“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

Dan Davies
Apr 3, 2015 · 9 min read

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

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

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

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

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’

Viability rating — (2/5)

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

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

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.

Bull Market

A collection of finance and business writing by…

Bull Market

A collection of finance and business writing by @alexisgoldstein, @delong, @dsquareddigest, @DuncanWeldon, @felixsalmon, @jamesykwak, @Mark__Buchanan, @WhelanKarl

Dan Davies

Written by

Senior Research Advisor, Frontline Analysts

Bull Market

A collection of finance and business writing by @alexisgoldstein, @delong, @dsquareddigest, @DuncanWeldon, @felixsalmon, @jamesykwak, @Mark__Buchanan, @WhelanKarl

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