Financial services firms face growing AI governance scrutiny

By Milan Rojan

A recent report has highlighted the need for financial services firms to strengthen AI governance as the technology becomes increasingly embedded in retail banking, payments, lending, insurance and investment services.

The review has examined how AI could reshape retail financial services through 2030 and beyond, focusing on the changing role of consumers, firms and markets as systems become more autonomous. Rather than proposing a separate AI rulebook, it has highlighted how existing regulatory and governance frameworks may need to adapt as AI adoption increases.

AI use has already moved beyond basic assistance, with consumers increasingly considering systems that can make or execute financial decisions on their behalf. The review’s research has found that one in five UK adults would be open to AI making financial decisions for them, particularly in areas such as debt advice, pensions and investments.

The findings have also highlighted a gap between consumer trust and awareness of the risks involved. Around 26% of consumers have said they trust general-purpose AI tools such as ChatGPT, Claude or Gemini for financial advice, despite limited awareness that formal routes to recourse may not apply when such tools provide incorrect guidance.

For financial institutions, existing frameworks including the Consumer Duty, Senior Managers and Certification Regime and operational resilience requirements have remained relevant as AI has become more deeply integrated into business processes.

Joe Norburn, CEO of TCC Group and Recordsure, has highlighted the importance of evidence and accountability as AI systems have become more embedded in customer journeys. Firms have increasingly needed to demonstrate where AI has been deployed, who remains responsible for decisions and how customer outcomes are being monitored.

The review has also identified growing risks from autonomous systems, including opaque decision-making, algorithmic bias, AI-enabled fraud and operational vulnerabilities. As adoption has accelerated, firms have faced pressure to strengthen oversight, data quality and accountability while continuing to capture AI’s potential efficiency and innovation benefits.