Financial services are failing to successfully implement artificial intelligence, European fintech executives have claimed, even as evidence suggests the technology will boost productivity and cut costs..
Fear of job losses, regulatory concerns and institutional inertia are among the factors that prevent bankers from fully adopting systems that drive products like ChatGPT.
“The big banks certainly won't adapt. [the technology] As early as any fintech,” said Tom Bloomfield, co-founder of Monzo and group partner at Silicon Valley startup incubator Y Combinator. But generative AI is “able to deliver the same products to banks more efficiently and at a lower cost. will make”.
Only 6 percent of retail banks are ready to implement AI at scale in their business, a Capgemini study found. But McKinsey estimates it could add up to $340bn a year to the global banking sector, equivalent to around 4.7% of total industry revenue.
Many say the technology, with its ability to answer questions and analyze vast amounts of text and numeric data in seconds, has the power to drive down costs across the industry. However, there are fears that the disruption will lead to job losses.
“People don't understand it as a productivity tool,” said Nasser Zuberi, chief executive of fintech accelerator Luxembourg House of Financial Technology. “They still genuinely believe it's going to take away their jobs.”
He added: “Traditional banks are fundamentally analog by design, and converting analog to digital has always been a difficult task.”
Zuberi, speaking at the Financial Times' TNW tech conference this month, used the example of money laundering checks, where institutions typically hire employees to trawl through spreadsheets looking for unusual activity.
He said that when he showed an organization how to optimize it with a custom AI model, which he estimated immediately saved up to €450,000 in payroll. Maybe, it was rejected.
“People don't like to shoot people,” he added. “They want to protect their job function and, if they have to fire people on their team who do that, they're potentially at risk as management or even their power. somehow ending.”
Central banks have recently been urged to “raise their game” with AI, according to the Bank for International Settlements, which said the technology could provide productivity benefits but also poses risks, such as misinformation. Information disclosure and risk of hacking.
A common problem with large language models, the technology behind most creative AI products, is their tendency to “deceive,” misrepresenting errors as fact. They are also known to generate information based on the data they have been trained on, which raises concerns about sensitive or protected information.
“There's not necessarily a need for rejection. [AI], but there is reluctance,” said Vince Wong, head of digital at NatWest, who called for an assessment of the risks, ethics and vulnerabilities of the technology before deployment. “Finally, we are one of the largest banks and Many customers store their data and finances with us. We should respect that.”
Customer service is one of the areas most affected by AI tools, which can talk and answer questions like humans. For more than a decade, digital banks have used machine learning to triage online queries, often sending customers directly to a customer service agent.
However, LLM-powered bots can understand a wide range of questions regardless of how they are phrased, and can execute decisions, such as placing a bank card order, on a human level. Eliminating the need for intervention.
“I really think it's going to kill the majority of customer service jobs in the next 12 months to the next five years,” Monzo's Bloomfield said.
Many banks and fintechs, including Klarna and NatWest, already use AI chatbots for customer service. NatWest's Wong said they've made huge strides with generative AI in their AI service Quora, receiving more than 11 million chats over the year, with more than half requiring no human intervention. In 2017, the service received 1,000 chats a month, and intervention was required.
Swedish fintech Klarna said its AI assistant can handle the work of 700 customer service workers and resolve queries in less than two minutes, up from 11 minutes previously. As a result, the company expects to save $40 million in customer service costs this year.
However, Wong said training the models is critical to his success. For example, one needs to understand that a change of address can have an emotional impact, such as bereavement of family.
“It was really important to understand the psychology behind it and, if you don't get it right, you can put it bluntly, confuse a lot of consumers,” he added.
Banks also had to be careful in introducing nascent technology while adhering to strict industry compliance rules and navigating an unregulated regulatory environment.
In a landmark ruling in 2022, a Dutch court ruled in favor of neobank Bunq after it sued the Dutch central bank to ban its use of AI to check money laundering.
Regulators last month lifted restrictions on German fintech N26 after it improved vetting measures. For years the bank had a cap on new client sign-ups due to poor money laundering controls and faced millions of euros in fines for consistently late filing of suspicious activity reports.
Karina Kozul, N26's chief risk officer, said it worked with regulators to build an AI model to predict whether a new customer is a criminal, which has reduced incidents on the platform by 90 percent. .
“If we don't embrace AI in the industry, in a few years, we won't be here,” he added. “We need to show the benefits and how we can adapt if we're using AI.”