Fraud, waste, and abuse (FWA) continue to pose significant financial and operational challenges to America’s healthcare system, costing billions of dollars each year. Traditional fraud detection methods, which are largely reactive and manual, have proven inadequate against increasingly sophisticated schemes. This whitepaper presents a transformative approach, leveraging Explainable AI (XAI) and machine learning to proactively identify and prevent fraud in Medicare and Medicaid programs.
The proposed framework integrates advanced anomaly detection, supervised models, and graph analytics to surface fraudulent activities in real time. Explainable AI ensures transparency and trust, providing clear, human-readable rationales for every flagged case. Human-AI collaboration is central to the solution, with intuitive dashboards and visualizations enabling stakeholders—including non-technical users—to quickly interpret insights and take targeted action. Ethical governance and compliance with regulations like HIPAA are built into the system, ensuring fairness and privacy.
By adopting this proactive, explainable AI-powered approach, healthcare organizations can strengthen program integrity, reduce improper payments, and streamline investigations. The framework not only enhances fraud prevention but also supports broader improvements in healthcare policy and operations.
Download the full whitepaper to discover how Persistent Systems’ innovative solution can help your organization stay ahead of emerging threats and safeguard healthcare for the future.
