Revolutionising Liquidity Risk Supervision: How Machine Learning is Driving Real-Time Crisis Prevention
Traditional liquidity risk measures like Basel III are too static to detect emerging threats in real time, as demonstrated by crises from 2008 to COVID-19. This blog presents the Bank of Tanzania’s machine learning-based Bank Liquidity Risk Supervision (BLRS) solution, which can retrain and predict liquidity risk classifications in under two minutes.
Smart Regulation: Enhancing compliance outcomes in the financial sector through native digitalisation of regulation
Financial regulation is caught in a vicious cycle where information gaps drive more complexity, which in turn makes compliance harder — a problem that native digitalisation can break. This blog traces the evolution from basic machine-readable regulation (MRR) to fully executable rules-as-code (RaC), examining the benefits, challenges, and cross-country experiments underway in New Zealand, France, the UK, and beyond.
