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Financial services shy away from AI over regulatory and labor fears
Financial services are failing to successfully implement artificial intelligence, European fintech executives said, despite emerging evidence that the much-hyped technology will boost productivity and cut costs..
Fear of job loss, regulatory concerns and institutional inertia are among the factors dissuading bankers from fully adopting the systems that underpin products like ChatGPT.
“The big banks will definitely not adopt [the technology] “As fast as any fintech,” said Tom Blomfield, co-founder of Monzo and group partner at Silicon Valley startup incubator Y Combinator. Generative AI, however, “will make banks more efficient and able to provide the same products at a cheaper cost.”
Only 6% of retail banks are ready to implement AI at scale across their businesses, a Capgemini study has found. McKinsey estimates, however, that it could add up to $340 billion in value to the global banking sector each year, equivalent to about 4.7% of the industry’s total revenues.
Many say the technology, with its ability to answer questions and analyse vast amounts of text and numerical data in seconds, has the power to cut costs across the industry. However, there are fears that the disruption will lead to job losses.
“People don’t understand that it exists as a productivity tool,” said Nasir Zubairi, chief executive of fintech accelerator Luxembourg House of Financial Technology. “They still genuinely believe it will take their jobs.”
He added: “Traditional banking is fundamentally analogue by design, and converting from analogue to digital has always been a difficult thing to do.”
Zubairi, speaking this month at the Financial Times’ TNW technology conference, used the example of money laundering checks, where institutions typically hire employees to scour spreadsheets for unusual activity.
He said that when he demonstrated to an institution how to improve this with a custom AI model, which he estimated could save up to “€450,000 a year in salary instantly”, the model was rejected.
“People don’t like firing people,” he added. “They want to protect their job function, and if they have to fire people within their team who do those jobs, they are also potentially under threat because management or their power is also being eroded in some way.”
Central banks have recently been urged to “up their game” with AI, According to the Bank for International Settlements, who said the technology could provide productivity gains, but also brought risks, such as providing incorrect information and being vulnerable to hackers.
A common problem with large language models, the technology behind most generative AI products, is their tendency to “hallucinate,” stating inaccuracies as facts. They are also known to generate information based on the data they were trained on, raising concerns about confidential or secure information.
“There is not necessarily a rejection of [AI]but there is hesitation,” said Wincie Wong, head of digital at NatWest, who called for the risks, ethics and vulnerabilities of the technology to be assessed before deployment. “In the end, we are one of the big banks and many customers keep their data and finances safe with us. We need to respect that.”
Customer service is one of the areas most disrupted by AI tools that can converse in a human-like manner and answer questions. For more than a decade, digital banks have used machine learning to triage online questions, often directing customers to a live customer service agent.
However, LLM-powered bots can understand a wider range of queries, regardless of how they are phrased, and can execute decisions, such as applying for a bank card, eliminating the need for human intervention.
“I truly believe this will eliminate the vast majority of customer service jobs” in the “next 12 months to the next five years,” Monzo’s Blomfield said.
Many banks and fintechs, including Klarna and NatWest, are already using AI chatbots for customer service. NatWest’s Wong said it has made great strides with generative AI on its AI service Cora, handling more than 11 million chats over the year, with more than half of those not requiring human intervention. In 2017, the service was handling 1,000 chats a month that required intervention.
Swedish fintech Klarna said its AI assistant could do the work of 700 customer service employees and resolve queries in less than two minutes, compared to 11 minutes previously. As a result, the company expected to save $40 million in customer service costs this year.
However, Wong said training the models to be nuanced was crucial to their success. For example, it needed to understand that a change of address could have an emotional tone, such as a family bereavement.
“Understanding the psychology behind this was really important and if you don’t get it right you can, quite frankly, irritate a lot of customers,” she added.
Banks also had to be careful when implementing the nascent technology, while adhering to strict industry compliance rules and navigating an unfamiliar regulatory environment.
In a landmark 2022 ruling, a Dutch court ruled in favor of neobank Bunq after it sued the Dutch central bank for banning it from using AI to carry out money laundering checks.
Regulators last month lifted restrictions on German fintech N26 after it improved its scrutiny measures. For years, the bank had a cap on new customer sign-ups because of its poor money-laundering controls and faced millions of euros in fines for persistently delaying the filing of suspicious activity reports.
Carina Kozole, chief risk officer at N26, said it worked closely with regulators to build an AI model to assess whether a new customer was a criminal, which reduced instances on the platform by 90 percent.
“If we don’t embrace AI in the industry, then in a few years we won’t be here anymore,” she added. “We need to show the advantages and how we can grow accordingly if we are using AI.”