is doing,
143. but the fact that
144. everyone is doing the same thing,
145. and when a certain trigger event happens,
146. it causes problems
147. in the entire financial system.
148. Since the global financial crisis,
149. regulators have spent
150. a very significant amount of effort and resources
151. on coming up with ways
152. to try to prevent crises from happening
153. before they take place.
154. And one of those areas
155. is using data analytics,
156. in particular in the context of regulatory filings,
157. to try to identify risks
158. prior to them actually happening.
159. And finally, one that we’ve seen before,
160. cybersecurity.
161. As the financial system
162. has become increasingly digitised,
163. that has also increased its risks
164. of hacking and cybersecurity.
165. Perhaps the best example of this in recent years
166. has been the hacking of Equifax.
167. Equifax is a large company in the United States,
168. which provides credit rating services.
169. It collects massive amounts of data,
170. uses that data to provide a credit score,
171. which banks and other financial institutions
172. then use as the basis of lending decisions.
173. In 2017, it announced that all of its data
174. had been hacked
175. of over 140 million people.
176. And that highlights that,
177. as a financial system becomes more digitised,
178. the risks of cybersecurity go up.
179. And many would say today that
180. cybersecurity is not the biggest financial risk,
181. it’s not the biggest economic risk.
182. Many would, in fact, say,
183. that it’s the biggest national security risk as well.
184. Because, after all, in addition to
185. disrupting or stealing money,
186. hackers can also seek to
187. bring down large financial institutions
188. in an effort to cause
189. the collapse of the financial system
190. and the economy.
191. So, like financial institutions and startups,
192. regulators, too, are a major part
193. of the RegTech Ecosystem.

Payments & the Regulatory Landscape in Asia Pacific (KorumLegal)

1. Hello, welcome to this lecture on payment services
2. and the regulatory landscape for them in Asia Pacific.
3. I’m Danh Nguyen, the General Manager
4. and Managing Consultant for EMEA of KorumLegal.
5. Most people are familiar with
6. the term “financial services”.
7. Less is understood about “payments”.
8. Not many people know or understand what it means.
9. “Payments” has traditionally been neglected
10. or underserviced as an area of the law
11. and as a subset of general banking
12. and financial services.
13. This is out of step with how payments
14. have quickly evolved to become a hotspot of
15. commercial and FinTech activity in recent years.
16. In addition to the more traditional players
17. such as the high street banks
18. and credit card companies,
19. like MasterCard and Visa,
20. and global remittance players like Western Union,
21. MoneyGram, PayPal,
22. new players are constantly emerging.
23. These include Monzo, Airwallex, TransferWise,
24. WorldRemit, TransferGo, Aussie Forex,
25. Paybase, Azimo, the list goes on.
26. The level of innovation
27. in this space is dizzying
28. and many hundreds of millions of dollars
29. are being poured into these companies
30. by astute investors.
31. So, what do we mean by payment service?
32. At its simplest, a payment service
33. is any service provided by a financial institution
34. to allow a person or a business to pay
35. another person or business
36. for a product or service.
37. A payment service provider offers merchants
38. online services for accepting electronic payments
39. by a variety of payment methods
40. which includes credit cards,
41. bank-based payments such as
42. direct debit, bank transfers,
43. and real-time bank transfers
44. based on online banking.
45. Typically, they use a Software as a Service model
46. and form a single payment gateway
47. for their clients to multiple payment methods.
48. Payments also cover
49. money transfer and remittances,
50. cross-border payments
51. including consumer to consumer,
52. business to business, consumer to business,
53. and business to consumer,
54. and credit cards, debit cards,
55. stored-value cards, and so on.
56. Now that you understand better
57. what is a payment service,
58. let’s now touch on the regulatory frameworks
59. for payment services in the Asia Pacific region.
60. Until about eight years ago,
61. the regulatory landscape for payments in APAC
62. was relatively light-touch.
63. Regulations were playing catch-up
64. with the new technologies
65. which allowed for an abundance of
66. new products and services to emerge,
67. including FinTechs.
68. The existing regulatory frameworks in many countries
69. were simply not equipped to
70. address the many challenges
71. and risks posed by these new technologies,
72. products and services.
73. Most of these laws were enacted at a time
74. when these technologies did not exist
75. or weren’t contemplated.
76. For example, in Singapore,
77. the relevant law,
78. the Money Changing and Remittance Business Act,
79. dates from 1979 and remained largely intact
80. with few substantive updates
81. or modifications for 40 years.
82. The new law to replace it,
83. the Payment Services Act 2019,
84. was only gazetted in February 2019.
85. It’s expected to come into effect sometime
86. at the end of this year or early 2020.
87. In Australia, remittance services
88. and remittance service providers
89. were not regulated until 2011
90. when the Anti-Money Laundering
91. and Counter-Terrorism Financing Act, 2006
92. was substantially amended to provide for this.
93. Lawmakers could not have imagined
94. the full potential of technology
95. to fundamentally transform how payment services
96. would be provided to consumers
97. and businesses in the digital age.
98. Few could have predicted that you could send
99. and receive money via your online messaging app,
100. or with a few simple clicks on your smartphone,
101. you can open a bank account
102. or apply for a debit card.
103. But lawmakers and
104. regulators entrusted to enforce them
105. have been catching up.
106. They’ve been busy enacting new laws,
107. or amending existing ones,
108. to regulate these new activities and products.
109. Since 2010, we’ve seen new payments
110. or funds transfer laws being enacted
111. in Japan, Singapore, Malaysia,
112. Thailand, Indonesia, Australia,
113. New Zealand and the Philippines.
114. While each national law is different,
115. they all essentially share some common themes.
116. They all focus on AML/CTF compliance,
117. good governance,
118. effective technology risk management,
119. the need for robust internal controls
120. and frameworks, and consumer protection.
121. For example, those against risks of fraud
122. and unauthorised use
123. or mishandling of customer funds.
124. I will now speak a little more in-depth
125. about one of these new laws,
126. the Payment Services Act in Singapore.
127. The stated objectives of
128. the Monetary Authority of Singapore,
129. the Central Bank of Singapore,
130. were to streamline payment services
131. under a single legislation,
132. enhance the scope of regulated activities
133. to address current and future developments
134. in payment services,
135. calibrate regulations according to the risks
136. the activities pose by
137. adopting a modular regulatory regime.
138. The Payment Services Act
139. adopts an activity-based approach
140. to the licensing and regulation of payment services
141. and classifies them under seven key activities.
142. You can see these on the screen right now.
143. More than one activity can be engaged in,
144. but only one licence will be
145. needed to cover all activities.
146. Retail payment activities will be grouped
147. into three main licence classes.
148. Money changing licence,
149. standard payment institution licence,
150. and major payment institution licence.
151. The regulation of licensees
152. is calibrated according to their activities
153. based on the risks
154. and these regulatory concerns.
155. Money laundering and terrorism financing,
156. consumer user protection, interoperability,
157. and technology risk management.
158. No doubt, the emergence of new technologies
159. has created tremendous opportunities
160. for new players to enter
161. this exciting and dynamic market.
162. The financial services sector
163. was ripe for disruption.
164. Consumers have greater choice
165. when it comes to the types and
166. availability of financial services products.
167. This has also enhanced financial inclusion
168. and access for everyone.
169. But with new opportunities,
170. there are additional legal
171. and compliance obligations and risk.
172. Regulatory and compliance burdens for players
173. seeking to operate in this space
174. can be quite onerous
175. and shouldn’t be underestimated.
176. Scrutiny from regulators in the region
177. has increased significantly.
178. Regulators expect payment service providers
179. to have in place robust compliance,
180. risk management and governance frameworks
181. to ensure that they can meet their legal
182. and regulatory obligations,
183. and to protect consumer rights and interests.
184. There needs to be a thoughtful approach
185. to compliance and risk management
186. which will help the company to establish
187. disciplined management of financial crimes,
188. operational risk and consumer protection.
189. Regulators also expect providers to
190. take active steps to enforce the compliance
191. and risk management framework,
192. and to monitor compliance
193. against the requirements.
194. Navigating through these complex and
195. onerous legal and regulatory regimes
196. can be daunting.
197. The costs of compliance can be high.
198. In some cases, this may affect
199. the commercial viability of their business.
200. So having in place a well-thought out strategy
201. and an effective and robust compliance
202. and risk management framework will help
203. the payment services providers
204. to take full advantage of the opportunities
205. that the new technologies offer.
206. It can also cushion the business
207. from the downside risks
208. of running a non-compliant business.
209. The legal, financial and reputational risks
210. for the company
211. and for its senior management team
212. are far too great
213. to simply ignore or downplay.
214. But where the company has a good understanding
215. of the regulatory requirements
216. and a culture of compliance is promoted
217. and embraced by senior management,
218. the company is positioned well for success
219. in this burgeoning area.

Industry Showcase: The Application of AI in Smart Regulation (Interview with John Craig from Mindbridge)

1. Well, I think regulators are looking at technologies
2. and startups such as MindBridge
3. to be able to introduce new technologies and new ideas
4. faster into the industry.
5. In particular, in our case, we’re working with
6. machine learning, artificial intelligence
7. with organisations such as the Bank of England.
8. And using that technology,
9. they’re able to better review and regulate
10. say the credit unions in the United Kingdom.
11. So they use machine learning, artificial intelligence
12. to be able to look at the liquidity ratios,
13. make sure that the banks are performing
14. the way they’re supposed to,
15. and analysing for things such as trend shock
16. when the bank introduces a new policy,
17. how are all the credit unions changing
18. in relation to each other
19. and being able to better understand
20. the different changes in policy that
21. bank makes relative to the credit unions.
22. I believe that regulators feel that
23. startups are a cost benefit
24. because they’re able to
25. accelerate the use of the technology
26. within their sphere of influence.
27. Well, here in Asia, the industry players
28. that are leading the charge are
29. groups like the Hong Kong Exchange.
30. And from a regulator perspective,
31. I certainly see, you know, strong movement from
32. say the Hong Kong Monetary Authority
33. in terms of using technology
34. such as artificial intelligence and machine learning
35. to better understand the regulatory market.
36. I think it’s already begun.
37. I think regulatory technology
38. has already started to become a widely used term
39. in the industry, and as such,
40. I think it’s going to only grow from here.
41. It’s certainly well-established in North America,
42. and I think it’s quickly gaining pace here in Asia.

4.8 Regulatory Sandboxes

1. We’re now going to talk about Regulatory Sandboxes,
2. a safe harbour for
3. supervised innovation in financial market.
4. The general perception of regulators
5. is that they are slow and reactive.
6. The Dodd-Frank Act illustrates this.
7. It was passed in 2010,
8. but its full implementation
9. remains a work in progress.
10. In almost ten years that have passed
11. since the great financial crisis,
12. what has emerged strongly is FinTech.
13. Whilst the regulators have been
14. implementing post-crisis reform,
15. entrepreneurs have been busy.
16. Today with the regulatory houses in order
17. regulators are being to also embrace
18. forward-looking innovation.
19. The best illustration of this is the speed
20. at which Regulatory Sandboxes have been announced.
21. So far, over 12 have been announced in the world,
22. out of which six have emerged in the last four months
23. and the majority of them are in Asia.
24. One might argue that
25. the boom in Regulatory Sandboxes
26. is yet another reactionary move driven by
27. the jurisdiction’s fear of missing out
28. on the chance of becoming or staying
29. a meaningful financial centre.
30. One can also argue that the intent behind establishing
31. a Sandbox matter as much, or more,
32. than their narrow regulatory outcome.
33. Establishing a Sandbox demonstrates
34. a Regulator’s desire to move forward
35. towards a more proportionate regulatory framework
36. that bounces risk with innovation.
37. And whilst most Regulators seems to have realised
38. that Sandboxes are not child’s play
39. many are yet to invest adequate resources
40. into their operation,
41. either from a human capital perspective
42. or technical capacity.
43. Similarly, as with startups,
44. Regulators will have to enter into
45. a reiteration cycle to improve
46. the quality of and add value to their Sandboxes.
47. Regulators will need to keep their visions alive
48. as Sandboxes are unlikely in the first year
49. to deliver much by ways of result.
50. Perhaps most importantly,
51. regulators must ensure
52. that in the event of another crisis
53. they do not fully revert from the proactive approach
54. that they have towards yet another reactive one.
55. In other words, the innovative spirit
56. of regulators needs to be nurtured and maintained
57. as it does with entrepreneurs.
58. Each needs to learn from the sum of their experience.
59. Similarly to startups,
60. regulators should cherish
61. the journey because innovation
62. and its effective regulation are ever evolving processes.
63. This is not to say that regulation
64. always follows innovation.
65. India and Europe have demonstrated how reform
66. can spur innovation and the rise of FinTech.
67. However, we need to ask the question
68. of how a proactive
69. and adaptive regulatory framework can be created.
70. At the core of this vision lies the numbers of
71. well explored and established principle for regulators.
72. First, financial stability at the macro and micro level.
73. Second, market integrity and
74. third, consumer protection.
75. The challenge is using technology to develop
76. a better way of doing things
77. from the standpoint of regulators,
78. the industry and infrastructure.
79. As an example, whilst all regulators agree
80. on the importance of AML and KYC,
81. there has been limited harmonisation
82. with respect to this most common form of compliance.
83. Too often, the spirit of the law
84. is distorted by its implementation.
85. In the context of banks, this often takes
86. the form of banks and regulators blaming
87. the other for each failing to take
88. the responsibility in addressing
89. the question of why they cannot innovate.
90. Lack of innovation is blamed on
91. a mutual misunderstanding as to what is possible
92. and how it can practically be achieved.
93. Regulatory Sandboxes should become the new form
94. for discussion in which the dominant outcome
95. is promoting innovation rather
96. than only trying to reduce risk.
97. This means that the regulator should not seek
98. to prevent all risk from occurring,
99. but instead evaluate whether
100. an innovation enhances or decreases risk
101. in comparison to what already exists.
102. Let’s take some examples.
103. First, it’s about accepting driverless cars
104. because they are statistically less likely
105. to generate an accident as opposed
106. to failing to support them because
107. they have caused one or two accidents.
108. Second, it’s about supporting facial recognition solution
109. as the instances of fraud associated with them
110. is likely to be far lower than
111. with traditional chip and pin mechanism.
112. For this to happen, regulators
113. will need data and a lot of it.
114. This is to ensure the true risk association
115. with a given innovation are adequately estimated.
116. Foreign experiences should also be taken
117. into consideration as their data are used.
118. The depth and size of the data necessary
119. has placed immediate pressure
120. on regulator’s resources.
121. With limited staff,
122. regulators will hit a bottleneck
123. in their review, evaluation,
124. and approval of innovation.
125. As a result, regulators need to start
126. embracing machine learning tools
127. which will allow them
128. to better understand large and unstructured data sets.
129. For now, the largest simulation in the world is in China.
130. China doesn’t need a regulatory Sandbox
131. because the whole country is one.
132. In its technology firm other kids playing in it.
133. When Alibaba released
134. its experimental credit scoring tool,
135. Sesame Credit, it was quickly apparent
136. that its credit scoring algorithm
137. was being gained by its users.
138. Sesame Credit was underpinned by the assumption
139. that the more a person spends or receives,
140. the more credit worthy they are.
141. However people quickly started
142. to send the same amount
143. of money back and forth in order
144. to increase their credit score.
145. The unusual patent allotted to Alibaba
146. and lent to the algorithm being readjusted.
147. However, not every country has the capacity
148. to run control experiment on the scale of China.
149. These countries will either have to rely
150. on machine learning tools or accept the risk
151. of regulation lagging behind innovation.
152. This is why Regulatory Sandboxes represent
153. a critical addition to the toolkit
154. of innovation available to regulators.

Industry Showcase: Balancing Innovation and Regulation Challenges in Hong Kong (Charles Mok)

1. Now even in the context of China,
2. we have seen some of the developments
3. get to such a stage where they’ve had to come in,
4. develop regulatory frameworks to balance out risks.
5. And this is something that I think
6. we’re seeing around the world
7. and this is the idea of piloting,
8. or a test-and-learn approach, regulatory sandboxes.
9. And this idea of sandboxes was something
10. that I wanted to ask you particularly about,
11. coming from the tech side of things, and that is,
12. we have these new regulatory sandboxes in finance,
13. but where does this idea come from?
14. It’s a good question.
15. I think some of the regulators around world
16. starting doing it first
17. but Hong Kong started looking at it
18. a couple of years ago, and said that particularly
19. because as we said in our regulatory regime,
20. we have to follow rules.
21. Some companies come out and say
22. I’m going to raise funds in this particular way,
23. I’m going to issue a cryptocurrency
24. in this particular way,
25. and it’s that violate the existing laws.
26. We’re not going to be able to allow them to do that,
27. but if that’s the case,
28. how do we balance the need for innovation
29. and giving some of these things a good try?
30. So we’ve been advocating that we should be trying
31. this particular approach. You know, for Hong Kong,
32. I think we have had some experience
33. in the last couple of years.
34. I hope that we would provide more incentives
35. for some of these companies or banks
36. or other institutions to try.
37. Initially, the regulators were a bit more conservative,
38. they only allowed banks to try
39. and then the rest of the innovators,
40. the startup companies, said well, then what do I do?
41. I have to partner with a bank?
42. Which means that in some cases
43. this is exactly the reason
44. why they want to do what they want to do
45. is to not to work with the banks.
46. So there have been some struggles in the beginning.
47. An added problem for Hong Kong would be the facts
48. that we have three different regulators,
49. for banks, for insurance, and for securities,
50. so which means that sometimes
51. these regulatory sandbox environment
52. would be a little bit more complicated.
53. So those are being worked on and
54. I think the regulatory sandbox experience is improving,
55. but I just came back from Silicon Valley,
56. having visited some of the companies over there,
57. including some of the startup companies
58. in FinTech over there.
59. I think what we need is a bit more promotion,
60. because that’s also important.
61. Sometimes they say
62. hey, we didn’t know that Hong Kong,
63. you have this particular environment
64. that we could give it a try.
65. But I’ve heard of other economists or countries saying
66. that they have this regulatory sandbox.
67. So I think now that we have something
68. that might be might be good,
69. we’d better give it the right promotion
70. to make sure that more people
71. around the world know about it,
72. because after all, one of the most important things
73. about FinTech that I believe, is that the nature of it
74. is going to be quite global.
75. And also that’s one of the advantages
76. that Hong Kong has
77. is being a traditional financial services centre.
78. We have the expertise, we have the banking
79. and the financial service expertise in Hong Kong,
80. not to mention the technology expertise.
81. And so we should leverage this particular advantage
82. to attract more startups or people around the world
83. to say hey, maybe I should give my idea a good try
84. in Hong Kong.
85. Yeah, I very much agree with that.

4.9 Smart Regulation

1. We suggest that RegTech goes beyond
2. simple use of technology
3. for compliance or regulatory purposes
4. and also extends to cooperative efforts
5. between policymakers, regulators, startups,
6. and traditional financial institutions
7. to build better financial systems.
8. We call this the idea of smart regulation.
9. Smart regulation suggests that
10. in the context of today’s technological transformation
11. of the financial system,
12. it is possible for the first time
13. to redesign underlying infrastructure,
14. the plumbing of the global financial system
15. to make the financial system
16. work better and effectively,
17. The idea of this is first,
18. a need for better information and monitoring
19. that regulators need not only
20. to follow what is going on
21. in traditional financial institutions
22. but they also need to be aware of new entrants,
23. whether those are FinTech startups,
24. or TechFins,
25. and also evolution of technologies.
26. Whether those technologies
27. are things like cryptocurrencies,
28. blockchain, cloud techniques
29. or anything more that emerges
30. in coming years.
31. So the first stage is really
32. an understanding of what is going on.
33. Without an understanding,
34. a regulator cannot do a proper job
35. of balancing the objectives of
36. economic growth and financial stability.
37. From that basis,
38. one can work together
39. to design better systems.
40. And really, the starting point in smart regulation
41. is systems design.
42. It is the idea of digitising regulation
43. so that regulatory requirements
44. to the greatest extent possible
45. can be conducted or met by industry participants
46. in a digital form.
47. Digitising reporting requirements
48. and other compliance requirements
49. allows financial institutions to submit reporting
50. and other obligations to
51. regulators in a digitised form.
52. That process of digitization
53. immediately makes it more straightforward
54. for regulators as well as the industry
55. to apply processes of data analytics,
56. of datafication
57. in order not only to
58. better achieve regulatory objectives,
59. but also to reduce costs
60. and increase efficiencies
61. as well as discover new opportunities.
62. The idea of smart regulation
63. is that technology is no longer the limiting factor
64. in how a financial system or its regulation works.
65. But to take advantage of these new opportunities,
66. we must be aware of
67. what the technology can do
68. as well as the existing inefficiencies
69. in many of our systems,
70. and that is a RegTech process
71. of designing financial infrastructure.

4.10 Redesigning Financial Intrastructure: India Stack

1. This idea of designing better financial infrastructure
2. is core to the idea of FinTech and RegTech’s
3. re-conceptualization and reconsideration,
4. recreation of both domestic
5. and global financial systems.
6. We can see this happening
7. in two big examples.
8. The first is one that
9. we’ve already looked at in the EU.
10. The development of a series of
11. new legal frameworks
12. reflected in MiFID II, PSD2, and GDPR,
13. which are transforming the way
14. that the financial system
15. in the European Union works.
16. The second is in the context of India.
17. And something that we’ve seen
18. throughout the course so far
19. is that China is probably the most advanced,
20. the most exciting digital transformation
21. that we’ve seen so far in the context
22. of this FinTech environment,
23. but the other transformation
24. which is taking place now
25. is in many ways just as exciting,
26. and that is the digital transformation
27. that is taking place in India.
28. In India about eight years ago,
29. a group of tech entrepreneurs
30. set about designing a strategy
31. to build a new system of digital infrastructure
32. to transform not only the Indian financial system
33. but access to finance
34. by the majority of the Indian population
35. and also India’s economy
36. and economic growth prospects more generally.
37. In some ways, this was partially a reaction
38. to the success that we’ve seen
39. in China’s long-term economic transformation
40. since the late 1970s.
41. The idea in India is a series of interlinked pieces
42. called India Stack.
43. The foundation of the India Stack
44. is a new digital biometric ID system.
45. That digital biometric ID system
46. includes 10 fingerprints
47. and two iris scans
48. for each individual who is issued with an ID.
49. And since 2010,
50. over 1.2 billion people in India
51. have been issued with new digital IDs.
52. That is more than the iPhone sold
53. in the same period from its launch in 2007.
54. The digital IDs in India
55. are the largest IT rollout
56. in the history of the world.
57. Well, that’s a good start.
58. Digital identity to make it possible
59. for immediate authentication
60. of any individual’s identity.
61. The second level has been a system built on
62. an electronic payment system that is open,
63. open API,
64. which means that it is open
65. not only to traditional banks,
66. but also to new entrants.
67. This payment system allows digital payments
68. to be made from one ID holder
69. to another very rapidly.
70. It also allows the entrance of
71. new forms of business,
72. whether those are payment providers
73. or robo-advisory services
74. or P2P lending and others.
75. The third level involves
76. increasing the use of bank accounts.
77. And India three years ago,
78. only about 1/3 of its population
79. would have had a bank account,
80. roughly 350 million people.
81. Now, as a result of a process
82. whereby government salaries are paid into accounts,
83. pensions and other benefits,
84. agricultural supports and the like
85. are all paid into individual bank accounts,
86. there has been an explosion
87. in the number of bank accounts in India.
88. Over the past five years,
89. over 300 million new bank accounts
90. have been opened in India,
91. more than the population of the United States,
92. and to the point where now for the first time,
93. over half of the population of India
94. has a bank account,
95. a bank account that is linked to their digital ID
96. and to an electronic payment system
97. that allows instantaneous payments
98. across the financial system.
99. The final element of this system
100. brings us back to the ideas of KYC.
101. An e-KYC system, an e-KYC utility
102. where individuals have
103. a sort of Dropbox-like account
104. where they can place digitised documents
105. which are the necessary filing requirements
106. for KYC requirements
107. across a range of financial institutions.
108. As a result of this combination of factors,
109. India has not only exploded the number of people
110. using bank accounts
111. and using the financial system,
112. it has also dramatically reduced the time taken
113. and the cost for opening an account
114. and as an added benefit
115. dramatically reduced the cost of corruption
116. in a previously cash-based economy.
117. In November 2016,
118. the Indian government announced
119. an incredible experiment
120. what was called demonetization.
121. The government said that
122. 86% of the cash bills in circulation in the country
123. were no longer valid,
124. that those paper notes
125. had to be turned in at a bank
126. and either left in a bank account
127. or exchanged for new bills
128. which would be issued.
129. Now, the intention of this initiative
130. was to crackdown on corruption,
131. to basically catch dark money
132. that was operating
133. outside of the formal financial system,
134. but its big impact was in the context of
135. driving digital transformation
136. of the Indian financial system.
137. And that was possible
138. because of the infrastructure
139. which had already been put in place
140. via the India Stack strategy.
141. Literally, hundreds of millions of people
142. for the first time
143. are now using digital forms of money
144. for payments, lending and investing
145. that previously would have been cash based.
146. We have seen an explosion
147. in the amount of money in the financial system,
148. which has reduced interest rates.
149. It has also increased liquidity available
150. for startups seeking to raise money
151. in the economy.
152. And as with China’s digital transformation,
153. countries around the world
154. but particularly in Asia
155. have been watching India’s process very closely.
156. And an increasing range of countries,
157. from Bangladesh to Thailand
158. to Indonesia and beyond
159. are seeking to develop similar strategies
160. to enable them like China has done
161. and like India is in the process of doing
162. to leapfrog
163. to a new digitally based financial system.

Additional Resource Insights

References and Suggestions for Further Reading

1.  FinTech, RegTech and the Reconceptualization of Financial Regulation (Academic Paper: Arner, Barberis, Buckley)
2.  Financial Stability Issues from FinTech (Industry Report – Financial Stability Board (FSB))
3. Regulating a Revolution: From Regulatory Sandboxes to Smart Regulation (Academic Paper: Zetzsche, Buckley, Arner Barberis)
   
4.  RegTech 102: The Evolution of RegTech and the Future of Regulatory Compliance (Industry Report – CB Insights)

Module 5 Data & TechFin

Welcome to Module 5

5.1 Module 5 Introduction

1. Welcome back to the HKU FinTech course.
2. You are now in module 5,
3. and we’ll be talking about data.
4. As you may know, data is the new oil,
5. and what this means is that it becomes
6. an increasingly valuable commodity both for you
7. as individuals, financial institutions,
8. or technology companies.
9. In this module, we will be covering
10. each of these aspects.
11. First, we’re going to be talking to you as an individual.
12. How is GDPR in Europe
13. covering and impacting businesses
14. as well as you as an individual?
15. What about digital identity?
16. How a piece of password can now be condensed
17. in a piece of data,
18. and how that piece of data
19. can better define who you are,
20. and therefore customise experiences around you.
21. We’ll then be also looking
22. at the financial services industry.
23. They have been using data since the 1970s,
24. and have been able to deliver new financial products
25. on the back of this.
26. However, there is challenge on doing so at scale.
27. Startups and the FinTech transformation
28. is also one which is underlied by the use
29. of technology and data accessibility
30. both by technology companies
31. as well as the financial institutions.
32. On the technology company side,
33. we’ll be talking about the challenges
34. brought by TechFin companies,
35. as well as the governments of AI.
36. And finally, regulators.
37. The increased value of data means
38. that more and more people want to
39. access it by legal and illegal means.
40. And therefore, the regulation of data
41. from a data privacy perspective,
42. or the protection of data
43. from a technological perspective,
44. will also be addressed in this module.

Module 5 Learning Objectives

Module 5 discusses data, data regulation, data security and the emergence of TechFin. In focuses on both the opportunities as well as the risks and challenges arising from the process of digitization and datafication in finance, as well as policy and regulatory approaches and their implications for business.    

In Module 5, learners will:

• Understand the role of data in financial services
• Consider various approaches to data protection and privacy
• Think about the challenges of digitization and datafication, particularly cybersecurity and technological risk
• Discuss the emergence of TechFins and the implications for financial services    

5.2 History of Data Regulation

1. When looking at data
2. and how it has been regulated over time,
3. there are different elements to it.
4. First, we can approach data from a privacy perspective.
5. A lot of you can relate to this
6. when we look at data breaches that infect
7. your personal information being released to the public.
8. What has been happening with Facebook
9. and how that data, for example,
10. has been used in the context of political elections,
11. both in the US and in Europe.
12. Data privacy matters
13. because it’s all about protecting your personal life,
14. and that life is increasingly now online.
15. The second element is about
16. cross-border data management,
17. and whilst digitization is a global phenomenon,
18. cross-border data management
19. is not necessarily something
20. which is as automatic than one may think,
21. and there’s some right reason to do so.
22. Certain jurisdictions are, for example,
23. much more stringent about data residency rules,
24. where data can only be held and stored
25. in a single country and not leave it.
26. This is one of the big problems for FinTech companies.
27. Whilst FinTech companies have global ambition,
28. data regulation, especially on how
29. cross-border data management is done,
30. can be a real limiting factor for their ambition of growth.
31. Why? Because for example, a regulator in a Country A
32. may not want that the data of its consumer
33. transferred to Country B where it will be processed
34. and then the insight brought back to Country A.
35. This can be for many different reasons,
36. including national sovereignty and national security.
37. Since 2007, the financial crisis has shown
38. that financial services stability
39. is a national sovereignty issue, and as a result,
40. data residency and data protection is equally important.
41. The third element is data management.
42. This is how people will access and control their data.
43. One of the topic that, for example,
44. we’ve covered in Module 4 was GDPR,
45. and here it’s about this idea that
46. every single piece of data
47. should be able to be traced back
48. to its individual owner, if it identified him.
49. And if it does, that owner should have the right
50. of querying the institution who has seen that data,
51. how many times the data has been used,
52. and how the data is actually being used,
53. and in which countries.
54. This is the idea of data that could be accounted
55. as a liability or an asset, from a financial perspective.
56. However, from all perspective,
57. data and its regulation
58. should be looked from another angle.
59. It should be looked from an angle
60. where data equals money,
61. and all the rights and obligation attributed to it
62. should be similar to money.
63. Data would therefore have a property right,
64. a commercial right,
65. and that can be transferred, exchanged, borrowed,
66. or leased to someone else.
67. And this matters a lot.
68. It matters because it will allow digital identity
69. and data sovereignty to keep on growing as an industry.
70. It also matters because as the economy
71. is going from a service economy to a digital economy,
72. more and more individuals will be looking at ways
73. of monetising their data to supplement,
74. if not totally replace their income.
75. So far, this topic of data regulation hasn’t emerged yet
76. because the money that can be made
77. from data monetisation
78. has not passed the poverty line.
79. However, when this will happen,
80. a real question will be raised
81. at the regulatory and the policy level
82. on how that data regulation should be approached.
83. From a trend perspective,
84. we can imagine that this will mainly
85. happen in countries like Asia.
86. This is because, proportionally,
87. the value of data from an individual in Asia
88. is higher compared to their salary
89. to what you would have in Europe.
90. For example, someone in Vietnam
91. earning 8,000 US dollar a year,
92. but having their data worth 50 US dollar a year,
93. has a higher value as a proportion
94. of their data to their salary,
95. compared to a European person
96. earning 50,000 US dollars a year,
97. but only having 50 US dollar worth of data.
98. This is why the future of data regulation
99. and data being treated as money
100. is mainly going to come from places like Asia.
101. However, so far, the regulatory tempo
102. has clearly been set by Europe,
103. which has one of the most stringent and complete
104. regulatory regime around data management,
105. which is followed across the world and including Asia.

5.3 Data in Financial Services

1. The importance of data in the economy
2. has been captured by Professor Klaus Schwab,
3. executive chairman of the World Economic Forum.
4. His analysis entails that the world
5. is entering a fourth industrial revolution
6. powered by artificial intelligence
7. and being distinguished
8. in its characteristic of hyper scalability,
9. which we will discuss more in module 6.
10. Importantly, the fourth industrial revolution
11. has been built on top of the third era,
12. which started in the 1970s,
13. thanks to computer and automation.
14. As we have seen throughout this course,
15. technological progress
16. and financial market development
17. have a close relationship.
18. Professor Schwab’s third era
19. of computer and automation coincides
20. with the digitization of financial services,
21. which we discussed in module three.
22. And in this lecture, we are instead
23. projecting ourself forward,
24. aiming to answer the following questions.
25. How can the data created since the 1970s
26. be used meaningfully in financial services?
27. And what does the fourth industrial revolution look like
28. for financial markets?
29. The importance lies in the fact
30. that as with any large economic shift,
31. the relationship of money
32. and power is being redistributed.
33. As such, answering if financial institutions need
34. to become data companies matters.
35. Should their business model move
36. towards a data refining instead
37. of interest or fee-based income?
38. In order to find answers,
39. we will present three examples
40. in exploring in turns, big data,
41. artificial intelligence, and analytics tools.
42. Let’s start with the hedge funds industry.
43. They have historically been distinguishing themselves
44. by their capacity of using quantitative skills
45. and hiring a lot of Math scientists.
46. They have increasingly been leveraging
47. an external and new alternative data
48. to make better investment decisions.
49. For example, the use of geolocation data
50. was used to estimate the footfall
51. in shopping malls, and therefore predict
52. the growth of sales ahead of public quarterly reports,
53. allowing to make an investment decision
54. before public information is out.
55. In the context of the insurance industry,
56. we have seen usage-based insurance changing
57. the current flat-fee insurance model
58. and instead moving towards
59. a pay-as-you-go service
60. centred around your lifestyle.
61. This has been made possible by the increase
62. of telematic solutions,
63. such as trackers in your car,
64. or your mobile phone,
65. which is then analysed for better pricing.
66. Here, data is being used
67. to change the underwriting decision model
68. whilst becoming the most cost-effective option
69. for you as a customer.
70. Finally, in banking,
71. by using predictive analytics,
72. a bank is able to monitor the spending patterns
73. of a consumer, and then
74. infer if a larger purchase will be made.
75. The size of that purchase will then define whether
76. the bank should proactively propose
77. a consumer loan or mortgage.
78. Likewise, a very simple example
79. is taking a travel insurance as soon as
80. you buy a plane ticket with your credit card.
81. Now, these examples illustrate that data
82. has previously been used in financial services,
83. but this has not been equally done by all.
84. This is mainly due to the fact
85. that data today remains a by-product
86. of activity as opposed to a core asset that is valued.
87. To make this change across the industry,
88. new C-level roles are emerging,
89. such as Chief Data Officer.
90. Regulators are also concerned by this,
91. and you saw that in module 4
92. when we were covering the topic of smart regulation
93. and what it means from a human capital perspective
94. for the regulators.
95. Now, in order to enhance the value of data,
96. whether internal or external,
97. going forward, financial institution will need
98. to consider the three Vs of data.
99. First, volume.
100. The combination of behaviour tracking
101. and Internet of Things is increasing
102. the amount of data points available.
103. Second, velocity.
104. The speed at which data is created requires
105. the need for real time analytics,
106. as it challenges the current storage capacity.
107. Third, variety.
108. The ability to handle,
109. understand structured and unstructured data
110. from internal or external sources.
111. As this transformation process occurs,
112. FinTech startups are increasingly providing
113. the necessary analytical tools to process
114. and analyse data held by financial institutions.
115. For now, these remain narrow use cases
116. and include identification of credit risk
117. in loan portfolio, transaction of quarterly reports
118. into investment advice,
119. or performing complete audit risk review.
120. Whilst these have always been performed by banks,
121. today the combination of data availability
122. and analytical tools make it possible
123. to do these in seconds instead of hours,
124. and this is done without a trade-off on accuracy levels.
125. Hopefully, this will provide banks a capacity
126. to restore profitability levels,
127. whilst for consumer,
128. create a new era of invisible finance,
129. one that support your lifestyle instead
130. of creating friction as you’re trying
131. to achieve your goals.
132.  

Industry Showcase: Application of Data Analytics in Finance (vPhrase)

1. Hello everyone, I’m Neerav Parekh.
2. I’m the founder of a company called vPhrase.
3. We’re from India.
4. I’ll tell you about how AI
5. is being used in the data analytics space
6. for FinTech companies.
7. So, we created a product that a lot of institutions use
8. for improving their report.
9. Let me give you a few examples.
10. Motilal Oswal which is one of the largest brokerages,
11. they use a platform for creating portfolio analysis
12. for their investors,
13. so we examine 500,000 portfolios every month
14. and create statements for the investors.
15. The whole idea is to give them
16. the key insights in the portfolio, using language.
17. So, AI is being used to generate language from data
18. to explain all the insights to the leader.
19. So, that is one example.
20. Another large very large private bank in India
21. is using our platform to create personalised reports
22. for the branch managers,
23. so the whole performance of the branch,
24. all the data is taken in,
25. is analysed and language is written
26. to explain to the branch manager
27. how exactly is this branch doing.
28. So, a few bullet points we’ll tell him,
29. Ok if your branch’s achieving its targets,
30. which products that are doing well,
31. which products that are not doing well and so on.
32. Then there’s another large investment bank
33. which is using our platform
34. for risk analysis of stocks and mutual funds.
35. So, they study the performance of mutual funds,
36. they study the performance of companies
37. and we use that data to create risk analysis reports
38. for them on those stocks and mutual funds.
39. So, as you’ll see,
40. we’re using AI for data analysis
41. and then creating language,
42. natural language generation,
43. so that people can understand the data better.
44. Enterprises can make their reports
45. easier to understand for their people.
46. Thank you.

Industry Showcase (NEW): How Startups are Transforming the Asset Management Landscape in Hong Kong? (MioTech)

1. Hi, my name’s Jason Tu
2. and I am the CEO and Co-Founder of MioTech.
3. We are a startup for financial institutions
4. to better manage and draw insights into their data.
5. Our company is two years old
6. and we began this journey in Hong Kong,
7. the largest financial hub here in Asia.
8. Just how important is this market?
9. In 2018, the Hong Kong Stock Exchange
10. actually snatched the crown jewels of IPO listings,
11. raising more than US$36.6 billion for 208 companies.
12. Hong Kong’s Asset and Wealth Management Business
13. reached more than US$3 trillion Asset
14. on the management
15. based on SFC’s annual survey in 2017,
16. effectively making Hong Kong the No. 1 leader in Asia.
17. This is just to give you a gist of how important
18. financial services is to Hong Kong, and vice versa.
19. Now let’s take a look at the ecosystem
20. surrounding Asset Management.
21. For every trade, from the back office perspective,
22. it will go through custodians, exchange,
23. clearing and settlement agencies,
24. and possibly, fund administrators
25. until accurate information is reflected
26. in Asset Manager’s hands.
27. From a front office perspective,
28. for every investment opportunity,
29. the asset manager
30. needs to gather conventional data sets
31. such as prices, volumes, as well as,
32. unconventional data sets
33. such as news, and alternative data.
34. Asset Managers are at the top of the pyramid,
35. they digest all these information
36. in order to deliver return
37. and avoid risks on their financial assets.
38. So, where are the opportunities in this industry
39. for a startup
40. and particularly in Hong Kong?
41. This goes back to Hong Kong’s unique role
42. as the gateway to both China
43. and broadly speaking, Asia.
44. From the data and technology perspective,
45. the market data
46. and market intelligence industry in Hong Kong
47. is still dominated by
48. western market data providers,
49. with a lack of coverage
50. and understanding of the local markets.
51. These large multi-national players
52. also have decades of company history
53. and very large complex corporate structure
54. that don’t allow them to adopt new technologies
55. as fast as startups can.
56. The lack of data coverage on Asia
57. and slow innovation on the technology side
58. creates opportunities for disrupters to fill the gap.
59. From a product and user experience perspective,
60. the entire financial software industry
61. is lagged behind the consumer app
62. and Software-As-A-Service industry.
63. From Google, Facebook to Slack, Zendesk,
64. user centric design and browser based enterprise
65. applications have completely changed
66. both the consumer and enterprise world.
67. There is a huge opportunity to create a product
68. that adapts to the modern user
69. as compared to having clients to adapt
70. to decades-old financial software
71. that was created
72. before most of the younger traders were born.
73. The question is how?
74. There are a number of tips
75. I can offer to entrepreneurs
76. aiming to change the asset management industry.
77. First of all,
78. Hong Kong has unparalleled advantage
79. in its access to the Greater China Region
80. and the rest of Asia.
81. However, entrepreneurs should keep in mind
82. that understanding Hong Kong isn’t enough,
83. but rather, you should be eager
84. to learn the needs in Greater China and Asia,
85. the places where Hong Kong has access to,
86. that’s where your users are.
87. Second of all,
88. the asset management industry
89. already has a very complex business structure
90. compared to other industries.
91. We have to be very careful
92. about business model innovations,
93. and not to introduce more complexity.
94. Technology innovation, on the other hand,
95. has much more room to improve efficiency
96. and reduce complexity.
97. Last but not the least,
98. as I’m speaking here right now,
99. talent is the single most important factor
100. to innovation.
101. I’m hopeful that Hong Kong will attract
102. more technology talents to mix up
103. with these finance professionals
104. to disrupt and to make a difference together.

Industry Showcase (NEW): Digitisation of Financial Services – A DBS Approach (Parts 1) (DBS)

1. Disclaimer: Views expressed are personal and do not reflect the views or thoughts of any organization the speaker may be affiliated/associated with.
2. Ladies and gentlemen, just to set the scene
3. and introduce myself.
4. I’m Mark Li
5. and I run a digital program office
6. for transaction banking in DBS.
7. So I’m really happy to be invited
8. by the University of Hong Kong
9. to talk about the digitalisation of financial services,
10. So my first question to all of you is:
11. Why does a traditional bank need to go digital?
12. Why can’t traditional banks just stay
13. within their comfort zone
14. and run their business as usual?
15. The reason is pretty simple.
16. Just to stay competitive.
17. In recent years, we have been
18. experiencing gigantic changes
19. brought by internet companies
20. such as Tencent, Alibaba, Amazon, etc.
21. They are opening up
22. their own affiliated financial subsidiaries
23. to engage in businesses that traditionally banks
24. are doing for a really long time ago.
25. We also see an increasing number of
26. startup companies that are focusing on
27. a single banking function and customer segment.
28. Within this, you can always find
29. that they may do a better job
30. than banks in terms of customer experience
31. and product offering.
32. Cost is another reason.
33. By putting up brick-and-mortar data centre in the clouds,
34. banks will be able to enjoy a lower cost
35. while expanding the banking business.
36. I’m not here to promote any banks
37. or any digital aspiration
38. but there are a few things I wish I could share
39. which I have been strongly inspired
40. by the top management in DBS.
41. Once our CEO Piyush has said,
42. “DBS is not a bank anymore.
43. Our competitors are not our fellow friends
44. in our banking industry anymore.
45. Our competitors are what I mentioned just now,
46. Alibaba, Amazon and Google.
47.  
48. We have to think, act and transform
49. like a technology company.”
50. That’s why DBS is a 27,000 startup.
51. How does this bank transform themselves?
52. In short, the entire backend is 85% cloud.
53. Yes, it reduces cost, improve resilience and scalability.
54. Across Asia, they have more than 180 APIs
55. and 60 API partners.
56. And their connectivity for client ranges
57. from all kinds such as transacts,
58. FX enquiries and ecosystems.
59. And that they have a philosophy and practise
60. that digitalise the entire internal process,
61. increases productivity, joy space
62. (which is work without any fixed space)
63. that promotes collaboration across units,
64. space improvement and optimization.
65. This is what I believe the basics of a new digital bank.
66. And GANDALF, of course, it is quite a funny thing,
67. as all of you may have watched
68. “The Lord of The Rings and the Hobbit”,
69. GANDALF over there is very different from
70. the DBS GANDALF.
71. Here it means Google, Apple,
72. Netflix, I’ll put the D aside,
73. Amazon, LinkedIn and Facebook.
74. All of them are technology bigwigs
75. who have reinvented their products and ways of working
76. to suit the rapid technology advancements
77. and yes, this is a digital bank.
78. And of course, the D over here,
79. I hope it means DBS and of course, the digital bank.
80. This shows a bank aspiration to become one of
81. the disruptors that can change and rock the markets.
82. And most importantly, it is not only a slogan.
83. It means a fundamental culture change.
84. A shift from projects to products and delivery.
85. Developing high performing agile teams
86. rather than just project management,
87. automating everything, yes, everything.
88. Designing for modern systems
89. means simple deployment,
90. organising for success and most importantly,
91. adopting all of these habits of large innovation
92. by providing fresh and new user experience.
93. The best thing of it is they don’t work in the box
94. but focuses at client deliverables,
95. such as co-creating solutions alongside of clients,
96. practise business agile,
97. solving real-life problems,
98. and that is digital.
99. In consumer banking group,
100. we have APIs that promotes
101. instant credit card promotion from transaction banking
102. from where I come from, of course,
103. with corporate insurance firms communicating
104. and transacting with us through APIs.
105. For treasury and markets,
106. we quote rates and transact real time on FX
107. with clients through APIs.
108. Even from a system perspective,
109. we have created a blockchain community
110. with suppliers and anchors
111. to promote a better trade environment.
112. As you can see from these three examples,
113. we are fully automated from top to bottom.
114. From client interface to back-end processing.
115. From client’s connectivity to internal dot-and-node.
116. My experience of DBS, this bank,
117. the Digital Bank of Singapore, we always joke,
118. you can really feel a huge change and difference
119. in people’s mindsets.
120. The way they work, the way things are structured.
121. This 27,000 startup
122. is so willing to experiment
123. and practise with the customers
124. and one thing I’m really amazed
125. is that doing business reviews
126. or even day-to-day meetings,
127. we do not use PowerPoints or Excels.
128. We do not create meeting decks
129. but instead, we use dashboards and data
130. for business decision.
131. We are hugely obsessed with data.
132. Data is our DNA and data is our basis
133. for business decision.
134. Many examples I can quote in the business environment
135. how data is being utilised to justify investments,
136. our lending principles,
137. collaboration across business groups or data driven.
138. Traditional banks like DBS
139. can actually be a FinTech ourselves.
140. Transform ourselves into a digital bank
141. which embraces many qualities below.
142. Digital management and staff culture,
143. Cloud-based and API-based technology
144. across all kinds of clients’ footsteps,
145. open to external clients’ connectivity
146. and most importantly, they’re able to accept failure
147. and adopt to changes very, very quickly.

Industry Showcase (NEW): Digitisation of Financial Services – A DBS Approach (Part 2) (DBS)

1. Disclaimer: Views expressed are personal and do not reflect the views or thoughts of any organization the speaker may be affiliated/associated with.
2. Another critical part of digital transformation
3. is to understand the legacy issues we are facing
4. we not only for DBS but also as a bank as a whole
5. and we have to improve with a digital mindset.
6. A few legacy examples, physical cash for all of us today
7. who really comes up without physical cash
8. in Hong Kong and Asia?
9. Let’s talk about branch needs for banks,
10. whether you agree or not, there’s still a strong demand
11. for physical branches in Hong Kong and in Asia
12. what kind of services
13. really needs to be done in branches?
14. Or can we move in digital,
15. even in terms of transaction and transparency?
16. Why can our fellow friends in the FinTech market
17. such as TNG or Tap & Go
18. offer instant overseas remittance at very low costs,
19. but many traditional banks cannot?
20. Account and mortgage opening at least 4 to 8 weeks
21. if not even able to complete the entire process
22. not to mention it is hugely paper-based
23. for majority of banks in Hong Kong,
24. if not even the region,
25. of course, one thing on emerging customers as well
26. in the way they interface with the buyers,
27. can they rely on bank to offer
28. an omni-channel experience,
29. or they need to have many devices
30. with different turnaround times and agreements?
31. For customer information retrieval,
32. why does bank data need to be retrieved from
33. internet banking but not embedded into daily apps?
34. These exactly are many legacy issues
35. that I can make one simple conclusion:
36. We need to offer
37. a brand new digital experience to our customers.
38. Change management is hard
39. and transformation comes with
40. both by time, disruption and experience.
41. And bank in a Hong kong example,
42. by collaborating with HKMA, HKICL,
43. fellow banking industry, SVFs and corporate customers,
44. we are trying to incorporate Faster Payments
45. and various SVF payments into our daily lives
46. in different progress.
47. The same for account opening,
48. there are many elements over here,
49. one is CDD (Client Due Diligence) and KYC (Know Your Customer) process
50. and the other is internal setup within banks ourselves.
51. For the former,
52. I truly do not see how this can change much over time.
53. So let’s talk about the latter,
54. this can be improved
55. by a fully automated and digitalised process
56. that’s within the bank’s back end,
57. instant data interchange of credit bureaus,
58. collaborating with RegTechs,
59. and of course with support from the government
60. in creating a digital, retail and corporate identity record.
61. The greatest difference across virtual banks
62. versus traditional banks is that
63. many VBs claim they can provide
64. a better customer journey
65. and customer experience to our customers.
66. My question again is: Why can’t traditional banks do so?
67. In 2025, I believe for banks to succeed,
68. they cannot exist alone.
69. They cannot offer lending standalone
70. offers standalone internet banking platforms,
71. and of course maintaining competitive for customers
72. to transact or even to sell insurance,
73. banks need to stay connected, like our customers’ life
74. for example, in DBS’ ambition of “Live More Bank Less”,
75. having invisible banking,
76. or providing banking service in an ecosystem
77. or together with partners in the world or in Hong Kong,
78. I believe this is the key for future.
79. I believe this is the new era
80. where banking service can be invisible,
81. in behind of daily lives or business services,
82. without going to detail into the process,
83. there are few ways traditional banks can actually help
84. to be a FinTech ourselves
85. and participate in these ecosystems build up
86. by participating in partners’ platforms
87. so that we can engage with the customers
88. across partners’ customers journeys,
89. or by creating platforms alone
90. that connects third parties’ platforms together
91. and of course creating an ecosystem
92. of course limited by the bank’s size and strength.
93. This is a dilemma over here:
94. I believe banks need to be
95. as inclusive into our customers daily lives if possible,
96. on the other hand, I do not believe a bank
97. can never and will never be able to create interfaces
98. that covers all segments,
99. it must be through ecosystem partnership,
100. it must be through enabling with FinTech partners,
101. it must be through collaboration
102. with many other financial institutions
103. in an automated manner
104. embracing collaboration over competition.
105. So thank you ladies and gentlemen,
106. I hope by sharing right now
107. of how a bank can actually work as a FinTech
108. and also collaborate with other FinTechs
109. can drive more change and momentum
110. in a market for Hong Kong and for Asia
111. to be more digital and more innovative.