Accelerating Gen AI Adoption in the Credit Business
Transformative technologies don’t come along very often, so when they do it pays to act quickly. When gen AI algorithms were launched in 2022, banks wasted little time exploring their potential in core commercial credit activities. But three years later, the results are mixed, with some institutions making good progress in putting the technology to work while others lag behind, a new study from McKinsey and the International Association of Credit Portfolio Managers (IACPM) shows.
Our Methodology
For the purposes of this article, McKinsey surveyed and interviewed decision-makers at 44 institutions globally in the second half of 2024. Our respondents included a roughly equal number of executives across megabanks, super-regionals, and core regionals. Megabanks comprised institutions with more than $1,000 billion in assets, super-regionals included institutions with $500 billion to $1,000 billion in assets, and core regionals were defined as having $100 billion to $500 billion in assets. We also connected with insurance companies/brokers and development banks.
Gen AI is now a priority for many banks
To gauge banks’ progress in adopting gen AI in the credit business, we interviewed and surveyed senior executives at 44 financial institutions globally. Across banks ranging in size from megaplayers to regionals, we asked about the factors affecting their adoption of gen AI, their most promising use cases, and their approaches to managing risks associated with the technology.
The responses were unequivocal on one point: Gen AI is starting to break through, with about half of senior leaders identifying it as a priority. Indeed, in key applications such as credit decisioning and pricing, rising numbers of institutions are rolling out one or more use cases. Moreover, credit applications often rank on a par or ahead of other applications, with executives seeing particular potential for gen AI in early-warning systems, credit memo drafting, and customer engagement activities.
Gen AI offers financial institutions three highly useful capabilities:
- Concision: the ability to summarize large volumes of data into digestible nuggets
- Content generation
- Customer engagement
Of the three, the largest number of institutions in our survey have made the most advances in concision, with the majority of institutions trying out gen AI applications in activities such as early-warning systems and credit decisioning.
Most institutions are testing credit use cases
Given a wide range of value creation opportunities, 52 percent of institutions have positioned gen AI adoption as a priority, our survey shows. That means senior leadership has prioritized developing gen AI use cases and backed that ambition through investment and hiring. Another 39 percent of institutions say they are interested in gen AI, but adoption is not yet a clear priority, and 9 percent admit that senior leaders are not actively engaged on the topic.
Why banks are taking a conservative approach
Many senior bankers, especially at regionals, are convinced that gen AI applications can create efficiencies, but there is a common gap between attitudes and implementation. Indeed, just 12 percent of North American survey respondents have deployed any use case at all.
At a McKinsey-hosted chief risk officer roundtable in 2023, we asked decision-makers what was holding them back on gen AI adoption. Sixty-seven percent highlighted shortages of gen AI capabilities, while 50 percent pointed to difficulties including defining uses cases and value at stake. A related point was that institutions putting an emphasis on early ROI from the technology were in fact more likely to give up on it, while others that pushed on through had started to see success.
Tackling challenges and building capabilities
Where banks are making progress is in laying the foundations for deeper gen AI adoption. Our survey shows, for example, that most institutions are in the process of attracting talent and establishing secure environments and processes.
Taking action: Five steps to accelerate the journey
While many of the challenges first identified in 2023 are still relevant to banks’ engagement with gen AI, there are signs at the margins that leading institutions are finding a way to balance risk and reward. Here we present five key steps in that process:
- Align with stakeholders
- Standardize data to streamline deployment
- Install modular solution architecture
- Pick low-hanging fruit
- Roll out agentic AI
FAQ
What is Gen AI?
Gen AI refers to the next generation of artificial intelligence algorithms that have the ability to learn, adapt, and make decisions autonomously.
How are banks using Gen AI in the credit business?
Banks are using Gen AI in activities such as credit decisioning, early-warning systems, credit memo drafting, and customer engagement to improve efficiency and effectiveness.
Conclusion
Banks have taken steps to accelerate adoption of gen AI in the credit business, but the results of our survey show that most remain on a journey. Leading banks are embracing a more strategic approach, ensuring they have put in place technology, talent, and operational building blocks to win the trust of stakeholders ahead of scaling. Many are also embracing agentic AI’s decision-making capabilities and are seeing positive results, not just in individual business lines but across the organization.
