KPMG Says the Old Rules of Model Risk Management Are Starting to Break Down in the AI Era
For years, model risk management inside financial institutions followed a fairly predictable rhythm. Models were reviewed periodically. Validators examined assumptions, tested outcomes, checked documentation, and challenged methodologies that were generally understandable to humans. The systems themselves, while complex at times, were still built on structures that could usually be traced, interpreted, and explained.
