By Erin Nicholson, Global Head of Data Protection and Privacy at Thoughtworks
Ever since the AI fuse was lit, it has fundamentally changed the landscape of financial services. AI is revolutionising the way we pay our weekly bills, check our credit score, and has ushered in an era of hyper-personalisation across the board. The most transformative uses of AI often lie not in flashy new toys, like ChatGPT, but rather in the diligent and smart work of integrating into existing processes.
The chatbot use case dominates headlines, but is not where the real impact will be with Generative AI. True AI impact lies in harnessing existing frameworks to empower individuals and democratise financial services. By fully embracing strategically and thoughtfully, we can ensure the AI revolution benefits not just a top select few, but everyone’s finances.
The tools we have in our arsenal, such as Data Protection Impact Assessments, transparency statements, data flows, and Legal departments assessing IP and confidentiality issues, all work with GenAI. Trying to reinvent the wheel could lead to a slowing of innovation or missing key risks which could have been easily overcome with tried and tested methods.
From Apple Pay and beyond
Established household name banks to savvy fintech scale-ups are now building faster, more scalable and future ready organisations. For example, the proliferation of digital payment methods is pushing us towards a post-cash world, for better or worse. Today, Apple Pay, and its peers have become commonplace, seamlessly woven into the fabric of our everyday existence.
This quick widespread adoption underscores the power of digital payments, not just in terms of convenience when you forget your wallet, but also for a more data-driven financial world.
At the forefront of this data revolution are emerging players who are using AI to lower cost and deliver more innovative offerings. And with more data, generative AI can be used to create personalised payment experiences, such as suggesting ways to cut down on household bills, aid in fraud detection, and to help supercharge customer loyalty and satisfaction.
With great power comes great responsibility
It is impossible to ignore the privacy and security needs of both sensitive customer data and proprietary and confidential data. It’s vital to create well-functioning digital infrastructure – sustainable and safe AI depends on it. For example, when a bank representative might want to quickly analyse long legal documents, could we empower them to safely use GenAI or AI systems to find information quickly and make a decision with AI assistance? Using privacy engineering you can unlock previously unworkable data sets as it is now possible to increase utility whilst maintaining privacy.
Risk management can be substantially enhanced by AI’s automation capabilities and greater understanding of customer profiles. With understanding profiles comes the ability to, in an automated fashion, pick out anomalies which could be fraud or a reaction to phishing. We can do this at the personal level, but also use it to analyse trends, such as new types of frauds, and alert people to it before it has had a chance to cause damage. Generative AI and privacy engineering together allows a public health approach to any business model, looking at trends and surfacing risks and opportunities which were buried in the data before.
The ability of completely changing the manual time consuming processes that are often prone to human error, means we can see far more accurate and data-driven processes driven by AI. It’s like replacing a spade with an excavator – same job, just a completely different level of speed and ability. AI can transform the way organisations generate reports, identify risk from large volumes of data and automate previously manual processes. Delivering long-term growth over short-term wins
Fintech firms who champion and strategically invest in AI and data to deliver long-term growth will beat those who chase short-term gains. People want their money in the safest place, without the nuisance of erroneous alerts, being pushed products they don’t have an interest in, or over laborious authentication. It’s a real balancing act, and one which AI is particularly well positioned to help with.
Competition is frenetic and fierce – and fintech firms who can supercharge efforts with GenAI will be better qualified and equipped to meet the needs of their customers. That said, financial services face a significant challenge in AI adoption due to the large amounts of sensitive and proprietary data they manage and process. For this reason, they need to embrace emerging privacy technologies to counteract the new privacy risks introduced by advanced AI systems.
It’s also about the ability to actually integrate AI into your business- it’s not always about who built the best product, but rather those who fitted this into their existing organisational goals.
