Machine Learning and IRB Capital Requirements: Advantages, Risks, and Recommendations
This paper examines the use of #machinelearning methods in the context of #banks' #capitalrequirements, specifically the internal Ratings Based (#irb) approach. The authors discuss the advantages and risks of using machine learning in this domain, and provide recommendations related to #risk parameter estimations, #regulatory capital, the trade‑off between performance and interpretability, international #banking competition, and #governance, #operationalrisk, and training.