Machine Learning Credit Risk Predictive Framework

Develop a sophisticated machine learning pipeline for credit risk prediction that integrates multiple data sources, handles feature engineering dynamically, and provides explainable AI insights. The framework must support multiple model architectures, perform automated hyperparameter tuning, and generate probabilistic risk assessments with confidence intervals. Implement robust cross-validation techniques and include mechanisms for detecting and mitigating potential bias in risk calculations.