Insights & Trends

The role of AI in fintech: A 10 year horizon

Insights & Trends

The role of AI in fintech: A 10 year horizon

Words Olly Betts

May 15th 2024 / 8 min read

The prospect of outsourcing almost every aspect of our lives to machines may seem scary—and yet increasingly inevitable. 

In the world of Fintech, this is certainly true. Machines are by no means novel to finance. Where people might have once looked with scepticism at ATMs dispensing our prized cash, we now happily put our life savings into ETFs and trust algorithms to make money, or indeed lose it, on our behalf. 

There are already huge productivity gains being made across financial services. Risk management, loan origination and assessment, due diligence, trading, and compliance are just some of the ‘functions’ (read jobs) being automated and enhanced through AI.

The bigger question surrounding AI in Fintech isn’t whether AI can do it, it’s whether we want it to, or indeed whether we trust it to. How comfortable are we with yielding control over financial decision making and security to machines?  

Over the next ten years, there are clear opportunities for AI to radically change and potentially improve our financial practices. Any change requires input from both incumbents (banks) and disruptors (fintechs). Both have a huge amount to offer—banks, a wealth of financial data that could massively improve the accuracy of LLMs, and fintechs, who can build solutions using the latest technology without being constrained by legacy systems. 

Here’s where I see key opportunities for AI to innovate in the next decade, and the role that both incumbents and disruptors have to play.

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AI for protecting against future threats

When: Already a problem

Bad actors often innovate faster than good actors. As AI capabilities advance, criminals are armed with a new set of tools and opportunities to attack with higher frequency. Generative AI is enabling more sophisticated and more creative threats than ever. 

Future threats posed by AI include:

  • Theft—direct attacks on banking infrastructure to steal money/data

  • Impersonation—use of AI agents to impersonate people and attack weak security

  • Social engineering—AI deepfakes and other social engineering tactics to scam customers

  • Fraud—AI generated synthetic data to circumvent AML, KYC and authentication controls

So how do Financial Services companies defend against these attacks? 

The only way to respond to this evolving threat is to upgrade defences by deploying the best AI experts armed with the latest tools. Fintech startups will have a huge role to play in this space due to their ability to attract the best talent and build using a greenfield tech stack, whilst incumbents have the huge data lakes required to build the LLMs required. 

Fintechs will help us detect deep fakes and protect consumers from scams—such as platforms like WILTY that can help you scan photos or videos and identify them as deep fakes. For older generations, who are typically at higher risk of being scammed, fintechs like Carefull help protect your money, credit, and identity from threats. 

There’s significant demand for more accurate fraud detection. Banks spend billions on fraud detection but suffer from models which are over-sensitive with false positives costing  merchants around $400bn in value last year—10x the value of genuine fraud! This is largely due to a lack of contextual data resulting in models being trained on data that is biased towards good transactions and overcompensating. 

Mastercard are demonstrating how incumbents can lead the way here, developing a new AI model built on a neural network that provides better context around whether the person is likely to spend money at the merchant based on their history, profile, etc. 

Insurance companies like Aviva are also turning to AI to reduce fraud. LLMs using AI image/video recognition can be used to identify legitimate claims and reduce the time it takes to settle these claims.

AI for hyper-personalised financial services

When: 2-5 years

The past five years has seen a great deal of focus on the ‘verticalization’ of Fintech, with startups creating financial products catering for specific niches to tap into greater customer loyalty and value per user. LLMs can be a catalyst for this trend to accelerate towards hyper-personalised financial services. 

One of the biggest fears preventing people outsourcing financial decision making to AI is the hallucination risk (e.g. one day you wake up to find your AI wealth manager has invested all your money in a meme stock). This risk is real when LLMs are trained using data from the internet—the internet is weird, so your AI will do weird stuff.  

But the technology now exists to make it possible for you to outsource your finances to AI. Banks won’t want us to do this, so Fintechs need to find a way to build LLMs trained using real financial data. Might this inflection point in AI capability be the missing ingredient for Open Banking to deliver its promise of a revolution in financial services?

AI finance for AI natives

When: 5-10 years

Gen Z has been labelled the first ‘internet-native’ generation, having grown up surrounded by and immersed in the internet. The next generation (Alpha) are likely to be dubbed the first ‘AI-native’ generation. Where Millenials and Gen Z may use ChatGPT to replace search and Midjourney to power memes, Gen Alpha will have an AI agent for all everyday tasks, have AI friends, and be taught by AI teachers.

They will likely see fundamental changes in the way they work and the way they consume products. And as this generation comes of age, they’ll start engaging with financial products in radically different ways. 

So what financial services does a consumer need when they’ve grown up in a world of AI?

Much of this will come down to interface and the way financial services look. A generation more comfortable with conversational interfaces might see a shift away from typical banking app interfaces and towards conversation, sending and receiving payments via message, for example (AKA Venmo for everything). 

There’s of course a growing literacy and comfort with new digital asset classes, and AI could be the vehicle to drive the shift towards ownership of virtual homes, virtual land, virtual apparel (which crypto has not been fully able to deliver on). 

Infinite optionality and ultra-customisation seems a likely demand. While we currently choose between competing financial products across different providers, AI natives will likely look for an infinite number of products and resources at the click of a button. Financial services can’t continue to exist with a small selection of products—they’ll need to expand, diversify, and adapt to the ever changing needs of their users. There are some fundamental questions that need answering here. How do you even start going about building a bank that serves this?  

Personalisation may have also advanced so far to the point that the algorithms you use are so predictive, you don’t even need to think or execute decisions—they’re just made automatically.

A final thought

There is another argument that runs counter to all this speculation—that AI has done all it can in financial services. 

Unlike most technology companies, the business model of financial services requires near-perfection in order to avoid high cost outcomes. There is far more room in other industries for ‘getting it wrong’, whereas in financial services, error results in loss of money, reputation, and livelihood. 

Plus Financial Services companies are really good at making high risk decisions. In lending, for instance, algorithms make real-time decisions about a customer’s affordability and are really good at making the right decision. Automated customer service agents are often inefficient with a lot of testing showing simple FAQs result in faster customer query resolution. 

That said, I write this excited and convinced this is the next platform shift. The world we live in has changed and financial services will have to adapt to keep up. Both incumbents and disruptors are about to encounter a whole new set of problems to solve. For both, the opportunity is tremendous. 

About Olly 

Olly Betts is the sector director for fintech at Founders Factory, overseeing building and support of our fintech ventures. Prior to this, Olly founded OpenWrks, an open banking API platform, which was acquired by Tink in 2020. He's also the Founder & CEO of Version 40, supporting founders who are building fintech products.

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