The finance function is undergoing a seismic shift from descriptive to predictive and prescriptive analytics. This course bridges the gap between financial expertise and artificial intelligence, equipping professionals with the knowledge to lead AI initiatives without becoming programmers. You will explore how machine learning models detect anomalous transactions in real-time, far surpassing traditional rule-based systems. The curriculum covers AI-driven cash flow forecasting, intelligent expense categorization, and automated reconciliation processes. A significant focus is placed on ethical AI in finance, including bias detection in credit models and explainability for regulatory compliance (e.g., Basel, IFRS 9). Through case studies from banking, insurance, and corporate finance, you will evaluate ROI for AI projects and learn to communicate requirements to data science teams. You will also work with no-code AI tools to build a basic predictive model for accounts receivable. By the end, you will be able to distinguish realistic AI opportunities from hype, manage vendor selection, and implement governance frameworks that ensure auditability.
