If you read any business or finance news, you would have found it impossible not to notice that there was another Davos last month. I rather agree with Andrew Curry, who says that the worst thing about the event is the temptation to take it seriously, but business leaders do turn up there to make speeches and it can be useful to listen to them to spot key themes. This year, as would expect, artificial intelligence (AI) was centre stage.

AI Is The Future of Fintech

Bryan Zhang (the executive director and co-founder of the Cambridge Centre for Alternative Finance at The University of Cambridge Judge Business School) presented the results of their research on the future of global fintech. The study gathered data from 227 fintechs across five verticals (digital lending, digital capital raising, digital payments, digital banking & savings and insurtech) across the Asia-Pacific, European, Latin America and Caribbean, Middle East & North African, North American and Sub-Saharan African regions. Almost three-quarters of those surveyed identified AI as the most important factor in the development of fintech in the next five years (and almost half of them pointed to embedded finance, open banking and the digital economy as the second most important factors).

I think these findings are uncontroversial. We can all agree that the fintech sector is poised to be significantly transformed by advances in artificial intelligence (AI) across a number of areas. But how, exactly? And where will the biggest impact be? Scanning through various reports, news feeds and post I can see a number of key business functions that will be affected. Here are a few of them:

Personalised Banking and Services: One of first and most obvious uses of AI, building on the masses of historical data available to banks, will be to push much more personalised products and services to customers. AI can help banks and their fintech competitors to create tailored offerings for each individual, ranging from from customised credit cards to unique savings plans;

Regulatory Compliance (RegTech): AI will help in the development of systems that can automatically adapt to new regulations and ensure compliance more efficiently. In my view, the next really big fintech businesses will actually be regtech businesses and AI is certain to power them;

Enhancing Robotic Process Automation (RPA): In their book “The Future of Finance”, Henri Arslanian and Fabrice Fisher pointed out that while automation can be enabled with relatively unsophisticated RPA technology, for more complex processes with more varied inputs, more sophisticated techniques are needed. Thus AI, combined with RPA, will result in cost savings and increased efficiency for financial institutions;

Credit Decisions and Risk Management: AI systems will help financial institutions make better lending decisions and manage risk more effectively. As a result, the market is moving towards insights-driven lending rather than expert judgement, which helps maximise rejection of high-risks customers and minimise rejection of creditworthy customers;

Investment and Trading: Mihir Desai, a Professor of Finance at Harvard Business School, points at two significant disruptions: the rise of passive fund managers and the growing dominance of quantitative investing because of the ability to analyze large amounts of data quickly. He thinks that these trends in finance suggests that an AI-dominated future can create “outsized” winners and losers pretty quickly;

Customer Support and Chatbots: AI-powered chatbots and virtual assistants will become more nuanced and capable of handling complex customer service inquiries, providing instant support and freeing up human resources for more strategic tasks. Personally, I am interacting with a bank chatbot, I don’t really care whether it is a person or not provided it does what I want; and

Fraud Detection and Security: I think this area is particularly concerning, because of the tidal wave of fraud that AI will unleash and the corresponding fintech opportunities to harness AI to get us to higher ground, as discussed in the recent U.S. Financial Services Committee hearing about the opportunities and risks associated with AI.

All of these uses of AI are, frankly, pretty unremarkable. But I think what a lot of this kind of analysis lacks is a recognition of the fact that it is the customers’ use of AI that will take the sector in some unexpected directions, not the banks’ use of AI. As I have written here before, financial services organisations need to pay strategic attention to the impending switch from human to machine customers.

Persuade My Bot!

The brilliant Cathy Hackl wrote about this a few years ago, noting that traditional marketing is all about the consumer, so marketers spend their effort of creating compelling narratives to connect with those consumers. Their goal is just to create demand for a product to but to build brand and relationships. That’s great for B2C and B2B2C, but what happens when we find ourselves in the world of Business-to-Robot-to-Consumer (B2R2C) commerce?

What happens to the accumulated knowledge and experience of the marketing department in a retail bank when banks will have to convince robots – rather than humans – that their deal is the best in the market? The robots won’t care about the Superbowl commerical. The robots won’t care about the race team sponsorship. The robots will be supremely indifferent to the brand colour and logo.

But what will they care about?