Incumbent banks have been on a long journey to scale their digital banking operations amid tough competition from agile upstarts. How are they doing? We have just returned from McKinsey’s 21st Global Digital Banking Conference in Barcelona where, together with 280-plus executives from more than 150 leading financial services institutions, we got a good sense of the changing landscape. Billed “Unleashing gen AI: Digital banking in 2024 and beyond,” the event showcased banking tech in action. Our key takeaways: first, that incumbents are getting their act together on digital banking in some powerful new ways; second, that they are bringing back technology as a core capability; and third, that this new focus on technological capabilities will help them with the next big challenge—that of scaling generative AI deployment.
Scaling digital banking. It has taken some time, and the progress has been far from even or uniform, but we are finally seeing examples of incumbent banks getting real scale in their digital banking operations—and making them profitable. That is the result of purposeful investments and clear focus. Improved net interest income and stronger capital ratios have helped, allowing financial institutions to reinvest their increased profits into digital transformation efforts. In Barcelona, we were impressed by some vivid examples of incumbent institutions in Europe and Latin America that had cracked the digital banking code, and we know for sure that many banks in Asia are also gaining traction. Any early doubts that leaders of large financial institutions might have had have been dispelled: our sense is that leaders now really believe in the need to build robust digital banking operations. The rapid rise of fintechs in the past decade was the competitive spark they needed. Now, they are increasingly able to fight back effectively, leveraging their big networks and experience with a large product proposition. The game is still far from won, but at least the competition is back on a more even footing.
Technology is back as a core capability. This is a trend we began observing a few years ago and, in Barcelona, it was evident that it’s now widespread. A decade or so ago, tech was seen as a support function and banking CIOs attending this sort of conference would have almost no software engineers on staff; they would mainly manage contracts with external vendors. Today, banks want the tech skills in-house. They are ramping up their internal teams and trying to work more like tech companies by building scalable platforms and seeking to master software development. Some are even providing their tech products and services to other institutions. We estimate that between about 40 and 60 percent of the software development now being done at financial institutions is in-house and, in a few pioneering cases, it is 80 percent or more. This new focus on tech as a core capability is increasingly seen as a key to boosting productivity as well as being needed for running platforms and managing data. Indeed, some large institutions are even thinking about creating platforms “as a service.” The implication of making tech a core capability is that financial institutions need to reinvent the employee value proposition to be able to attract leading tech talent, build a great engineering experience in which repetitive work is automated, and standardize or reuse components to avoid waste.
Getting real about generative AI. Our expert colleagues have already written about how financial institutions have been quickly getting up to speed on gen AI—and what we saw in Barcelona amply confirms their analysis. At the global digital banking conference one year ago, most attendees were still trying to figure out what this technology was and could potentially do (or not). This year, gen AI was the main theme of the Barcelona conference, and we noted a wide range of applications are already up and running across financial institutions. There’s still a lively discussion taking place about the full extent of the benefits that the technology will bring and how to achieve them, but the talk is now about real use cases. Financial institutions are seeing gen AI as bringing about major productivity improvements in a range of areas, including customer operations, technology development, back office, personalization of the customer experience, risk, and compliance, among others. Gen AI has the potential to affect and make more efficient up to 80 percent of what a bank’s workforce now handles. Among other advantages, it can also radically speed up software development (thereby making our second point on tech as a core capability even more critical). In other words, we now have some fact-based evidence that this technology can be truly transformational. What’s still missing is evidence of scaling, and fuller details of how adoption can translate into impact. That’s likely to be a theme of this conference next year.
About the authors
Brian Ledbetter is a senior partner in McKinsey’s London office where Gökhan Sari is also a senior partner, Harald Kube is a senior partner in the Frankfurt office, and Leorizio D’Aversa is a senior partner in the Milan office.
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