Your question is Model Robustness and Calibration. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How do you evaluate the robustness and calibration of a predictive risk model before deploying it into a production environment?
Explain the statistical validation plan you would use, including out-of-sample evaluation, calibration assessment, robustness and stress testing, subgroup analysis, uncertainty quantification, and deployment monitoring. State the metrics, resampling or hypothesis-testing methods, decision criteria, and failure conditions you would apply. Address how your approach changes for rare outcomes, temporal drift, class imbalance, and models that influence consequential decisions.