Complex Medical Billing Error Detection System

Design a sophisticated medical billing error detection framework using pandas and machine learning that can automatically identify potential billing inconsistencies, fraudulent claims, and coding errors across large healthcare datasets. Implement advanced feature engineering techniques, develop unsupervised and supervised anomaly detection models, and create a comprehensive reporting system that provides actionable insights for billing compliance teams. The system must handle multiple insurance coding standards and support dynamic model retraining.