Machine Learning Credit Risk Predictive Model Pipeline

Develop an end-to-end machine learning pipeline for credit risk prediction that integrates historical financial data, real-time economic indicators, and multiple feature engineering techniques. The model must support dynamic retraining, handle feature drift detection, provide interpretability scores, and generate probabilistic risk assessments with 95% confidence intervals. Include comprehensive model versioning and A/B testing infrastructure.