McKinsey study

Generative AI could create up to $340 billion in annual value for banks

Generative AI could create up to $340 billion in annual value for banks, particularly in corporate and retail banking, according to McKinsey. However, the challenges are immense.

Generative AI could create up to $340 billion in annual value for banks

Just when banks believed they could finally bridge the gap between technology and business through agile and cloud-based operating models, a new megatrend has emerged: generative artificial intelligence (AI). According to a current McKinsey study, this technology could generate up to $340 billion per year for banks. This would represent approximately 9 to 15% of their operational profits.

Bank executives have already taken notice. At a McKinsey event at the end of September, two-thirds of the 30 bank executives in attendance believed that generative AI will fundamentally change their business. The pressing questions now are how to most effectively use the technology and how to deploy it within banks.

Generative AI in corporate and retail banking

The study found that all banking divisions could financially benefit from generative AI. Whether it's capital markets and investment banking, asset and wealth management, corporate, or retail banking. However, McKinsey sees the greatest financial benefit of the technology in corporate and retail banking, where it could create $56 billion and $54 billion in value, respectively. The study also attributes great potential to increase value in software development for banks at $48 billion. Explicitly, this refers only to generative AI – that is, technology that creates content in some form. Non-generative artificial intelligence, which merely processes and evaluates data, is already being used by banks, particularly in risk and legal areas. With $385 billion, the overall value created by AI in these areas is therefore the highest.

AI Is the new smartphone

Banks are currently using generative AI primarily to boost productivity in pilot projects, according to the study. However, the technology could also significantly change the job profiles of bankers and the way they communicate with customers. Yet, scaling the technology presents several significant challenges to banks and especially their leadership teams.

One initial challenge is the broad scope and extensive impact of generative AI. The study compares the situation with the advent of smartphones, which not only radically changed banking afterward but also brought an entire ecosystem of new businesses and business models.

Operative challenges for banks

The scaling of generative AI also brings operative challenges for banks, according to the study. Until now, the topic of "analytics" has been very focused and often centrally controlled. However, generative AI has shown that data and its analysis must be considered much more crucially for each part of the value chain.

The third major challenge is the incredible speed at which the technology is developing. The study states that the rate of change has never been greater. Whereas smartphones took several years to digitalize banking, the introduction of generative AI tools is happening in a fraction of that time.

Deutsche Bank and Commerzbank rely on partnerships for AI

For generative AI to enhance value for banks, seven strong capabilities from different areas are needed, according to the study. Banks would need a clear "strategic roadmap" outlining where and how different forms of artificial intelligence could play a role. Further, employees with the appropriate "skills" are needed, which is a challenge for banks, mainly due to the rapid pace at which generative AI is developing.

Banks would also need a more flexible and decentralized "operating business model." In addition, banks must decide how to handle technical solutions: build in-house, buy, or partner. For instance, Deutsche Bank is heavily focused on partnerships, as IT chief Bernd Leukert emphasized at the Euro Finance Week in mid-November. Commerzbank is collaborating with Microsoft and OpenAI, the company behind the ChatGPT chatbot, which has made the topic of generative AI widely accepted.

Another central requirement for deploying generative AI is high-quality "data and infrastructure" that AI can access. Despite all the opportunities, generative AI also introduces new risks, so banks will eventually need to revise their "risk and governance guidelines" and introduce new control systems. Lastly, the implementation of all these critical points requires good "change management."