Will European Banks Embrace AI to Revive Fortunes?11 min read
Why are European banks so unloved and can they do anything to turn on the charm? Despite a return to profitability as interest rates finally resumed an upwards path to create positive net interest margins, investors continue to show little interest in them.
In the US the story is already very different as bank share prices have rebounded well in the wake of bumper profits. But could a wider and faster commitment to AI and other new technologies by US banks be behind this divergent appetite in the investment community?
Nearly all US banks now trade at a premium to book value, while (according to an analysis by The Daily Telegraph) “it’s hard to find any European banks whose shares trade above it.”
After the Farage scandal, no wonder banks are regarded as uninvestable.
To emphasise the difference, the report points out that JP Morgan Chase is currently trading at around 1.7 times its book value, while HSBC, one of Europe’s largest and most solvent banks, trades at just 80% of book despite similar returns on equity to JPM. The NatWest Bank share price, it notes, is actually lower today on a comparative basis than it was in 2009 when the entire banking system was teetering on the brink.
Of course, there are multiple reasons for the different positions, including macroeconomic and geopolitical factors. European banks also have to carry a far heavier regulatory burden than their US counterparts, including more onerous capital requirements. There are also threats of bank windfall taxes in Spain, Italy and elsewhere, while other political “punishments” are more common in Europe says The Telegraph. It cites the example of European and UK banks being banned from paying dividends during the pandemic, something not imposed in the US.
However, could there be a more fundamental difference which more discerning investors have identified? Is there a much lower appetite for innovative investment in Europe’s banks for the new technologies that could deliver future competitive advantage? If so, will they do something about it?
A study from research group Evident Insights suggests that might be the case. In its “AI Innovation in Banking” report, which includes an index that ranks banks on their commitment to AI investment, it says “North American banks and payment providers occupy 10 out of the top 15 rankings, while only four European banks feature in the top 15.” The lone bank outside those core regions ranked in the top 15 is Australian. (The Evident AI Index uses 142 distinct indicators to rank 23 of the largest banks in the world on their AI maturity and will soon be expanded to cover 50 banks and financial institutions in North America, Europe, and Asia.)
Evident, which has many banks as its clients, not only sees deployment of AI in banking as the single most important game changer in the industry but also uses AI and machine learning tools to conduct much of its research and data gathering.
There seems little doubt that banks who embrace Gen AI will strengthen performance and speed, reduce costs, improve customer experience, and more easily satisfy regulatory compliance. This can all take place within a trustworthy AI environment that builds confidence in the technology.
In essence, AI automates different learning approaches. These enable organizations to quickly deploy large amounts of data to create foundation models that can be used as a base for AI systems. Gen AI then becomes a powerful tool that streamlines the workflow of creatives, engineers, researchers, scientists, and more across many diverse use cases.
Evident says that while different strategies are emerging with AI innovation in banking, “All banks are thinking about how AI can enable them to operate better, faster and more efficiently.” But it recognises that only a handful of banks appear to be pursuing cutting-edge AI innovation.
The four most common factors it sees that differentiate the leaders in this race include:
- A focus on pure and applied AI research. Important, but the scarcity and cost of research talent make this an expensive strategy that few banks can follow.
- A volume of highly cited AI-related patents. This is a strategy that not every bank can follow - especially in Europe where patent filing is more restricted.
- A strong ecosystem: Participate in the open-source community, as well as develop a wide range of partnerships with universities, accelerators, and vendors.
- Strategic investments: Partner in early-stage companies at the cutting edge of AI - ideally with an internal venture rather than a VC return focus alone.
There is a growing belief that the use cases for AI in finance are widespread. AI can be a lynchpin technology for addressing the challenges of growth, cost reduction and risk management. With it, new products can be built more quickly, propositions scaled at lower marginal cost, and poor credit risks measured and monitored at previously unimaginable scale and scope.
The report not only makes it clear that AI will make the differences its supporters claim, but that bringing it onboard now has fewer obstacles than previous new initiatives might have faced.
This, it says, is because “persuading organisations that AI is important and needs to be supported has become far easier. This is partly because everyone can see what the potential impact might be, but also because the tools to actually do things are suddenly at hand.”
“Secondly, shareholders no longer need to be convinced of the importance of an AI strategy.” It warns that “CEOs who cannot show coherent AI strategies will fast become an endangered species.” Investment resources should therefore become available as it also expects that wider executive buy-in is gaining traction. It notes that “CFOs will want evidence of AI Innovation at least as much as they used to demand some evidence of ROI on complicated data projects.”
Investing in AI is another barometer Evident uses to measure commitment to the new technology and here too it says “US banks have long been leading the way in terms of the number of investments they make into AI companies. However, European banks - particularly the French - are increasingly focusing on this space. Back in 2015, 89% of AI-related investments were made by US banks. This has since decreased to 61% in 2022.”
Nevertheless, it says that North American banks continue to “accelerate away from their European competitors.” They published 80% of all AI research in 2022, filed 99% of all the AI-related patents in 2021 and made 60% of all AI-related investments in 2022.
It said that it expects these “leadership positions being taken will become increasingly hard to overcome.” It added that the long tail of North American banks will find that competition with the top tier banks is going to get even harder. And Europe might already be too far behind.
The report says: “We see comparatively little AI innovation across European banks” and accordingly concludes that “financial institutions in APAC currently look to be the only significant potential AI innovation competitors to the North Americans.” Although it does accept that there is a real market gap and branding opportunity for “The European AI Bank” to be created.
“Getting AI innovation right is key for the banks that wish to prosper in the coming decade.“
Finally Evident asks: “Does Generative AI change the rules of the game?” It acknowledges that, to date, AI innovation has been a top-down game characterised by strong leadership, aggressive focus of resources and highly educated AI specialists.
It says that advances in Gen AI have reinforced this. To counter it banks need a centralised AI innovation strategy, with group-wide orchestration and leadership. This is neither easy nor inexpensive, and counter to many banks’ embedded cultures.
But easy access to Gen AI tools like ChatGPT does allow for new levels of bottom-up innovation that can create new working practices and business tooling. “Therefore, those banks that manage to let their staff test and share their new AI hacks will have cracked possibly the biggest innovation opportunity on offer: how to genuinely become learning organisations.” But as we know from past experience, this is easier said than done in the conservative corridors of bank executive suites.
Evident concludes its report with a 10-point plan for bank executives who want to embrace AI and make a difference in their industry. These are:
- Establish an AI innovation strategy - ideally with a sense of vision for the future and a roadmap against which to prioritise investments.
- Build an AI research team, covering applied and pure research, and give them a clear route to liaise with business leaders across the bank.
- Publish their research and encourage them to submit papers to academic AI conferences.
- Build a couple of strong AI university relationships supporting pure research. This might perhaps be with one domestic and one globally relevant university.
- Build out a patent strategy - especially if aspiring to operate in the US or globally.
- Build incentives and foster a culture of patenting to boost focus in the AI patents space.
- Think through what the ecosystem looks like and have a proactive investment strategy to improve it.
- Lean into strategic investments - and test out acqui-hires as a strategy. There are experienced AI teams who can be acquired in the market.
- Continuously benchmark the bank’s position and progress against the competition.
- Celebrate and reward even the first minor steps into AI innovation. Momentum is key.
So, it is clear that while European banks are well behind in the AI race, they are not completely out – yet. But they do need commitment, leadership, and an AI strategy if they want to catch up and they should not take too much more time considering it.
Or perhaps The Telegraph was right when it concluded that the combination of business and political factors has “made the entire European banking sector uninvestable.”
But we don’t believe the future is as bleak as some commentators make out. That is why we partner with the leading technology firms that are developing the AI capabilities and the hardware and other resources to deliver them. SoftServe understands the stack, technologies, industry use cases, technical jargon, and specific business challenges to ensure smooth AI implementation. Working with key partners, SoftServe experts deploy the right hardware for whichever option of in-house or hybrid cloud is selected to allow the smartest Gen AI software and drivers to do their job.
Our conversations are also well advanced with many leading financial institutions to help them realise the benefits of AI to their customers, employees, and shareholders. We therefore remain optimistic that the future for a Gen AI-led financial ecosystem is bright, where challenges and entrenched attitudes can be resolved by working with the right partners.
As Evident observes: “Not having a strategy around AI innovation is also a choice. But it's unlikely to be a wise one.” Shareholders in European banks should therefore be asking their boards of directors which option they have chosen to pursue.
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