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FinTech: Observations of a Skeptic

FinTech: Observations of a Skeptic

The year is 1967. Everyone is talking about the Hollywood movie The Graduate, especially about this dialog:

Mr McGuire: Are you listening?

Benjamin: Yes, I am.

Mr McGuire: Plastics.

Benjamin: Exactly how do you mean?

Mr McGuire: There's a great future in plastics. Think about it. Will you think about it?

Fast forward 50 years to 2017. We now know, with the wisdom of hindsight, that plastics did not have a great future. But now everyone is talking about this dialog:

Mr Hype: Are you listening?

Utpal: Yes, I am.

Mr Hype: FinTech.

Utpal: Exactly how do you mean?

Mr Hype: There's a great future in FinTech. Think about it. Will you think about it?

I have been thinking a lot about FinTech. Why? Because I, a finance professor, am being told that if I do not adapt to this new technology, I will become a dinosaur. The fear of obsolescence is a great motivator. But to think about something, you first have to define it. What does FinTech mean? I asked the “experts”. That was useless, because it meant different things to different experts. So I consulted the report that the Steering Group on Financial Technologies set up by the Hong Kong Government in April 2015 produced. It said: “FinTech refers to the application of information and communication technology (‘ICT’) in the field of financial services, including such areas as digital payment and remittance, financial product investment and distribution platforms, peer-to-peer financing platforms, cybersecurity and data security technology, big data and data analytics, and distributed ledger application to new asset classes and processes.”

The question for me as a finance professor is whether there is more fin here or more tech. My answer for each of these areas:

1)      Digital payment and remittance: All tech, little fin. E-payments are not new. Credit cards came in 1946 (John Biggins, USA, 1946, “Charg-It”). Then came Paypal in 1998, but payments had to be guaranteed with credit cards. Then came mobile phone companies – Vodafone in Kenya in 2007 – where talk minutes became cash and could be transferred. Now with new technologies and smartphones, buyers and sellers are identified by matrix-like bar codes (called QR codes), and their bank accounts are automatically debited or credited when there is a transaction. Nowhere has this grown as fast as in China (WeChat or Alipay for example) and that is because the traditional banking system there has not served the customer very well. Some banking functions will disappear.

2)      Financial product investment: Mostly tech, little fin. Modern finance begins with Harry Markowitz in 1952. His model, and numerous advancements thereof, advise on how to invest to maximize our expected return given our risk. In the real world, however, there are numerous obstacles. First, the model requires a lot of data about the past performance of assets to estimate their future return and risk. Second, it requires this data in real time, and it does complex computations in real time. Third, and the most important and the most difficult, it requires us to be rational. Robo-advisers solve some of these problems. A set of complex algorithms are linked to real-time data inputs from the financial markets, inputs about demographics and preferences from the advisee, and, if the advisee so delegates, dynamic portfolio rebalancing by algorithmic trading done by the machine. Financial advisors and wealth management experts may disappear.

3)      Peer to peer financing platform/crowdfunding: Mostly tech, little fin. Humans have been borrowing and lending since humans began. The fundamental problem has always been trust: will the lender get the money back, hopefully with interest? This problem has been ameliorated with the rise of trusted intermediaries like banks. But banks have their own problems. Peer-to-peer financing is an attempt to remove the banks. Borrowers approach a platform with loan requests, information about themselves and the proposed use of the loan. Sometimes credit scores are provided. The platform decides on an interest rate, and puts the loan up for viewing. Lenders then decide how much to lend, if any. Some loans are subscribed to, some are not. There is a lot of default. But more important, and this is true in China where hundreds of these platforms mushroom every year, there is a lot of fraud. It is not so easy to get rid of banks. So again, some banking functions will disappear.

4)      Cybersecurity and data security: All tech, no fin. This field holds a lot of promise, but we finance professors have little to contribute here.

5)      Big data and data analytics: Mostly tech, little fin. The heart of investment finance, as I mentioned before, is how to maximize expected return given risk. The inputs in this model are predictions of future risk and return of various assets. If the inputs (predictions) are bad, the output will be bad. GIGO (garbage in, garbage out). So prediction is big business in finance. However, pattern detection and other models current data scientists use have yet to prove themselves definitively in finance. Financial analysts – professionals who predict the current and future health of companies – may disappear. Financial regulators will be able to detect more fraud.

6)      Distributed ledger application: Half and half. Though this technology is complex, the big ideas are simple. And the biggest idea is really big: we do not need trust any more. In the old days, if A buys from B, it shows up as a double entry in a private ledger. If there is a dispute, an intermediary is needed. In this new technology, transactions are encrypted and grouped into blocks, and blocks are chained to each other. Everyone can see it. The ledger becomes universal. Changing one data item changes the whole chain, and that can be observed, and so fraud is impossible. Anyone can join the network. They can compete to authenticate and create a new block, and the fastest person is rewarded. These persons are called miners. Miners are the new accountants. The disruptions caused by this new technology are huge: auditors will be displaced, sovereign fiat money may be displaced by private crypto-currencies and monetary policy will have to be rethought, intermediaries in supply chains will disappear and working capital may disappear, etc., etc.

7)      Smart contracts: Half and half. This technology was not mentioned, but this is where the finance excites me the most. For example, we would like to invent a contract where a firm takes a loan and promises to pay it off every six months, but is excused for a month if there is a typhoon. This is difficult to enforce today. When there is no typhoon, the firm may not pay, and recovery is painfully slow. If there is a typhoon, the typhoon is difficult to define. In a smart contract, typhoons are defined as wind speeds above 150kms per hour, and the contract is linked to the local weather station and the local electricity utility. If there is no typhoon and the firm does not pay, its electricity is automatically switched off. If there is a typhoon and the firm does not pay, its electricity is not switched off. Only better borrowers will sign such contracts. They will obtain lower interest rates, and the lenders will get a higher quality pool of borrowers. The insurance business model will change.

I am 58. I have lived through the plastics hype, the AI hype, the dot com boom hype, and I will live through the FinTech hype. No fewer than 485 US car companies began in the first decade of the 1900s; today only three remain, but they still employ many workers. Thousands of FinTech companies began in the first two decades of the 2000s; few will remain in about 10 years. The few who remain will change the lives of most of us for the better. Finance professors will not become dinosaurs; at least, not until greed and reason are removed from human nature. But finance professors will have to adapt because their students will not get the same jobs as before. Other business school professors will also have to adapt.

Opportunity and skepticism could be the two guiding principles. Take peer-to-peer financing, for example, in the case of finance professors who teach banking. New banking models can be taught on this platform with a critical eye on two old concepts – adverse selection and moral hazard. The new models should minimize lower quality borrowers, and they should minimize risk-taking after the borrowing. Take distributed ledger application, for example, in the case of accounting professors who teach auditing. Can they really allow an open source where all business secrets will be revealed? Take big data, for example, in the case of marketing professors who teach consumer marketing. Are the observed patterns a cause or an effect? Take blockchains, for example, in the case of operations research professors who teach supply chain management. The dark side of efficient interconnections is the increase in the probability of contagion. Management professors could invent new business models with smart contracts, and economics professors can rank order these models by their benefit-cost ratios.

I could go on and on. The skeptic in me believes that FinTech is just better plumbing for most business models. The opportunist in me believes that we can retool our business courses to reflect that and, in the few cases where the business model changes, introduce new courses. The marriage between technology and business has now entered a different phase. Management schools will have to teach how to manage that. They will become even more relevant.

Professor Utpal Bhattacharya, Department of Finance, HKUST Business School