Description: This is a brief report that summarizes recent changes in the prevalent medical loss ratio methodologies and also looks at some of the more recent experience of health insurers that filed medical loss ratio reports.

Description: This report outlines a framework for interpretable machine learning algorithms for detecting fraud in health insurance. It discusses the challenges of using black-box machine learning models in the insurance industry and proposes various interpretable methods to enhance transparency and understanding.