Bank of England Governor Andrew Bailey has urged greater use of artificial intelligence in financial regulation, arguing that advanced data tools could help regulators “find the smoking gun” in cases of misconduct or systemic risk.
AI as a Tool for Vigilance
Speaking on the future of oversight, Bailey stressed that AI and data science should not be limited to supporting innovation in banking but integrated into regulatory supervision. By analyzing vast volumes of transactions, communications, and institutional data, AI systems could detect patterns of fraud, money laundering, or excessive risk-taking more effectively than traditional methods.
“Financial stability depends not only on trust, but on vigilance,” Bailey noted. “AI gives us a sharper lens to spot where that trust may be undermined.”
Global Regulatory Momentum
Bailey’s remarks align with global regulatory experiments. In the United States, the SEC and Federal Reserve have piloted AI systems to monitor trading behavior and market anomalies. Meanwhile, regulators across Europe and Asia are testing machine learning tools to track cross-border financial flows and compliance risks.
Challenges of AI-Driven Oversight
Experts caution that AI-driven regulation is not without risks. Concerns include algorithmic bias, data privacy, and overreliance on opaque systems. Analysts emphasize that human judgment must remain central, with AI acting as an aid rather than a replacement for regulatory expertise.
Keeping Pace with Industry Adoption
The call reflects a broader trend: as banks and financial institutions adopt AI to optimize trading and operations, regulators face pressure to leverage the same tools. The challenge will be ensuring AI strengthens transparency, accountability, and stability rather than complicating oversight.
