“Silicon Roundabout” — Old Street near the City of London. A lot of fintech startups are based here

A Cynic’s Guide To Fintech

Several business models that are bound to fail — and a few that might have a chance

A pal working in and around the VC industry asked me the other week what I thought about financial technology, or as the unlovely abbreviation has it, “fintech”. Here are my edited thoughts, from the point of view of someone who spent many years as a banks and diversified financials analyst, and who has some fairly strong prejudices about what works and what doesn’t work in financial services industry. In my view, the portmanteau term “fintech” groups together a number of different business models; I haven’t included “something something Bitcoin” in the list because that’s a slightly different debate. Here’s my partial list …

Fintech business model #1. Reinventing past mistakes of the banking industry because you don’t know about adverse selection

There are a lot of people out there who have expertise in data science, and who think that the incumbents in the industry don’t have sophisticated risk-based pricing because their technological skills aren’t up to the task of identifying risks. These people tend to think that they can go into the credit cards business, or the payday lending business or even the car insurance business, and pick up market share from the dumb old banks by using algorithms! and social media data! and so on.

This is not true. It is true that banking IT is generally terrible, but actually, if you look into the digital archives of any large incumbent player, you will tend to find an extremely sophisticated, cutting-edge algorithmic risk pricing system which was thrown away a couple of years ago because it worked great in testing and then fell apart really badly in the real world.

There are two reasons why fine-grained risk based pricing has been such a catalogue of failure. First, banks almost never lose money on bad risks. They lose money on good risks, which go bad. The nature of algorithm-driven pricing is that you are searching out profitable niches, Moneyball style, in the form of customers which have some set of characteristics in common which marks them out as statistically better than the average. Unfortunately, this tends to mean that you get a book of business which has loads of little concentrations in them — you’ve got all the mixed-race dentists in Yorkshire, or something. And this, in turn, means that when the world changes, your risks tend to be very correlated and you lose years’ worth of profit in one lump.

And the second is that the customers get to make decisions too. Unless your system is perfect, it’s going to make mistakes. And the kind of mistake it’s going to make is the kind which ends up with you hanging out an extremely attractive pricing offer, and attracting customers who have the particular set of characteristics that your algorithms have identified. But the people who respond to your offer are never exactly the same as the people that you modelled. In particular, the market share you gain tends to come from people who have all the characteristics that your algorithm liked, plus one more — the property of being more than usually price-sensitive. And it turns out that price-sensitive customers are often significantly worse risks; there’s often a reason why someone’s so keen on getting the cheapest deal, and it’s usually a reason that isn’t in the database you bought.

I’m not saying it’s impossible, but it’s been tried a lot of times, by very clever people, and it’s worked precisely once — Direct Line car insurance, and they were attacking a much less competitive industry than anything that exists today. The safe way to do financial services is to keep the segmentation down to a minimum and let the mathematics of risk pooling look after you.

Viability rating — (2/5)

Fintech business model #2. Thinking that a great big lump of transactions data is more valuable than it is

The real evangelists of Big Data thinking in the fintech industry seem to think that providing the actual financial services is a tiresome encumbrance, a loss leader that you have to provide in order to get access to the true mother lode of value — a load of Big Data. This is, to be frank, incomprehensible. Transactions data just isn’t that valuable, and in order to get lots of it, you need to have a very big operation indeed.

Look at it this way — the single most developed transaction data analytics business in the world is Dunnhumby. They have more than a decade of experience, and they work with the Tesco Clubcard dataset, which accounts for a material proportion of all the supermarket transactions in the UK over the last ten years. And they have managed to segment Tesco’s customer base into a grand total of … eight economically meaningful groupings. Along with that, they have come up with insights like “people who buy carrots also often buy cucumbers”. Dunnhumby is currently being shopped around for sale at a valuation of about £2bn, and this is most likely the biggest and best such company that has ever existed. Which is not to say that it’s not valuable — the thing is worth a couple of billion dollars, after all — but it’s clearly incremental to Tesco rather than transformational. It’s also pretty clear that things like this make sense as potentially helpful adjuncts to a profitable main business, not as goals in themselves.

Also in this category are people who believe that a combination of Twitter’s Decahose feed and a neural net algorithm are going to make them billions on the stock market, but I don’t think we need to lose too much time on that.

Viability rating — (1/5).

Fintech business model #3. Hoping that a load of people who actively mistrust each other will trust you instead

This business model is very common in the wholesale markets version of fintech. Often put together by a former star IT guy at a major investment bank, often by someone who got passed over for the COO job because his understanding of the business didn’t match his technical ability. And it usually involves the creation of a “platform” which will bring together a fragmented market, automate the process of collecting dealer quotes, and generally make forex, derivatives, bond trading or whatever look more like a stock exchange. It’s aimed at disrupting the “middlemen”.

I wrote a whole chapter in me and @TessRead’s book about what service it is which the middlemen provide. If you don’t want to buy the book, I’ll explain it succintly here — the service that interdealer brokers provide to their clients is simply that of being middlemen — so that parties who really badly don’t trust each other don’t have to deal with each other directly. And if they don’t trust each other, then they are really very unlikely to just hand over their position and order data to a fintech startup.

This isn’t a totally unviable business model. Trading facilities do get set up, and they sometimes do take off — BATS being the most obvious example. But if you look at the success stories, there is always a lot more “fin” and a lot less “tech” to their way of going about things. Getting a trading platform set up is always a delicate and hugely political business of reassuring all the parties that they are not going to get ripped off either by each other or by you. Just having cool technology is never enough — it’s always about building the trust and relationships. And if you are able to do that, you’re going to make money whether or not you’ve got good technology.

Viability rating — (3/5)

Fintech business model #4. Trying to use someone else’s network and only pay the marginal cost of doing so

On the face of it, this ought to look like a non-starter. All the big and important financial networks are owned by the incumbents. You would think that this would mean that startups would be hard pressed to get access to them at all, let alone to do so without paying their share of the overhead. This would make sense, but in many cases it would be wrong.

For starters, regulators are currently very keen on encouraging competition and entry in financial services markets. For another, wherever you find competing networks in financial services, you will find somebody whose bonus is only dependent on traffic and market share, and who doesn’t really care about economic viability of the business that he or she is winning. And finally, don’t underestimate simple inertia, incompetence and general failure to get one’s act together, which are often the most powerful competitive forces in financial services.

So there are actually a surprising number of viable business models which involve undercutting the incumbents for payment services. And although any business which is, at base, dependent on the industry not getting its act together is vulnerable to the risk that one day, the industry will get its act together, this can often involve an acquisition.

Viability rating — (4/5)

Fintech business model #5. Assuming that the regulators will be more inclined to listen to your whining than to the incumbents’

Usually a bad idea in financial services. Regulators basically don’t like small financial services companies. There are severe diseconomies of small scale in supervising them, they are more prone to blowing up and they don’t do very much for your career. And financial services is an intrinsically regulated industry where consumer protection is often very rigorous for a good reason. So the whole Uber idea of just blatantly breaking the law and then sending out a press release about how uncool and obstructive everyone is being is not going to go down well. Several fintech startups have already found out that there is no exemption for tech companies from the money-laundering or consumer finance laws, and that regulators usually don’t care if they’ve driven someone they regard as a rule-breaker out of business. The existence of financial regulations also tends to mean that fintech companies need to have a lot more capital lying around than they would if they didn’t need a financial services licence.

Viability rating — (2/5)

Fintech business model #6. Giving customers a worse service for a lower price

The only fintech business model I would regard as a proven success story. Giving a worse service for a lower price is what made the discount brokerage industry. What’s going on here is that banks love to bundle services and charge a premium price for the bundle, on the assumption that lots of customers will thereby pay for a load of expensive services that they don’t really need. Attacking this bundling has often been a good source of competitive advantage. As far as I can see, something like this is at the heart of business models like Transferwise — most retail clients really don’t need immediacy for their foreign exchange transactions.

Viability rating — (5/5)

Fintech business model #7. Getting your act together with respect to an industry standard where the industry has conspicuously failed to do so

In principle, it should be impossible to seriously compete against the banks in international monetary transmission. They all ought to have good networks of correspondent banks, to be able to handle their nostro, vostro and loro accounting and so to be able to convert foreign exchange and send payments via extremely cheap central bank systems. In fact, the correspondent networks are often lousy, meaning that payments have to take dozens of extra unnecessary steps, and the accounting systems are reconciled too slowly. Even the small number of banks that know what they are doing don’t feel like they’re in a competitive industry, so they don’t act that way. And this is only one of a number of areas — Apple Pay ought to have been a huge wakeup call to the banks not because it was a brand new way of making payments, but because it was basically the only fully satisfactory implementation of an existing industry standard. Again, there is a certain degree of long term business risk inherent in building your company around the inability of the banking industry to get its act together, but there are lots of very vulnerable areas here too.

Viability rating — (5/5)

These seven business models are the ones which stood out to me in a quick survey of the fintech industry — I’m sure there are others. I’m also fully aware that I’m being more than a little bit unfair in some areas, for the sake of making a point. But I don’t think I’ve been wholly unfair to any of them, and the broader point is quite important. “Fintech” is apparently a big priority policy area for the UK government’s industrial policy, and seems to have attracted a whole load of fairly uncritical support. Actually, a lot of these businesses are based on repeating old mistakes, and the ones which aren’t seem to be based on solving problems that should never have existed if the world had a fully functional banking industry.