Fintech Thesis

According to McKinsey, 60% of banks globally have an ROE below their cost of capital and even in developed markets, which have seen ROE increase from 6.8% to 8.9% post GFC, they are not in a healthy position as we come to the end of the economic cycle.

To compound this bleak picture, not a day goes by without the mention of another fintech that is disrupting the most profitable parts of banks businesses e.g. retail deposits, payments, wealth management and consumer finance.

Banks need to look for opportunities to increase revenue and reduce costs fast. Fortunately, there are some fintechs out there providing solutions to these problems and helping incumbents transform into 21st century banks.

The first theme that banks need to address is their legacy infrastructure. Legacy infrastructure is a problem because;

• Costly to maintain, let alone upgrade
• Fragmentation reduces deep customer insights and personalisation opportunities
• Makes banks slow to bring new products and services to market
• Difficult for third parties to connect to directly

Thought Machine is a fintech startup launched in 2014 that has created a cloud native core banking system to address these issues using open source technology. UK bank Lloyds, has a 10% stake and it is backed by Playfair Capital and Backed VC. The founder has had two successful prior exits and has staffed the company with former Google engineers for a rockstart team! They are focused on the UK at the moment but similar issues exist in the USA that could be a great opportunity for them. One risk to their business is the long contracts that existing core banking providers such as Jack Henry and Temenos have with customers, often 10+ years, but over time these can be phased out once banks realise the need for modernisation with the support of the Bank of England.

Another group of interesting companies in infrastructure space are the API providers such as Tink, Yapily, TrueLayer, Plaid and Bud. These companies provide platforms and API layers to enable new fintech companies to connect with banks. For example, if you use a personal financial management (PFM) app and you connect your different bank accounts, that will probably be done by one of these companies. This is one of the most interesting spaces in fintech as they are essentially the plumbing of the future for financial services and are well placed to benefit from the explosion of all fintech going forward.

In this space, I like Bud the most because it offers a complete platform to connect with, including both data aggregation and also data enrichment. Furthermore, they also offer a marketplace for banks to distribute third party products and for Fintechs to leverage the scale of the banks userbase at a reduced cost. Bud counts HSBC, ANZ, GS, Nutmeg, Azimo and PensionBee as customers and has raised its Series A.

Big data. AI. ML. All of these buzzwords are used pervasively across many industries but less so in finance until recently, which is the second theme of how banks will move into 21st century. All of these tools have the ability to reduce KYC, regulatory and compliance costs for banks by automating manual jobs and focusing on being proactive not reactive. However these tools also have the ability to drive revenues. Banks have some of the most intimate data on its customers but it has been under utilised to date. These tools can provide deep customer insights and cross selling opportunities for banks financial products, but only if banks core infrastructure fragmentation issues are solved. McKinsey estimated the value of AI in banking to be 2.5%-5.2% of revenues, equating to $200bn-$300bn annually, a HUGE opportunity!

A startup in this space that I like is Artudata which takes a multilayered approach to enriching a banks data with third party data to combine with AI to provide customer insights to make accurate predictions that increase conversion rates for customers. CEO Tal Zohar has experience at IG Index and London Stock Exchange as well as being an Oxford graduate student. They have backing from some big names such as Intel, Amazon and Alphabet and has already signed up customers Kabbee, LiveCoach and a retail financial services firm.

Another use for AI and ML within financial services is for automation of some tasks that customers find it difficult to do, such as saving, investing and managing debt. Plum is one such startup which currently focuses on being a digital personal savings assistant. When you sign up and connect your bank account, it uses its AI algorithm to understand your financial life and automatically stashes small amounts of money away on your behalf, either to save or to invest. The company has integrated with Facebook messenger for enhanced customer chat functionality. Whilst I like their product offering, the future for the automation of financial products is huge.

Imagine a world where once we are paid, we could automatically pay off the most costly debt (Tally is also working on this), automatically save or invest expected disposable income based on our set goals and to switch or negotiate deals on utilities, phone contracts and other subscriptions. This is what I believe is Fintech 2.0, where we have to manage our financial situation less because it is automated. Exciting times!!