Financial Services May Be 'Overly Cautious' in Embracing Generative AI Technologies

Despite being a highly regulated field, the financial services industry is brimming with opportunities for generative AI applications.

During a panel discussion at VB Transform, Shri Santhanam, Executive Vice President and General Manager of Software, Platforms, and AI at Experian North America, highlighted that while many perceive the industry as slow to adopt new technologies, it is actually undergoing significant digital transformation.

"Generative AI is profoundly impacting various industries—financial services included," Santhanam stated. "AI can enhance everything from management writing to productivity, with the most significant transformation being improved financial inclusion."

Santhanam, along with fellow panelist Christian Mitchell, Chief Digital and Information Officer at Northwestern Mutual, discussed current generative AI applications in the financial sector and how regulated industries navigate potential challenges.

Mitchell explained that Northwestern Mutual utilizes generative AI to enhance client choice and conduct lifecycle analysis. AI assists clients in understanding available financial and insurance options while providing insights into retirement planning.

Both Santhanam and Mitchell warned against deploying AI indiscriminately, as it may inadvertently expose sensitive information. However, they noted that companies can be excessively cautious as well.

“It’s easy to get trapped in proof of concept land, so we invested early in scalable production and are selective about which projects move to market. We encourage teams to generate AI ideas, but they must meet specific criteria before launch,” Santhanam emphasized.

This criteria includes strategic alignment, customization beyond off-the-shelf solutions, and compliance with regulatory standards. Santhanam shared that an early experiment at Experian focused on leveraging over 60 years' worth of data, which posed a significant challenge for engineers.

The anticipated benefits of AI in finance encompass increased efficiency, cost savings, improved risk management, personalized services, and enhanced decision-making. However, many current use cases center on data analysis and customer service—areas already well-integrated within financial organizations. Research indicates that some aspects of finance remain intricate, often necessitating human oversight.