AI Will Transform Financial Services, But Not By Making Personalised Credit Card Offers

At this year’s World Economic Forum (WEF) in Davos, artificial intelligence (AI) was centre stage.

AI Is The Future if 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 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 a wide selection of 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.

Over the coming three to five years then, we can all agree 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 posts 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 the first and most obvious uses of AI, will be to push much more personalised products and services to customers. By analysing behaviour, preferences and transaction histories (one of the key reasons for banks to stay intermediated), AI can help banks and their fintech competitors to create tailored offerings for each individual, ranging from customised credit cards to unique savings plans;

Regulatory Compliance (RegTech): Keeping up with changing regulations is a massive challenge for the financial industry and accounts for a substantial fraction of the new development spend of banks. AI will help in the development of systems that can automatically adapt to new regulations and ensure compliance more efficiently.?

Enhancing Robotic Process Automation (RPA): In their book “The Future of Finance ”, Henri Arslanian and Fabrice Fischer point out that while automation can be enabled with relatively unsophisticated RPA technology, for more complex processes with more varied inputs, sophisticated techniques such as machine vision and advanced pattern recognition systems with self-learning capabilities can be deployed. Thus AI, combined with RPA, will result in cost savings and increased efficiency for financial institutions;

Credit Decisions and Risk Management: AI systems will provide more accurate credit scoring models by taking into account a wider range of data, including non-traditional data sources. This 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 as technology made passive investing more competitive and the growing dominance of quantitative investing because of the ability to analyse large amounts of data quickly appears to be beating the deeper analysis that traditionally led to long and short investment decisions;

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; and?

Fraud Detection and Security: AI algorithms excel at detecting patterns and anomalies, which makes them perfect for identifying fraudulent activities and potential security breaches. In the next five years, AI-driven security solutions are expected to become even more sophisticated, lowering fraud rates and enhancing trust in financial services. 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 AI technology matures and regulatory frameworks adapt, the fintech sector will lean heavily on AI to drive innovation, reduce costs, improve customer experiences, and maintain a competitive edge. 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 pretty interesting, and pretty 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 creating compelling narratives to connect with those consumers. 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 will be supremely indifferent to the brand colour and logo, superbowl commercial or race team sponsorship. And if trust is indeed the top factor for consumers in choosing a financial services provider, the technical nature of the trust demanded by a robot (which depends on digital signatures, authentication schemes and liabilities) is a very different thing indeed.

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