Underwriting Model Validation overview

Validates the statistical and machine-learning models used in insurance underwriting -- back-testing loss-ratio predictions against actual experience, evaluating model discrimination and calibration metrics (AUC, Brier score), running regulatory-mandated adverse-impact analyses across protected classes, reviewing feature-importance stability for concept drift, and comparing challenger models against incumbent production models. Produces model validation reports, regulatory compliance documentation, and champion-challenger comparison summaries. Excludes model development and retraining.