What to look for when investing in a fintech startup
By FF Newsroom · 19 March 2015
Our job at SBT Venture Capital is to invest in startups. To a novice, it sounds simple, until you realize there are thousands of startups, at various stages, and we need to narrow it down to a manageable list of teams that we can work with.
I wrote recently about our filtering process – the ‘why we don’t invest’ part of our thinking – yet, this post is about the characteristics of the startups we do invest in. But first a short note about unicorns.
Unicorns are a popular metaphor for those VC-backed investments that have extraordinary returns. Many argue that a VC should seek only unicorns – look for those 20x to 100x returns that make up for most of the financial success of a venture capital firm. There are at least two problems with this approach:
- No one really knows ahead of time which startup will be the ‘greatest ever’, and with a lot of people chasing the same deals ‘for fear of missing out’ reasons, valuations move into bubble territory and extraordinary returns suddenly don’t look so likely.
- At the other end of the spectrum are firms that invest at seed stage, hundreds of startups, and hope for the best.
Becoming a significant player
So, startup becomes a significant player in financial services, company value increases, everybody is happy. The key being becoming a significant player, and money will follow. For this, we need to either be told, or develop a narrative ourselves, on how that will happen. The immediate candidate would be startups that develop technologies that are aligned with what banks do today, aligned with their strategies, business and IT. Banking executives do read the same books by Brett King and Chris Skinner, Gartner emerging technology reports, and attend the same conferences about what’s new in financial services and fintech. Successful startups, in the immediate future, are the ones that are already aligned with banks, provide an immediate benefit to banks and can get a commercial contract pretty much now. A subclass that gets a lot of attention is fintech startups that compete with banks, sometimes called ‘disruptors’. We believe that those companies will be able to arbitrage the execution speed and clarity of vision between themselves and incumbent financial services institutions (for a while). There may be banks that don’t believe in fintech and technology innovation. There will be fewer tomorrow, and the incumbents, as a category, will adapt. You cannot build a business model predicated on disrupting an industry under the assumption that all executives in that industry are dumb and dumber. A more interesting class is fintech startups that develop new or complementary (to banks) products or services. Banks may not enter into a commercial relationship with such a startup (for now), which will need to go to customers directly, sell to retailers, and find ways to grow until it becomes obvious that it’s a good idea. It’s in this unproven/untested, strategically misaligned startup where we see a lot of potential for extraordinary returns for fintech venture capital. No one can predict the future, but a good, educated guess helps. It’s in this area where we also look for a significant ‘tech’ component of fintech, otherwise the ‘idea’ is quickly copied once it becomes clear that it works; think of all the Square clones worldwide (there are hundreds, if you were wondering). The next category is the dangerous one: the ‘visionary’, revolutionary, futuristic startup. Think bitcoin in 2014. We don’t ignore these companies, but we’re careful how much we invest in them; we like the idea to test new concepts in fail-fast mode, to learn ‘by doing’. We accept that such a company may not benefit an incumbent financial services institution for a while, but we stay close to those that show potential to change things dramatically. The ‘tech’ component needs to be even stronger, and aligned with the trends we see taking shape, such as mobile, cloud, social, software-defined-everything, automation, crypto, cyber security, big data, predictive learning, etc. To recap, the horizons we look at are:- now
- next two years
- next five years.