Executives in banking are starting to recognize more and more of the possibilities offered by generative artificial intelligence. And yet, the scaling of such projects has new challenges in store, warns consulting firm McKinsey.
Two-thirds of the leading digital and analysis experts who recently took part in a forum about generative artificial intelligence (GenAI) organized by U.S. consulting firm McKinsey expect that this technology will fundamentally change how they do business.
The most pressing issues for the banks are how and where they can use AI most effectively, and how they can ensure that the applications are accepted and scaled throughout the entire organization. This is the conclusion of the new McKinsey study «Capturing the full value of generative AI in banking».
This Is Different
For banks wanting to benefit from the advantages, the scaling of GenAI requires the same capabilities as any other type of scaling, in some ways – change management skills and the support of the top management level.
According to McKinsey, however, there is a series of factors that explain why the scaling of GenAI is different – for instance, in terms of the scope of the task and the associated implications. In just the same way as the smartphone catalyzed an entire ecosystem of businesses and business models, GenAI will make the full scope of advanced analytical capabilities and applications relevant.
«Obscure» Jargon
From one day to the next, bank managers must fight their way through a jungle of once-obscure concepts such as «reinforcement learning» and «convolutional neural networks». Yet to scale GenAI, they need to do more than just learn some new concepts. Management teams must look at the various potential routes that GenAI could take, decode them and consider them, adapt in terms of strategy, and position themselves for the options.
While analysis in banks has been controlled in a relatively focused and often centralized manner in the past, GenAI has also shown that data and analytics must be utilized much more to support each step of the value chain. Management must have more of an intensive exchange with colleagues in analytics, and coordinate their often differing priorities with each other.
No Easy Task
Not least, the speed of the transition has never been as high as it is now. This presents challenges, particularly to companies that move a little slower. The spread of AI also brings unique challenges regarding the skills of employees, as the extent of the spread is highly dependent on a bank’s pool of talent.
Banks that employ fewer AI experts must improve their capabilities through a mixture of training and recruitment – not an easy task.
Vast Potential
The McKinsey Global Institute estimates that GenAI could create a global added value of $2.6 billion to $4.4 billion every year.
Among the individual sectors, the technology offers one of the greatest opportunities for banking: an annual potential of $200 to $340 billion – above all through increased productivity. The greatest absolute profits are expected in corporate banking and in private banking ($56 and $54 billion respectively).
