This fourth edition of our FAQs focuses on emerging techniques to explain complex models and builds on prior FAQs that covered the use of AI in financial services and the importance of model transparency and explainability in the context of machine learning credit underwriting models.

This third edition of our FAQs considers the technological, market, and policy implications of using federated machine learning to improve risk identification across anti-financial crime disciplines, including in customer onboarding where it may facilitate more accurate and inclusive customer due diligence.

This second edition of our FAQs considers more deeply issues and debates about model transparency, explainability, and the implications of using machine learning for credit underwriting.

This first edition of our FAQs addresses a range of introductory questions about AI and machine learning.