Assessing the Cost of Monotonicity in Credit Risk Modeling with Gradient Boosting

This research paper explores the performance implications of incorporating monotonicity constraints in gradient boosting models, specifically for credit risk probability of default (PD) estimation. The study provides valuable insights into the trade-offs between model accuracy and constraint satisfaction, a key consideration for regulatory compliance in finance.