New Technologies, New Crises: Chat with Prof Douglas Arner
Yeah. You know, it's really very exciting. We spent it's probably been about between two and three years that we've been talking about an Arabic version. And the thing about these translations is that because of the volume of content in the course and if you will, the technical nature of it, it's not just anybody who can do the translations so you need a fairly sophisticated partner. We've been very lucky in this case to have FinTech Saudi who has been doing the translation work.
But it's a slow process. And I think add in the fact of COVID over the past two, several years, that's made it even slower but yeah, I think we're really excited about this. So from my standpoint, hugely excited.
This is, you know, a region where a lot is developing very fast. I think we have if you're looking at more broadly, we're looking at around 400, 450 million Arabic native speakers across the region. And this if you look in terms of spoken languages, Arabic is one of the top five spoken languages. So the opportunity in getting an Arabic translation to go with the English Chinese and actually Russian versions is a huge opportunity to reach out to an audience that has not been well-served with this before.
And as you say, it will be the first online fintech course. Personally, it's really exciting because I've been working with the region for an extended period of time. And, you know, going back to I even I in secondary school, I used to attend a summer program at Duke University and one of the first courses I took in that program, I was actually in Arabic. And so this has been something that I've been doing for a long time. If you think about some of the global finance work and petrodollar recycling crises, these sorts of things, a lot of time on Islamic finance.
And really over the past five, six years, I've been a member of the Arab Monetary Fund's FinTech Working Group. So you've got a really exciting region. You've got a region that I personally have been working at for a long time.
And so it's really exciting personally. But really the third piece is from the standpoint of this course, you know, it's been about five years now since we launched introduction of FinTech. And if you think about this, when we started there was almost nothing going on in Hong Kong in the fintech context. 2016, 2017, yeah. And so initially this was a discussion between Janos Barbaris, who was doing a PhD with me had just started Huy Nguyen Trieu, who was based in London at the time, hadn't even started CFTE yet.
And we had this idea that, you know, there was this huge take off in online learning. This was pre COVID and so we were focusing on, on massive open online courses, thinking about edX and thinking about how we might be able to do what would be the first massive open online course in FinTech. And eventually we did the region's first course. And what is today, as you say, the most popular online fintech course on the EdX platform. But you know, from that initial starting point to where we are today, I think what we've seen in the context of take up impact enthusiasm about this course has broken all of our hopes and expectations. So I think it's been a really exciting period.
And from the standpoint of today's launch, I think it's a really nice culmination of a lot of work across a lot of people over a lot of years. Yeah, I think that's a tremendous question and it's something that, you know, when we were designing the course initially and you know, when we were putting it together and it was mainly across 2018, 2019, so pre-COVID that we built most of the course, one of our central objectives, one of the central sort of principles in the design of the course was this idea that we wanted it to be as timeless as possible. In other words, we made an effort not to focus in on very highly specific numbers from a specific date or single events that were happening at the time we were filming. Instead we were trying to present a bigger picture background, evolutionary context for learners to understand this big picture integration between finance, technology and regulation.
And it's something that if I think about our original idea, our original idea was that we really wanted a course that could explain to people from a finance background how tech was changing finance and we wanted a course that could explain to people from a tech background how finance worked. And so that regardless of whatever your background was, whether you were a deputy central bank governor or you were a high school student, we wanted the course to basically give you a big picture understanding of the long term trends that we've seen in finance, technology and regulation. And I think that the continuing attraction of the course highlights the it worked pretty well. But the other thing that we tried to do is having built up this community of learners, you know, there's a lot of value in this community. And so we have a continual process of engaging with that community.
In particular discussions like this videos which will go out to all of the learners. But we also do every single month a sort of update on current issues, what is called looking back looking forward. But even in those monthly videos which go to all of the learners we're not trying to focus too much on current events, but we're trying to look at the bigger picture context. And I think from the standpoint of the relevance of the course as well as continual engagement with the community of learners all across the world, that it's that combination of your original design, the fact that we had some really good people involved in the first of the course and this effort over the past several years to continually update with analysis of big trends. I think that has been one of our biggest contributions yeah. You know, I think there's a big question here, which is, you know, we look at all of these crises we look at the crypto winter over the past year, almost year and a half, and, you know, questions about, you know, positive versus negative impact of digital finance.
And something that I think is really important to realize is some of the lessons that we've seen over the past decade with digital finance. And, you know, if we think about it, over the five years of Introduction to Fintech yeah, we've had 120,000 plus learners all over the world, which is hugely exciting. But at the same time, over that same period, literally hundreds of millions of people have gotten access to financial services for the first time, and that has been very heavily focused in developing countries, particularly in China, in Southeast Asia and in India. And I think that this transformation that we've seen in China, in Southeast Asia, in India, in Brazil and a range of others, as a result of digital finance, that this is tremendously important.
It has had huge impacts on the lives of individual people, not least in the context of being able to receive funds in the context of COVID based lockdowns or other sorts of disaster responses. But it's also had huge impact on personal empowerment for people all over the world, as well as on economic opportunities and innovation. So the first point that I really want to highlight is I think this story about the big impact of digital finance is one that we shouldn't lose track of. But with that said, you know, I've spent the past 25 years looking really at the intersection of finance, of technology, of broader development.
And I think the key lesson that we've learned out of this is that finance and innovation can have a tremendously positive impact on development. Exactly. But at the same time, finance suffers not just from these ideas of what we think of as positive externalities, but also negative externalities. And this is a point about financial crises, and it's something that if we think about finance, financial crises are not something that is unexpected.
One should view financial crises as an inherent feature of a market based financial system. They just happen about every ten years or so, and we're due for one now. It happens to be that there is also often a relationship between innovation and financial crisis. It's often more like a sort of Gartner hype cycle, in other words, that you get people are overly excited about something, drive up huge increases in prices, which typically are then fed by a variety of lending and leverage or something, then triggers a drop and you then see a collapse of that. But just because you have these sorts of bubbles cycles doesn't mean the innovation isn't actually significant. If we think about the Internet in 2001 Dotcom bubble-related sort of crash, but the internet was still huge.
We think about 1720 and the South Sea bubble huge run up in the bubble huge crash. But the joint stock company this was huge. And so similarly if we're thinking about digital finance today, there's certainly been a big hype cycle and we're now seeing the fallout of some of that. The question really is how do we go about one maximizing the benefits while, two, minimizing the costs? And that is really where regulation comes in. In other words, we have to realize that crises are going to happen and we build regulatory systems because we know that they do happen.
And one of the classic elements in a regulatory system is the idea of one requirements from the standpoint of risk management, of capitalization, which are designed to reduce the likelihood of financial institutions failing. A second piece is often around systems to provide liquid acidity to markets when markets stop functioning on a normal basis. And the third is systems for resolving financial institution failures when they actually happen.
And if we look at 2008, one of the problems with 2008 is that none of these systems really worked very well. We had lots of financial institutions which had structured themselves in a way to reduce their regulatory requirements. So when the crisis hit they were not very strong in its wake. Second, we had a very limited view of liquidity provision, which meant that generally speaking central banks and other liquidity providers didn't provide liquidity at an early stage and in the context of complex financial institutions we lacked resolution systems. Now if we look at today, we spent a lot of time building these systems, and that's good news. But just because you have regulatory systems doesn't mean that crises don't happen.
And I think what we're seeing right now is a really interesting one because you have both the combination of the hype cycle, but it's really combined with something else, and that is in particular reactions to inflation by major central banks. And a lot of our challenges are that we've seen a very quick run up in interest rates, which are then impacting a lot of positions which were built in a different environment. And the more interest rates go up, the more we're likely to see these sorts of problems emerge. And that is really not only a challenge right now, but it's also a big challenge as we go forward from the standpoint of innovation and development. So I think let's take that from a couple of different angles.
The first is I think the extreme example of this is is really the crypto context where if you think about the original Bitcoin whitepaper, the idea here was to prevent to present a technologically based alternative to the failures of traditional finance and so the idea presented by the crypto ecosystem, by decentralized finance, was this sort of idea that we could design a technological basis which would address or prevent the sorts of market failures and externalities which have always characterized traditional finance and which have resulted over a period of hundreds of years in the evolutionary development and of our modern financial regulatory systems. Now, what I think is interesting is that over the past and it's been almost 15 years now, and it's often suggested that crypto is a new market, that blockchain is a new technology, but 15 years it's no longer so new. But what we've seen over that 15 year period is something that that my coauthors and I call the financialization of crypto. In other words, we've seen that first many participants in the crypto ecosystem have developed approaches which are designed to provide similar sorts of products, services, functions to traditional finance, albeit in a different environment. And at the same time, exactly what we've seen is the emergence of exactly the same regulatory failures and negative externalities that we've seen in the context of traditional finance. Exactly.
And so I think if we take this sort of extreme view, that technology can address all of those problems, maybe it could if you remove the humans from the system. But I think once you have that element of human behavior, it changes everything. Now, with that said, if we look at the recent failures, I mean, one aspect in the context of, say, the crypto winter failures was we didn't have a clear picture of the interdependencies, the inter-connections, the concentrations of risk that had emerged in the crypto ecosystem. And so we didn't necessarily understand that a problem in one part, say a Stablecoin collapse could then trigger losses via an investment fund that could then trigger the failure of a large intermediary, which would then have knock on effects throughout the ecosystem had we had better systems for monitoring these interconnections, we would have been in a better position to identify those risks before they arose.
Now, the irony here is that a blockchain-based environment is supposed to make that easier but in some ways the problem had been the centralization of a variety of transactions into individual intermediaries and systems, which meant that it wasn't possible. Now, that's one piece. The second piece is if we think about from the standpoint of the initial banks that have had problems. So Silvergate has really been this sort of initial trigger, and that's where you see this linkage to the crypto ecosystem. Silvergate had lots of crypto customers for a variety of reasons.
All of those customers began reducing their deposits at the same time. Silvergate, as with any bank, is in the business of basically borrowing short from its depositors and lending long from the standpoint of its loans and investors. So banks face this natural miss match between their assets on one side, their loans and investments and their depositors, their liabilities on the other, and we have, in addition to prudent business behavior, we have capital standards, leverage requirements, liquidity limits, lender of last resort systems, which are all designed to try to balance some of the inherent instabilities. Now, if we look at Silvergate perhaps the biggest issue was we didn't identify the potential risks in having a concentrated depositor base In other words, if all of your depositors have the same sort of business and suddenly they all have the same sort of business problem, they can then all need their money back at the same time, which can then cause liquidity problems in the bank.
And similarly, if we think about Silicon Valley Bank or we think about Signature Bank, they have had similar concentrated customer bases. If we look at Silicon Valley Bank, its customer base was largely tech companies - tech companies, which once again, all had sort of similar influences from the standpoint of their businesses, if you will, a tech downturn resulting in losses, which was resulting in a rundown of balances, but also in the same way that you have with the crypto community, very high levels of communications amongst participants. So once one triggers some sort of loss of confidence in the bank, they can all remove their deposits very quickly, which then highlights some of the other underlying problems. And we look at signature, it's kind of a mix of the two, a mix of crypto and tech customers. Now in each of these cases, you had both this sort of concentrated customer base often with businesses as opposed to individual retail accounts, which has its own dynamic.
And second, in each case, you often had losses, but they were usually unrealized losses in the context of their various investments, which were usually related to interest rate changes. In other words, at the bottom of the cycle they had invested in long dated bonds, which as a result of rapid interest rate increases were suffering large losses, which so long as they didn't need to sell those assets, they didn't have real losses on. But once they had an actual demand for funds and they had to sell those assets, suddenly they were facing large losses. And that results in insolvency and failure So I think in some ways, if we look at the key lessons of, say, these three banks it's really about a need to better look at the depositor base and to have a more dynamic analysis of smaller banks of their assets and liability framework. And it's interesting because since 2008 we've done a lot of this with big institutions with the systemically important financial institutions, but frequently we've given exceptions to smaller banks.
And in each of these cases, the banks were not tiny, but they were just under the regulatory thresholds which would have brought higher regulatory requirements. So could tech have solve these problems? Yeah, probably if they had a better system of basically monitoring on an ongoing basis the real time asset and liability position of some of these medium sized banks Exactly. And I think the final point and what's interesting is the one that doesn't match these and that's the big one. Credit Suisse. Credit Suisse is not like all of these others, their national favorite. It's not just their national favorite.
This is a globally systemically important financial institution, the failure of which would cause very significant problems. And, of course, from the standpoint of post-2008, all of our regulatory attention has been focused on preventing exactly what's happening now from happening And if we look at Credit Suisse, you know, one, it does very much reflect these sorts of human behavioral elements. It does very much reflect some of the interest rate changes.
But at the other end of the spectrum, if we look at Credit Suisse's problems, it's really been about a decade of progressive errors or problems that have emerged in the bank's management. And, you know, each time one of these has happened, there's been an effort to try to address the problem. But then something else has happened.
You know, they have a comprehensive restructuring plan, but it doesn't you know, there are questions about whether it makes sense. And so if one looks at Credit Suisse, one can almost say it looks like just poor management over about a decade and that's a problem. Does it seem to have serious sorts of asset problems like we saw with Silicon Valley Bank? Not really. Its asset quality looks okay.
Does it seem to have a sort of concentrated depositor base? Well, it does a bit because it's focused on wealth management but it's a pretty sticky depositor base. You are seeing some liquidity questions, but I think the biggest question with Credit Suisse is that markets and investors just don't see a positive future for its business model. And that's something that's quite different from the other ones. From the standpoint of technology, I think Credit Suisse is a very interesting story because about seven or eight years ago they started a major project to essentially do something that many have argued in the context of large banks is the way forward, and that is to integrate through digital systems, basically RegTech, their risk management systems, their regulatory capital systems and their compliance and IT systems. It sounded very good. But just as they were getting started, one of these periodic crises hit.
And so they never finished that. And then just as they were dealing with whatever that crisis was, something else hits and they get another change up and I think from the standpoint of the institution, they never manage to actually complete any of their strategies because each time they make a progress on something, something else happens and throws a wrench into the work and then they fire all the people who are doing whatever it is and not exactly build a new business. And so could Tech have solved Credit Suisse's problems? Maybe. But this looks a whole lot more like long term management problems. Even with the best technology and regulation, you can't solve that.
You know, I think that there is this argument about sort of ... you have this sort of moral hazard argument and it's usually focused on shareholders and management. And basically what we now see is a situation where in the context of Silicon Valley Bank, for instance, shareholders lose their money, management loses their jobs, bank keeps going. So that takes out your sort of two main constituents, I think with Credit Suisse, in some ways it's more that it's been such a big organization that no one has necessarily been able to grasp the complexities. And this is an idea that emerged in 2008 with Lehman Brothers and others the sort of not just too big to fail or too connected to fail or too big to save, but the idea of too complex to manage and this has become a serious problem in many financial institutions and I think Credit Suisse is an interesting case because they have tried periodically to implement better systems of management or risk management or understanding what is going on. But at each point there has been some division or some individual or some component that has been more or less behaving in isolation, which no one has necessarily understood what they were doing, until a problem hits.
And that I think in many ways it's more the complexity as opposed to any sort of necessary moral hazard from the standpoint that you are too big to fail. Yes and one in particular that is has been built as many of our large financial institutions are today as a result of a series of mergers and acquisitions over a long period of time which certainly pre-COVID most large financial institutions didn't have in place, comprehensive I.T systems. In other words, if we look at the most recent major regulatory action against Citibank, in 2000 and a $400 billion fine, the exit of its chief executive and mandating a multi-billion multi year internal systems and data governance rewiring.
You know part of the problem is that each time you did an acquisition it came with a new IT department, a new set of databases, a new set of systems, and no one ever managed to put everything together. Now we've had some huge progression as a result of some actions like the action against Citi we've had similar actions against UBS, Goldman Sachs, a range of others from the FCA, mandating the building of better systems. And probably actually the biggest motivator has been Covid. Over the past few years, the necessity of large financial institutions all over the world having management, compliance, trading desks, everyone working from home remotely has driven them at a very rapid rate towards implementation of cloud based systems, which has been a way to leapfrog the problems of those legacy balkanization across divisions. But I think in Credit Suisse's situation, the continual emergence of problems has meant that they've never been able to get a grasp on what's actually going on.
So could Tech save them? Yes, but maybe it's the humans that need to get their acts together first.