Explainable Artificial Intelligence in Risk Management: A Framework
Silvio Andrae · Transformations in banking, finance and regulation · 2024
It is easier than ever to run modern machine learning (ML) models. However, developing and implementing systems that support real-world risk management applications in a bank is a significant challenge. It is partly because ML models are not transparent and explainable. The framework presented here covers the leading eXplainable AI (XAI) methods. Practical challenges in implementing these methods are discussed.