Are you a homo economicus? Fintech and the human touch

Time to embrace behavioural economics

You are not logical. Neither am I. At least that is what proponents of behavioural economics say.

Behavioural economics is a relatively new concept in the banking world, but the theory is widely accepted to have been around since the late 18th century when Adam Smith published “The Theory of Moral Sentiments”.

In short, it is a mixture of psychology, decision science and economics, which attempts to make sense of the often seemingly irrational decisions we all make. This challenges the traditional “homo economicus”, or rational economic man theory that has dominated over the years, and which basically assumes that we make logical decisions, always choosing the best option. Behavioural economics asserts that this assumption ignores the human condition. Let’s look at some simple examples to illustrate the point.

It’s quite likely that at some time you have made a New Year’s resolution to get your finances in order, get fit or lose weight. Yet by early spring the gym has given away your locker, your exercise bike is now a clothes rack, your bank account remains emaciated, and your waistline is still ample. Normal service has been resumed. If we really were logical, rational beings we would all be much healthier, wealthier and svelte. And we make heuristic decisions every day – think gut feeling, common sense or rule-of-thumb – about our finances. We accept personal loans with an exorbitant APR and do not save nearly enough for a comfortable retirement despite having the benefits clearly spelled out to us.

So, an understanding of the human decision-making process would seem sensible for all businesses, banks included. It is estimated that we make at least 3,000 decisions per day, but our brains are not up to the task of making rational decisions all the time. Now, through behavioural economics, coupled with the power of data science and machine learning, it is possible to analyse huge data sets quickly and identify patterns, likely outcomes and the factors that may alter those outcomes. And together with the wider field of behavioural science are powerful tools that can provide relevant, timely insights and define appropriate incentives that are aligned with, and can influence human behaviour.

And that brings us to the world of banking and fintech. First, let us look briefly at the impact of data science. Providing the right product to the right person in the right way and at the right time is in fact one of the major challenges all banks face today, but in particular legacy banks. Fintechs have embraced the benefits offered by new technology and ways of thinking, especially in terms of efficiency and effectiveness. For instance, data science allows fintechs to build quicker and more precise credit risk decision processes than those used by legacy banks, which often are encumbered by clunky and outdated systems. Payments and purchasing habits of customers are also available with precise prediction models that can map out future behaviors and their causes. Data science allows fintech firms to deep dive into and ascertain the lifetime value of every customer, which enables them to focus finite resources on those customers most likely to be of the highest value over time.

And, looking at the practical aspect, fintechs have used technology to create robo-advisors tailored to the individual client and without the drawbacks and biases inherent in the human decision-making process. This allows asset allocation decisions to be made in line with client expectations. And as importantly, the use of such data is helping prevent and detect fraud by way of the ability to monitor transactions in real time and flag the anomalies. Put simply, data science is how fintech firms make decisions about everything from onboarding to client asset allocation.

But this is only half the story. In our digital world there is also need for a broader and deeper understanding of what customers want and how to get them onboard. For example, a new insurtech firm, Lemonade, recently hit the headlines when it successfully approved a claim in just three seconds. That is impressive when you think that in that time it had run 18 anti-fraud algorithms and sent a payment to the customer’s bank account, much faster than any legacy system. Only time will tell how impressed their customers and the rest of the fintech and banking world are with such developments.

However, many forward-looking organisations seem to be embracing behavioral economics – JPMorgan being a notable example –  as a way to better design products and client interactions and experiences. Indeed, an automated investing service, Betterment, estimates that between ten and 20 Fortune 500 companies have a C-suite Chief Behavioural Officer tasked with bringing this new way of business thinking to strategic business decisions, easing customer pain points and delivering exceptional user experiences.

So, does the combination of big data and behavioural economics give fintechs an edge? Well, they are certainly less weighed down by legacy systems and outmoded ways of thinking than legacy banks. This means they are able to create deeper customer connections faster and be more responsive to market trends. And legacy banks are not oblivious to what is going on around them. They are absorbing many of the technologies fintech offers, and often small fintechs themselves. But it is plain to see that big is no longer so beautiful.

Technology and behavioural economics will continue to expand their influence in a fast-changing world. The paradigm has well and truly shifted. What will emerge? Watch this space.

By Daniel Spier, CEO of Initium

About the author

Daniel Spier is the founder and CEO of Initium, a start-up banking services provider for fledgling fintech and blockchain firms.

Spier was most recently CEO of IDT Financial Services, a Gibraltar-based card provider.