A recent estimate suggests the global artificial intelligence in banking market size and share will generate $236.7bn by 2032, a Compound Annual Growth Rate (CAGR) of 31.7% between now and 2032. This tallies with McKinsey’s findings that Generative AI could add between $200bn to $340bn in value to the sector.

These figures indicate the extent to which AI will increasingly power financial services, informing digital payment advisors, intelligence, bots, fraud detection systems, risk management, trading algorithms, regulatory compliance and process automation.

Notable examples of AI implementation include Morgan Stanley’s OpenAI powered chatbot, which gives financial advisors access to 100,000 research reports and documents; Wells Fargo’s virtual assistant app powered by Google Cloud AI, which is capable of handling nearly 100 million interactions per year; and Deutsche Bank’s 2022 partnership with NVIDIA, which facilitates AI and machine learning within its business.

Can UK fintechs raise their AI game accordingly? The jury’s out. A recent survey from EY found almost half (47%) of leading UK fintechs believe their board lacks the requisite level of expertise in generative AI.

Another issue is winning over consumers. FIS’ Trust in Generative AI research found that almost one-third (30%) of UK consumers do not trust generative AI at all. For respondents with little or no trust in the technology, the most important factors in increasing their trust are more transparency into how data is used (66%), the introduction of regulation or legislation at government level (62%), as well as knowing there is a human overseeing the technology (61%).

In order to harness AI’s potential, fintech firms will not only need to become proficient with the technology, but also be transparent about its use, avoid data breaches, and communicate the value of AI to their customers.

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Why AI?

For financial service providers in a landscape marked by high insolvency rates, risk is a key battleground. The FIS Global Innovation Report found 47% of executives in the UK face more risk now than in the past, with financial risk cited as the top concern (62%).

In response, 60% of UK executives plan to increase their investment in AI, with 74% of leaders believing the technology can help to address risk. For example, credit officers can harness AI score breakdowns and recommendations to identify risk drivers for business borrowers and replicate how changes to the credit terms impact the risk profile for individual customers.

AI can also assist with strategic decision making, as the technology makes it possible to draw upon – and make sense of – huge sets of data, in no time at all. Not only can AI analyse historical financial data, but it can also dive into transaction and market data, as well as news feeds and social media, to make customer and market predictions. AI-powered algorithms can uncover hidden patterns without the need for human intervention, supporting data analysis and customer segmentation.

Customer experience can therefore also be supported by AI, as the technology can help financial service providers understand their customers, their preferences and needs. This has great potential to support the delivery of personalised experiences and services.

Another key use case of AI is in transaction monitoring and identity verification to counter fraud, such as impersonation fraud during digital onboarding. AI can be used to scan a prospective customer’s identification documents, analyse security patterns, and even implement biometric scanning and behaviour analysis to verify a person’s identity.

Keeping pace

Despite all its potential, AI has a communication challenge. The technology needs to be explained better, not only to end-customers but also within the financial services sector itself.

Andrew Bailey, governor of the Bank of England, recently tried to articulate his experience of the use of AI to analyse markets to buy or sell shares. He commented, “all of us who have used it [AI] have had the experience of a sort of hallucination, and it sort of comes up with something that you think: ‘how on Earth did that come out?’”

He added, “if you’re going to use it for the real world and real financial services, you can’t have that sort of thing happening. You’ve obviously got to have controls and an understanding of how this thing works, and there’s a lot to do there.”

Regulation that champions innovation while ensuring customers are protected is needed for AI to gain trust and flourish. As such, steps are being taken to address safety concerns – one example is the UK’s partnership with the US AI Safety Institute. More collaboration and the pooling of resources between friendly nations can only be a good thing if AI is to do more good than harm.

AI is changing the way financial service providers interact with customers, mitigate fraud and make strategic decisions. This starts with fintechs, which are often the canaries in the mine – their innovation representing the changing needs of the customer and their success or failure illustrating the market’s response.

​Firms can win in this space, but to ensure success they must bring everyone along on the journey – by educating their customers about AI and being transparent about how they are using data. They must also address the cost and management concerns that surround the technology. If they can do all of this, generative AI has great potential to transform financial services in the UK.

Rob Hudson is Head of International Banking and Payments at FIS