For some readers of New Money, I know that some of the fintech specifics can be a little hard to follow, and so as a response to that I thought we should explore, in more general terms, simple answers to a complex question: what is fintech?
And we’ll do that by taking a trip down memory lane.
My interest in financial technology started over a decade ago and remained rather informal until 2015. At that time, as my curiosity began to expand, I realized I didn’t have a good mental model for fintech. So, as I started to learn about these new companies, I found myself thinking of a way to categorize them.
On my first attempt I took the easy path by breaking FinTech (as it is often stylized and stylized here for avoidance of doubt) in to its two most obvious components: the “fin” and the “tech.” Having had enough exposure to both at Credit Suisse along with some additional help on the “tech” side from my first year at MIT, I would occasionally draft a rudimentary market map that helped me clarify my thinking.
Here is a digital recreation (via GoogleSlides) of my notebook drawings from 2016, including companies that I was actually following at the time:
Looking back on it now, it is far from perfect. But it is also very helpful, even today, as a simple tool for understanding how fintech companies can actually use technology and maybe, even as a tool to understand where there might be opportunities for innovation. As an example, look at the open space at the intersection of “investing” and “digital.” In 2016, I didn’t know of any companies in that gap. Of course, there were many. Funny to think that four years ago, Robinhood wasn’t even on my radar.
These added layers of specificity also goes a long way in clarifying one of the hardest things about fintech: the term is extremely broad. As one of my favorite professors from MIT put in crisply for the FT, “Saying you are an expert on fintech is like saying you are an expert on the whole world.”
But with this map as a starting point, we can at start to identify some important subcategories and have an objective framework for critiquing some of the things that are missing. Today, we’ll look at six places on the map (identified in blue, above) and do a little of both:
My personal square one: B2B Solutions
Perhaps not the most ideal starting place for a fintech newbie (B2B fintech solutions aren’t always relatable), but for me, it signifies the start of my formal exposure to financial technology. In 2014, when Credit Suisse decided to get serious about “digital transformation” for its private bank, I sat through probably dozens of different company pitches to help our “platform strategy team” decide which companies to partner with to make that happen. It is safe to say during that time, I met with almost every company in the market that had the word “vest” in their name.
Because these companies are esoteric, we won’t go too deep here, but it suffices to say that they are dozens, if not hundreds of companies, out there who are in the primary business of selling software and automation services to big financial service firms. And because they are often SaaS companies, I would argue that, in a sense, they are the purest “tech” plays on the map.Which brings us to everyone’s favorite topic: Blockchain
Even back in 2016, as cryptomania was heating up, I wasn’t completely sold that blockchain was the latest and greatest thing to happen to the financial services industry. I had been intrigued with the idea behind Bitcoin ever since reading this Economist article in 2013 (stupidly, I didn’t buy any), but over the years I have generally considered blockchain technology to be a “hammer without a nail.” However, I stand by my belief that this technology "deserves its own swim lane” and that we may see some exciting products in areas like identification and governance (both corporate and political) form the basis for some big companies in the next decade.The big miss: Marketplace, Platform, Crowded Thinking
After going through some old notes and emails to build this “old” market map I realize now that the use of the word “aggregation” represents my most unclear thinking from that period. I definitely recognized that it was important, and it is, but it also requires more nuance for at least these three reasons:
First, aggregation is not, on its own, a technology.
Second, the businesses in that swimlane can probably be subdivided into two (or arguably three) subtypes: marketplaces & platforms (companies that bring buyers and sellers together in a single location, think NerdWallet) and aggregators (companies that bring existing products together for ease of use, think Mint or Paypal). It’s also worth noting that platforms and marketplaces, although similar in some regards, are different, and not necessarily mutually exclusive. Envestnet, for example, is a company with both platform and marketplace elements to their strategy. Over time I’ve been able to distill my thinking on how to re-categorize these types of firms specifically, but that is something we will explore at a later date.
Finally, I spent at least 5 minutes agonizing over the location of “aggregation” on the map. Something about putting it next to “blockchain” (often associated with “decentralization”) seemed wrong. They seem kind of opposite, don’t they? For now, I can live with the fact that aggregation and decentralization can live in harmony, but perhaps this is something we can also explore later.
Needless to say, there were some contradictions and shortfalls in my first go around, but hey, that’s why this is version 0.0.The digital debacle
As I mentioned above, I spent a big chunk of my early career scoping and implementing digital transformation at a large bank. At the time I didn’t have a clean way to describe “digitization.” Even today I sometimes find myself struggling. I’m sure there is a great HBR article or business book out there that summarizes it nicely, but at the time it probably would have been most appropriate to quote American Supreme Court Justice Potter Stewart, “I [knew] it when I [saw] it.”
Today, I think the two buckets on the map (“automation” and “digital / UX”) still pass muster. It can be more helpful to be specific for the business in question, but in general we can view them as ways to reduce costs vs. incumbent firms. For example, Betterment uses automation to reduce production costs (algorithms are a lot cheaper than portfolio managers) and pairs it with digital onboarding and marketing to reduce acquisition costs (via reduced friction). I made similar points when breaking down Lemonade’s recent IPO. So while these categories may also need some retooling in later versions, it is safe to say they’ve earned their place on the map.Confession time…
I don’t REALLY understand payments.
I understand interchange fees, card issuers, merchant acquirers, card networks, and ACH. I understood why Square was a big deal back in 2009 and why Stripe is a huge deal right now. I even went to Money20/20 last year.
But I also struggle to understand why JPMorgan’s deal with Marqueta is important or how PayPal has become bigger than some credit card networks. Things like that leave me feeling like my knowledge of the industry is inadequate.
I say “industry” here for payments to highlight one thing that I definitely recognized in 2016: payments is a huge deal. It is so big (quick Google search, TAM = $2T) that it’s offensive to compare it to “fintech” (quick Google search, TAM = ~$125B). And that TAM creates opportunities for companies to succeed, at massive scale, in a variety of different ways. Some of which I haven’t taken the time to study.So let’s talk about something I’ve studied plenty…
Microsoft Excel. And yes, I know Microsoft Excel isn’t a company, but it is so ubiquitous that it deserves a space on the map.
Some of you certainly know this, but in the spheres of corporate finance (think functions like: corporate development, investment banking, financial planning, treasury, etc.), there is some extremely important work that happens on Excel spreadsheets.
How important you ask? The famous ‘London Whale’ debacle, in which JPMorgan reported a $6B trading loss, was attributed, in part, to a copy & paste error!
On a more distributed basis, it is no secret that junior bankers spend countless hours (okay, 90-100 per week) at their computers tweaking and re-tweaking the precious models that senior bankers use to advise companies on billion dollar transactions.
This has always led me to wonder a simple question: why?
Don’t get me wrong, I love Excel. Like many others that do too, I’ve certainly been guilty of pushing the limits of its usefulness. But as a lover of technology, I’ve also struggled to understand why analysis of that importance can’t be formalized in a way that removes opportunities for such costly human error.
And over time that has led me to a very simple answer: it can. But not in a way that is immediately obvious with our first map.
Which concludes this analysis of v0.0.
Of course, no conversation that includes a slide deck would be complete with a comment on version control: any version of the map that includes both a “Fin” and “Tech” axis will be memorialized under v0 and will likely expand to include topics discussed both today and in the future.
And for any market maps that need different axes to help us better understand fintech, I’ll be sure to use a new “version,” for which we will have to go back to the drawing board.