What Regulators Are Finding in Banks' AI Risk Management
In a letter sent on April 30 to every institution it supervises, the Australian Prudential Regulation Authority reported that assurance over artificial intelligence at the large banks, insurers and superannuation trustees it had reviewed was relying on methods designed for a different kind of system. Assurance providers were leaning on point-in-time, sample-based testing, which APRA judged poorly suited to probabilistic models that "learn, adapt and degrade over time." Many internal audit and risk functions, it added, lacked the specialist skills and tools to assess AI. Its summary was plain: "assurance practices are not keeping pace with the scale, speed and complexity of AI."


