AI for Real-Time Liquidity Forecasting and Anomaly Detection

Accurate, real-time liquidity management is paramount for central banks and financial institutions, particularly in high-volume payment systems like RTGS. This course focuses on leveraging Artificial Intelligence (AI) and Machine Learning (ML) to transform traditional, often backward-looking, liquidity forecasting and risk monitoring. Participants will learn how to build and deploy advanced models, such as LSTMs and Deep Neural Networks, to predict intraday liquidity needs with unprecedented accuracy, moving beyond simple time-series analysis. A significant component covers using unsupervised learning techniques, like Isolation Forest and Autoencoders, to detect subtle, fast-moving anomalies and potential market manipulation or operational failures in payment flows in real-time, thereby enabling proactive intervention and mitigating systemic risk.