Capital One, one of the largest US banks, has used artificial intelligence to reduce quality errors in audit risk and compliance by 85%, according to MIT Sloan Management Review. The bank’s intelligent assistant, built using open-weight models and advanced analytics, has also saved 5,000 audit hours across 30 auditors in a few months, with one task cut from five hours to three minutes. AI is also used for fraud reduction, software development, and customer service, including generative AI to help agents answer customer queries more quickly and accurately. Several hundred agents now use AI-powered call summarisation, which has improved productivity and customer experience.
Capital One’s leaders say the bank’s approach to AI is focused on enterprise-wide capabilities, not just individual productivity. Training is prioritised to ensure staff can use new tools effectively. The bank’s chief enterprise AI officer, Prem Natarajan, argues that transformation with AI cannot be measured by short-term ROI, but by long-term customer satisfaction and operational improvement.
For regulated-industry leaders, the Capital One example shows the scale of operational gains possible from AI in core risk and compliance functions. The bank’s focus on training and enterprise adoption may offer a model for other financial institutions and insurers seeking to improve quality and efficiency at scale.
