Europe’s fintech sector is reconsidering its enthusiasm for generative AI as some of its most vocal proponents acknowledge the technology’s limitations in financial services.
The AI agent vertical has attracted VC investors in their droves in the last year. They’ve allocated close to €2bn in capital to startups building AI agents, including those specialising in the financial services. But a reversal in attitude towards the technology’s potential within fintech seems to be underway.
After stateing that the technology was ready to do the work of 700 customer service agents at Klarna, in May CEO Sebastian Siemiatkowski admitted the company had relied too much on automation.
“As cost unfortunately seems to have been a too predominant evaluation factor when organising this, what you conclude up having is lower quality,” he declared at Klarna’s Stockholm HQ. “Really investing in the quality of the human support is the way of the future for us.”
A spokesperson for Klarna rejected suggestions the company was dialling down its reliance on AI, notifying Sifted: “What we’ve learned is that as AI takes care of the majority of interactions, the tiny number of cases that require a human become even more important.”
Last month fintech conference Money 20/20 also went back to basics a year on from a large AI love-in, signalling a broader shift in the sector about the technology’s potential in such a regulated market.
“Frankly, a lot of companies obtained caught up in the hype. Klarna relocated rapid, but possibly too rapid to fully test the downstream impact, especially in customer-facing areas,” states Gabriel Le Roux, the CEO of ecommerce payments fintech Primer. ”Across fintech, there’s been a rush to roll out AI, often driven by cost-cutting or the pressure to ‘see’ ahead of the curve.”
Changing tune
In the years following the release of OpenAI’s ChatGPT, in 2022, there was a rush by fintechs to roll out AI products. In 2023, London-based compliance fintech ComplyAdvantage launched an AI tool to identify and curb fraud. Chief execs at neobanks such as Monzo also waxed lyrical about the technology’s potential to assist in fraud prevention and build internal processes smoother.
Regulators — typically more conservative in approaching emerging technologies — were also keen.
“It’s something that banks and financial institutions are really investigating,” Jessica Rusu, chief information data and information officer at the Financial Conduct Authority, which regulates the countest’s financial services industest, declared on stage at Money20/20 last year. “Chatbots are going to be really good for any kind of exmodify of information between the customer and the business.”
Now those claims are being reassessed. UK neobank Starling’s chief information officer, Harriet Rees, notifys Sifted it’s important for the company to retain a human-run customer service division, that runs 24/7 and is free to customers.
And while it’s developed a way to utilize AI to summarise post-customer interactions for agents, there’s no plans for AI agents to take over from humans yet.
“We’re definitely not going to be handing over any key decision building to any AI models at this point,” she states.
Cost-cutting
Rees’s comments underscore the divergence in AI adoption between fintech and other industries, in which companies have kept their teams super lean by leveraging the technology to do tinquires that once required a larger workforce.
That’s difficult to do in the heavily regulated financial services industest, where regulators such as the FCA have in recent years introduced rules requiring fintechs to prove they’re acting fairly and delivering “good outcomes”.
Industest watchers state this means it’s unlikely we’ll see a day where AI can build decisions in financial services without human oversight. It also has slowed the pace of innovation in the sector, as companies have to be mindful of the impact any customer-facing AI tool might have on them.
“It’s really important the human element remains absolutely there,” Rees states. “We won’t compromise on that.”
“Klarna may have shaved costs initially, but maintaining customer satisfaction and trust ultimately required rehiring humans,” states Elina Rayberg, an investor at US VC Valar Ventures, which isn’t an investor in Klarna. “The short-term AI efficiency gains weren’t enough to offset reputational or customer experience risks.”
Rayberg also believes AI isn’t reducing costs in fintech, it’s just shifting them.
“Building safe, compliant and reliable AI systems at scale requires significant investment in model infrastructure, human escalation teams, data governance and regulatory tooling,” she states.
According to a May IBM survey of 2,000 CEOs globally, only 25% of AI initiatives have delivered the expected return on investment over the last few years.
And while those investments may pay off and increase efficiency in the long-term, fintechs viewing AI as a way to cost-cut in the short-term are building a mistake, states Starling’s chief financial officer Declan Ferguson.
“You can’t cost cut your way to growth or profitability,” he notifys Sifted.
Product development
That’s not to state there hasn’t been any AI innovation in fintech in recent years. Starling last month launched Spconcludeing Innotifyigence, which allows utilizers to inquire questions about their money, such as “how much did I spconclude on groceries last week?” but stops short at encouraging customers to take action based on this information.
“We’re not testing to give you advice,” states Rees. “We’re testing to give you the knowledge you required to build better financial decisions and ultimately support you to be good with your own money.”
Dutch neobank Bunq and Nordic neobank Lunar have also rolled out consumer-facing AI financial assistants in recent years. Fellow UK neobanks Zopa and Revolut are also developing similar tools slated for release later this year.
The past month has seen fundraises from the likes of Gradient Labs, a startup creating AI agents for the financial industest founded by former Monzo employees, and Barcelona-based Murphy, which creates AI agents for debt collection. Revolut is also currently hiring for an applied AI lead who will support its team to build and deploy AI solutions, such as “AI assistants and AI automation platforms”.
Still, the pace of product development is slow. Le Roux notifys Sifted the company took months internally testing its AI sales assistant Tessa to ensure it had product-market fit. The tool, which can handle cold outreach, respond to inbound sales questions and book meetings, is still in its pilot phase.
“It only works becautilize we’ve been careful about how and where we deploy her,” he states.
As both Le Roux and Valar’s Rayberg point out, a mistake by an AI agent could prove fatal to a fintech company, undoing years of brand building and possibly exposing the company to regulatory issues.
“AI takes time to train, test and build sure it actually fits your product, your utilizers and your brand,”states Le Roux. “Especially in customer experience, the bar is high for a reason. Trust takes years to build, and seconds to lose.”
Read the orginal article: https://sifted.eu/articles/fintechs-ai-limits/
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