Europe’s banks are currently earning better than they have for a long time. But the fat years could soon be over. Because the private customer business is once again in a state of upheaval. The reason for this is artificial intelligence. This has long since become part of everyday life among Austrians. ChatGPT, Claude and Grok are primarily used for information searches, price comparisons and recommendations, as an analysis by strategy consultancy Zeb shows. The recommendations often revolve around finances. In particular, Generation Z (born 1996 to 2010) and Generation Alpha (2010 to 2024) now consume content completely digitally in their everyday lives. They expect short, visual information.
These generations are certainly willing to take out consumer loans directly via social media. Generation Y (1981–1996) also uses digital offerings intensively, but combines them more with traditional channels – such as a website – and attaches more importance to data protection. AI is no longer a generational question. “The question is no longer who uses AI for financial topics, but how,” says Zeb boss Michaela Schneider. According to the study, common general artificial intelligence will soon be replaced by AI agents in the banking sector. An example: People can instruct their AI agent to regularly compare interest rates, check account fees or automatically process foreign currency transactions using the cheapest account model.
At the moment, the AI agents are not quite there yet. In the current year, the maximum that will probably happen is that the AI agent will inform the user about the savings potential, while the final decision as to whether to change an account or a bank still lies with the user.
In the coming years, however, the agent could – if the user agrees – independently optimize account packages, reduce unnecessary services or automatically initiate debt restructuring. The effect is said to be particularly large for deposits, according to a study by management consultancy McKinsey. There are significant interest rate differences between banks. A reallocation of just five to ten percent of the world’s deposits held in low-interest accounts to higher-interest accounts, mediated by AI agents, could reduce banks’ income on deposits by 20 percent, McKinsey expects. The majority of bank users already have at least two account details at different banks.
It is not the first time that banks’ business has been challenged. After all, when online banking was introduced, banks feared that customers would no longer come to the branches. And even with the emergence of fintechs, banks feared that they would further lose relationships with their customers. The concerns are not unfounded. In recent years, the bank has increasingly become an app for customers, Zeb expert Christoph Fischer told journalists on Wednesday.
But the banks should also take advantage of this. Banking apps need to evolve, says Fischer. While they are currently often just a digital bank statement, in the future they will become intelligent financial assistants. This means that they continually analyze the customer’s purchases and proactively provide information. For example, the app can warn if the account is in danger of slipping into the red, or point out that spending in certain categories is above average. Ultimately, the customer should avoid expensive overdraft interest or excessive indebtedness.
If banks do not adapt their business models, their global profits could fall by up to 170 billion dollars (147 billion euros). This corresponds to around nine percent of total profits, according to the McKinsey banking report.
In the next step, the experts expect the customer to only take on a passive role. His agent then negotiates directly with the bank’s agent. This eliminates emotional factors. Customers no longer stay with a bank out of loyalty. Decisions will then only be made based on rational criteria.
The lending business will also fundamentally change on the banking side as a result of AI. Artificial intelligence can automate almost the entire process chain – from the first customer inquiry through credit checks to payment and ongoing monitoring of the loan. This makes processes more efficient and precise, while at the same time risks can be identified earlier.
For banks, there is fundamentally great savings potential in AI agents. According to McKinsey, they could reduce costs worldwide by up to 800 billion dollars (690 billion euros), or around 20 percent. For example, through automation in customer service or in combating fraud. However, this requires high upfront investments in these new technologies.
