As banks look to use generative AI, can they move quickly enough?
ChatGPT launched in November 2022 and, less than 18 months later, it’s clear banks must urgently undergo an artificial intelligence transformation to remain competitive.
Generative AI, which uses machine learning algorithms to interpret and respond to language, has already begun to revolutionise workplaces. For banks looking to utilise the technology, scaling up is part of an ongoing digitalisation process – it will require effective change management, clear targets and accountability for results.
However, banks face fierce competition. The Sopra Steria Digital Banking Experience report, with Forrester & Ipsos, surveying 900+ banks and 12,500 users, showed that banking leaders have embraced generative AI – indeed, some pilots are already underway. But it also illustrated a landscape in flux, as traditional banks compete with tech-savvy newcomers and consumers demand a higher level of digitisation.
Generative AI: The latest player in digitisation
Generative AI has emerged as a critical component of digital transformation, with almost one-in-two (47 per cent) banks planning to integrate AI into their business, according to the DBX report.
Many of these forays are in their early stages, with pilots being conducted that will explore how to deploy AI while mitigating risk. The most advanced banks, however, have identified high-priority areas to scale, with the aim of turning AI-led banking into reality.
“There is a high level of personalisation offered by AI, whereas currently most banks react to their customers’ requests,” said Mung Ki Woo, chief operating officer, Sopra Steria Financial Services
“When is the last time your bank called to propose a product or change? That’s probably something that would be appreciated – a bank suggesting, for example, that you put money into a savings account to take advantage of rising interest rates. Something as simple as that is what generative AI can provide.”
These technologies are unlikely to be customer-facing – at least not at first.
In the short-to-medium-term, generative AI is more likely to be used to help bank staff, who in turn will help customers.
“Bank staff are overwhelmed with the level of complexity in banking. That’s down to a combination of two things: the portfolio of services that banks offer has become very broad, and the regulatory environment is ever-changing,” Woo explained.
“For instance with rising interest rates, many consumers have wanted to understand more about their mortgages, but the same question asked by two different people, each with a different mortgage product, may have two completely different answers. A ChatGPT-like service that helps bank staff to sort through regulatory and product information would dramatically increase their quality of service.”
The risk posed by Big Tech
While banks’ appetite to deploy AI appears strong, traditional providers face competition from an intimidating source: Big Tech.
Tech companies such as Apple and Amazon have begun to creep into financial services, streamlined by the fact that many consumers already trust them to store their financial information. In fact, almost half (47 per cent) of customers surveyed in the DBX report said they were tempted to open a bank account with a Big Tech player. Banking leaders registered this threat, with more than one-in-three (36 per cent) judging Big Tech as “the greatest threat to our business”.
“Big Tech is entering banking slowly but surely,” Woo said.
“Most have made forays into payments, which is probably the easiest banking service to penetrate – particularly in Europe, where the regulatory barriers to entry have been lowered. From there, they have expanded into simple loans and basic savings products. Most likely, they will continue to expand one step at a time.
“These companies are formidable competitors. They own large technology platforms, they have very large customer bases, they can invest massively. What’s more, many customers already trust them to provide financial services.”
The DBX report also indicated that banks were at risk of losing customer trust. While trust remained high at 80 per cent, over half of consumers (51 per cent) said they believed their bank was not interested in earning them money and only 27 per cent believed their bank offered them suitable financial services.
“One of the things on which banks pride themselves, one of their core assets, is the trust that the general public has in them. That trust is being challenged,” Woo said.
“Our report shows clearly that banks need to do a better job of serving consumers. That means becoming more personalised, more proactive and more streamlined. Generative AI can help on those fronts.”
A cyber arms race
Like any technology, generative AI also poses risks, which become more pronounced given the sensitivities of financial services.
The DBX report highlighted concerns of an AI ‘arms race’, with per cent of bankers concerned the technology will put their company at greater risk of a successful cyberattack.
These fears are not unfounded. For example, generative AI makes it easier to produce deep fakes, which may surpass banks’ identity checks. However, on the other hand, AI can also be trained to identify deep fakes and respond to this threat.
“This is where you see an arms race,” Woo said.
“On the one side, you have fraudsters using AI maliciously. On the other side, banks can use the technology to improve the tools they have to protect themselves.”
While the pace of change in generative AI is fast, the message is clear: Banks must work quickly to keep up with competition.
“It’s a never-ending race,” Woo said.
“Those who act quickly will be the first to gain the benefits and build a competitive edge.”
