Early Warning Systems (EWS) using Real-Time Interbank Data

The ability to detect nascent signs of financial stress before a crisis erupts is the ultimate goal of macro-prudential surveillance. This course focuses on building and deploying **Early Warning Systems (EWS)** that leverage high-frequency, real-time data from interbank markets and payment systems to provide a proactive alert mechanism for financial instability. Participants will learn how to process and analyze data on interbank lending rates, payment flows, collateral usage, and funding liquidity to identify anomalies and indicators of stress (e.g., fragmentation, flight to quality). The program emphasizes the use of advanced econometric and Machine Learning techniques to build robust EWS models, ensuring they achieve a critical balance between sensitivity and managing false positives, thereby enabling timely and effective policy intervention.