Dynamic Credit Risk Assessment Model

Develop a sophisticated credit risk assessment framework using scikit-learn that can probabilistically evaluate loan applicant creditworthiness. The model should incorporate multiple data sources including financial history, macroeconomic indicators, and machine learning classifiers. Implement cross-validation techniques, generate interpretable risk scoring, and create a modular pipeline that can be easily updated with new feature engineering approaches.