Financial services are failing to successfully implement artificial intelligence, European fintech executives have claimed, even as evidence mounts that the touted technology will boost productivity and cut costs..
Fear of job losses, regulatory concerns and institutional inertia are among the factors preventing bankers from fully embracing systems that support products such as ChatGPT.
“Big banks will definitely not approve [the technology] as fast as any fintech,” said Tom Blomfield, co-founder of Monzo and group partner at Silicon Valley startup incubator Y Combinator. However, generative AI will “make banks more efficient and able to offer the same products at a cheaper cost.”
Only 6 percent of retail banks are prepared to implement AI at scale across their business, a Capgemini study found. McKinsey estimates, however, that it could add up to $340 billion in value annually to the global banking sector, equivalent to about 4.7 percent of the industry’s total revenue.
Many say the technology, with its ability to answer questions and analyze vast amounts of text and numerical data in seconds, has the power to cut costs across the industry. However, there are fears that the shutdown will lead to job losses.
“People don’t realize it’s there as a productivity tool,” said Nasir Zubairi, chief executive of fintech accelerator Luxembourg’s House of Financial Technology. “They still honestly believe it’s going to take away their jobs.”
He added: “Traditional banks are inherently analog by design and converting analog to digital has always been a difficult thing to do.”
Zubairi, speaking at the Financial Times’ TNW technology conference this month, used the example of money-laundering checks, where institutions typically hire employees to go through spreadsheets looking for unusual activity.
He said that when he showed one institution how to improve this with a custom AI model, which he estimated could save up to “€450,000 a year in salary immediately”, he was turned down.
“People don’t like to lay people off,” he added. “They want to protect their job function and, if they have to fire people within their team who do these jobs, they’re also potentially under threat as management or their power is being eroded in some way.”
Central banks have recently been urged to “up their game” with AI, according to the Bank for International Settlements, which said the technology could provide productivity gains but also carries risks, such as providing inaccurate information. and being vulnerable to hackers.
A common issue with large language models, the technology behind most generative AI products, is their tendency to “hallucinate,” to declare inaccuracies as fact. They are also known to generate information based on the data they are trained on, leading to concerns about sensitive or secure information.
“There is not necessarily a rejection of [AI], but there is reluctance,” said Wincie Wong, head of digital at NatWest, who called for the risks, ethics and vulnerabilities of the technology to be assessed before deployment. “After all, we are one of the big banks and many customers keep their data and finances safe with us. We have to respect that.”
Customer service is one of the areas most disrupted by AI tools that can converse in a human way and answer questions. For more than a decade, digital banks have used machine learning to classify online inquiries, often directing customers to a live customer service agent.
However, LLM-powered bots can understand a wider range of questions, regardless of how they are phrased, and they can execute decisions, such as ordering a bank card, removing the need for human intervention.
“I really think it’s going to eliminate the vast majority of customer service jobs” over “the next 12 months to the next five years,” Monzo’s Blomfield said.
Many banks and fintechs, including Klarna and NatWest, already use AI chatbots for customer service. NatWest’s Wong said they had made great strides with generative AI in their Cora AI service, receiving more than 11 million conversations during the year, more than half of which required no human intervention. In 2017, the service received 1,000 calls per month and needed intervention.
Swedish fintech Klarna said its AI assistant could do the work of 700 customer service workers and resolve queries in less than two minutes, compared to 11 minutes previously. As a result, the company is expected to save $40 million in customer service costs this year.
However, Wong said training the models to color was crucial to his success. For example, he had to understand that a change of address could have an emotional core, such as a family loss.
“Understanding the psychology behind it was really important and, if you don’t get it right, you can put it bluntly, piss off a lot of customers,” she added.
Banks also had to be careful to deploy the nascent technology while adhering to strict industry compliance rules and navigating an uncharted regulatory environment.
In a landmark ruling in 2022, a Dutch court ruled in favor of neobank Bunq after it sued the Dutch central bank for banning the use of AI to conduct money laundering checks.
Regulators last month lifted restrictions on German fintech N26 after it improved its control measures. For years the bank had a cap on new customer registrations due to lax money-laundering controls and faced millions of euros in fines for consistently late filing of suspicious activity reports.
Carina Kozole, chief risk officer at N26, said she worked closely with regulators to build an AI model to assess whether a new customer was a criminal, which had reduced cases 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 use AI.”
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