Robust Credit Scoring Models: Handling Outliers and Missing Data
Building robust credit scoring models requires a pragmatic approach to data preprocessing. Ahmad Wael explains why lazy imputation kills model performance and how to correctly use the IQR method for outliers and MAR/MCAR strategies for missing values in Python, ensuring your risk models generalize effectively without data leakage.