Other parts of this series:
Spring is a time when most people, bankers included, take a fresh look at the challenges they face and tackle them with renewed vigor. Commercial banking should be on this year’s spring-cleaning list. While it is often the bank’s largest revenue generator, its processes continue to be highly manual, constraining the potential for profit growth. Our Commercial Banking Top Trends for 2024 report highlights the most critical issues, and it’s no surprise that generative AI features in all of them.
To dive deeper into the potential of generative AI across commercial banking, we are working closely with our top commercial banking leaders in North America, Europe and Asia Pacific to put together a three-part series that will help generate ideas for our clients as they start and scale their generative AI journey. While many banks continue to struggle with when and where to begin, we are well underway with a handful of clients to drive the art of the possible to reality with generative AI. We wanted to reflect and provide perspective on the lessons we’ve learned so far.
Generative AI has sparked a great deal of excitement. That’s obviously because of its potential to transform so many different aspects of our life and work, in ways that are difficult to predict beyond the next few years. But it’s also because the technology is evolving so rapidly that most people struggle to keep up.
We believe generative AI will prove to be a breakthrough for commercial banks—and their customers, large and small alike. Accenture research has confirmed that banking is one of the industries likely to be most affected by the technology: 41% of the time spent by US bank employees has a high potential to be impacted by automation, and 34% by augmentation. We analyzed specific banking roles and found that few, if any, will remain untouched (Figure 1). The sales and advisory function—which accounts for 39% of all bank employees—is expected to benefit most.
We see a fundamental difference in how commercial banks are typically approaching generative AI. On one end of the spectrum, ‘Experimenters’ are focusing on piloting, proving and ultimately scaling use cases that deliver specific benefits to customers, employees or regulators. On the other end, ‘Reinventors’ are looking at entire experiences and value chains and making far-reaching changes to their operating model while introducing a combination of technologies, including generative AI, to systematically create competitive advantage through human and machine collaboration.
There is no one-size-fits-all approach for commercial banks, and many find themselves somewhere between these two extremes. One of our more innovative clients is using a combination of generative AI and human agents to reach customers with personalized, insight-driven offers at a much lower cost to serve and acquire than its competitors. At the same time, it is using generative AI to automate and augment operations to reduce ‘time to yes’ and ‘time to cash’. No commercial bank can afford to downplay the transformative potential of generative AI for its organization and its customers. The challenge is not whether to explore this innovative technology, but where to start and how to scale rapidly.
We would like to thank our colleagues, Julie Zhu and Gustavo Pintado for their contributions to this post. In our next post, we will share what leading commercial banks are doing to generate immediate value. In the meantime, if you would like to know more about this topic, we’re sure you’ll find our two recent reports useful: Commercial Banking Top Trends for 2024 and The Age of AI–Banking’s New Reality. Or you could simply contact us—we’d love to chat with you about your bank’s journey to generative AI.
In addition, if you’re planning to attend this year’s nSight2024 in Charlotte, please make sure to connect with our Accenture experts. We’ll have a booth and will moderate multiple sessions, including two on AI and commercial banking. Learn more about our presence as the exclusive diamond sponsors of nSight.
