Last month I had the pleasure of speaking at the NextGen Banking conference in London, on a panel with some leading lights from the industry’s Artificial Intelligence (AI) community.
Creating a better world—that’s the potential Intel sees in Artificial Intelligence. If that sounds rather grandiose, the following paragraphs should explain it in a little more detail.
People still talk about AI as hype, or something that’s still a few years away, but one phrase that I heard repeatedly at the event was “low-hanging fruit”, referring to the use cases for AI that are either already proving successful, or that can be implemented relatively easily.
Tackle the low-hanging fruit first
Foremost among that low-hanging fruit was compliance and risk. Here, AI can be deployed to recognise patterns to detect fraud, for example, or in anti-money-laundering (AML) applications, or for sanction screening. According to Action Fraud, fraud (including cybercrime) cost the UK nearly £11bn last year, the equivalent of £120 for each adult in the UK. Plus, with only 50 per cent of money laundering or terrorist-financing activity detected systematically, the industry has to find ways to do better. This is what we mean by AI creating a better world.
I also see AI helping banks improve their top and bottom lines through operational efficiencies and better customer engagement. One of my panel colleagues—the digital and mobile director from a major UK building society—was talking about their initiatives to provide more tailored advice to customers at greater speed than before. In retail banking especially, this often means digital assistants powered by AI. The benefits to end-users are clear: an automated assistant that’s always available and infinitely scalable to meet customer demand; and instant access to data and systems, providing quicker advice based on a wider array of data. If that advice helps somebody manage their finances better, and can afford a home where they couldn’t before, that’s another win for AI, and another step towards a better world.
Keeping data under control
One of the reasons AI has seen a resurgence in interest over the past five years is the explosion of data. We’re moving from a person-based to a machine-based data ecosystem. Where a human generates 1.5 Gigabytes of data a day, an autonomous car can generate 4 Terabytes in the one-and-a-half hours it typically spends on the road. As these devices become more commonplace—and there’s every reason to think that they will—good data management and accessibility will be essential to prevent a trickle becoming a flood.
There’s always been a big question mark over banks’ ability to bring their data under one umbrella. Complex combinations of legacy and modern systems create silos that may prevent deep analysis. Potentially banks can build scaffolding around their data centres to extract the information and build effective AI tools right now; however, it will be essential for banks to build an agile infrastructure for innovation to be able to meet real-time demands of their customers and regulators.
From tiny steps to giant leaps
If a bank can develop a robust data management strategy, we foresee them being able to diversify beyond financial services, stay relevant with their customers and become core to their lives, even becoming lifestyle companies. Instead of being places to just store money, could banks become trusted custodians of data? Could they allow their customers to monetise that data by allowing other companies to access it? Make no mistake, there are questions around responsible use that still need to be addressed, but there’s a fantastic opportunity here for banks to capitalise on their leading position as trusted guardians.
This is what we mean when we talk about a better world through AI. More secure, responsible banking, improved services to customers so they can manage their finances better, and innovative new services that benefit banks and their customers. With the right approach, it’s not a huge leap from today’s low-hanging fruit to tomorrow’s pie in the sky.