We are building the next generation financial application aimed at millennials, promoting financial inclusion – built on blockchain powered by AI all available through state of the art APIs. Everyone has heard this pitch from at least one fintech. How should banks and investors look beyond the hype to distinguish substantial companies from empty promises?
The obvious place to start is the value proposition. Is the company aiming to solve an actual problem, or is it a solution looking for a problem. No matter how much cutting-edge technology that is under the hood, it is useless unless there exists a tangible customer problem.
What is the business model? Even if there is a problem to be solved, how is the company planning to earn money? Disruptive innovation often means attacking the incumbent industry’s profit margins. How sustainable is the proposed business model? Are you merely drawing first blood in a downward spiral where margins move closer to zero for every day? For many aiming directly at consumers, it is all about building a user base first and monetizing later. Is there a plan that states when and how you will be able to monetize the user base. What is the customer acquisition cost, and are there any wildcards that may mess up the assumptions in your business case?
Further on, is the business case based on assumption beyond the company’s control? This is seen by some fintechs that have placed a bet on establishing a position pre-PSD2 and then challenging the incumbent banks head-on. For every day the regulatory technical standards are delayed, the distance towards the company’s final form is prolonged.
How many customers are required to gain the necessary scale to be profitable? Many challenger banks are competing for the attention of the same target audience by offering an app-only everyday bank with an accompanying credit card. While this may offer convenience to the customers, Monzo reported that its prepaid card scheme loses around £50 per active customer per year, and other digital banks face similar challenges.
The key question is how the company is going to make money. Is it a B2C play, or a B2B-play? For the B2C-companies out there, will the company own their own balance sheet or base the business case on transactional revenues? Is it even possible to create a scalable revenue stream without relying on net interest income? For fintechs positioning themselves B2B it is easier to identify potential business models, as these will be similar to traditional banking software vendors.
Another area to investigate is the use of the underlying technology. The reason behind the success for several fintechs is clever use of technology to solve a customer problem. Neither blockchain nor AI as a magic wand that makes all the inherent problems of the financial industry go away.
For companies claiming to base their platform on blockchain or distributed ledger technology, it is useful to assess whether this is even necessary. There are many use cases for blockchain that is just as easily solved with a traditional database. One relevant questions to ask is if there is a need to establish trust between multiple stakeholders.
AI is no single discipline, but a collective term describing a wide array of disciplines that may prove to be useful. The most common area in fintech and banking is machine learning, e.g. having a computer program learn from examples rather than explicitly telling the program what to do. This is useful in any context where it is required to process a large amount of data to look for patterns such as Anti Money Laundering (AML), quantitative analysis or analyzing customer behavior. Natural Language Processing (NLP) is the backbone for the development of chatbots, and image recognition is useful for cybersecurity and Know Your Customer (KYC).
Access to relevant data is another area that is crucial for most companies. Even though the banking industry is set on open banking, there is no such thing as a free lunch. PSD2 is delayed and staying compliant with GDPR, reducing operational risk and securing customer data will always win over opening up APIs to third parties.
Does the team have the necessary experience that is required to build and run a fintech company? I have previously argued that being an entrepreneur is hard, but being a fintech entrepreneur is a whole new level of self-inflicted pain. The team should have the necessary skills in both finance, commercial, technology, and compliance. Even though one might be able to think out of the box by having a team with little to no experience from financial services, the financial industry is in many cases boxed in by compliance.
Is the company sufficiently aware of the cost of doing business from a compliance perspective? Financial regulations are constantly evolving, and it is easy to underestimate the cost of doing business in the long run. No matter how troublesome compliance may seem, as long as a company is handling other peoples finances, financial regulations are here for a reason.
For potential investors, fintech valuations are often cumbersome. Market trends show that deal volume has declined some, but remain at a relatively high plateau in terms of number of deals. Late stage valuations have experienced a drop and remain low as the sector matures. Despite this, early stage (early venture, seed and angel investments) valuations are steadily increasing. For potential investors, there are a couple of obvious pitfalls to avoid. What are the value object(s) of the company at hand and how sound are the assumptions that make up the business case? If either of these are unclear, it is better to stay away and place your investment elsewhere.
At the end of the day, a simple checklist-based approach may be the most useful:
If there is a good answer to all these, then you may move further in your dialogue, either as a customer or investor.