Cashing in on AI: More than a dozen reasons why financial services is already seeing ROI on gen AI
Zac Maufe
Global Head of Regulated Industries, Google Cloud
Many financial services firms are already putting gen AI into production — and seeing real returns across their operations.
Financial services has always been a data-rich, insight-poor industry, but gen AI has the potential to unlock this data and deliver new experiences in ways banking and investing executives could barely dream of. We’re already seeing endeavors toward greater personalization, fraud prevention, risk mitigation, servicing, and other data-intensive functions.
We already know this to be true thanks to Google Cloud’s recent survey of hundreds of business leaders in the financial services industry. We have collected the responses and trends into a new report, The ROI of Gen AI for Financial Services.
You can read all the findings in the full report, but we wanted to share some highlights with you here, as well as the perspective of two industry leaders: Christoph Rabenseifner, managing director for Technology, Data and Innovation at Deutsche Bank, and Luis Uguina, chief digital officer, Macquarie Bank.
What we heard is that improving customer experience, boosting productivity, and enhancing security, particularly the ability to identify threats and reduce time to resolution, are all top of mind.
1. 63% have already moved gen AI use cases into production
Not only is the financial services industry embracing gen AI, but as our survey shows, it’s having a strong impact on business outcomes. However, the pace of adoption varies, with a distinct pattern emerging in the industry.
While 63% of financial services respondents have already moved gen AI use cases into production, 35% are still evaluating or testing gen AI use cases.1
Given that we are only a full year into the gen AI boom, the adoption rate is pretty impressive. However, the considerable adoption rate may be attributed to a focus on internal use cases that pose lower risks than external, customer-facing ones.
These are quick wins, but as Christoph Rabenseifner points out, “It’s tremendously hard to put something into production in a complex corporate technology environment, especially in highly regulated industries like the financial industry.”
Focusing on incorporating gen AI into internal processes first is one way to make fast progress. Luis Uguina, chief digital officer, Macquarie Bank sees the need for a measured approach: “We operate in a highly regulated environment, so while innovation is our north star, we always take small and considered steps with gen AI to enhance our internal processes and to deliver better experiences to customers.”
2. 90% of those running gen AI in production report revenue gains of 6% or more
Early adoption is paying off. At the same time, the success of those invested in gen AI serves as a warning for organizations not yet embracing the technology, as they may be missing out on a significant revenue opportunity. Ultimately, those surveyed are finding gen AI is delivering on its promise of driving growth, with 9 out of 10 firms running gen AI in production seeing revenue gains of 6% or more.2
From customer service to product innovation, financial services organizations are already using gen AI in production across a range of use cases to deliver financial returns and increase productivity.
“It’s no surprise that organizations are seeing these revenue gains. In the long term, I expect even greater returns as the industry explores use cases that really change business models,” Rabenseifner said.
3. 50% who reported productivity improvements indicated employee productivity has at least doubled
Financial institutions report significant improvements when asked about the ability of gen AI to increase business and IT productivity to drive innovation and transformation — indeed half are seeing productivity nearly double.3 This suggests that employees, recognizing gen AI tools as useful “work BFFs,” are driving strong demand and rapid adoption.
“With gen AI, we can automate document classification or information extraction to sort information or check for fraud, and enable our teams to be even more productive and efficient,” said Uguina.
4. 61% of respondents using gen AI in production saw meaningful improvements in security
The evolving threat landscape is becoming more complex, with bad actors using gen AI to create new attack vectors, conduct fraud, and exploit vulnerabilities in banking and payment systems. This trend is prompting a significant shift in the industry, as many financial services organizations are turning to gen AI to strengthen their security defenses — more than 3 in 5 we surveyed said they are seeing measurable improvements in their cybersecurity posture.4
Uguina emphasized the importance of integrating gen AI into fraud and scam operations.
“Fraud and anomaly detection require you to crunch a massive amount of data in real time to establish a relationship between data points that may not be obviously connected," he said. "We know that the bad actors are also learning to use gen AI, so we continue to find ways to apply it to safeguard us and our customers.”
Realizing gen AI to its fullest will require a strategic approach, to ensure seamless integration into how people work, and navigate the complex regulatory landscape. Moving forward, the message is clear: the time to innovate with gen AI is now.
1Total Market - Financial Services (global): n=340
2Financial services organizations currently leveraging gen AI in production and reporting increased revenue: n=108
3Organizations currently leveraging gen AI in production and reporting productivity improvements: n=152
4Organizations currently leveraging gen AI in production and reporting security improvements: n=213
