The client handles almost 200,000 claimants currently receiving medical compensation for services rendered by tens of thousands of medical providers and wanted to improve the efficiency of their fraud analysts by using analytics to detect high-risk cases for further investigation.
Elder Research partnered with the client to develop a solution that generates fraud leads based on risk indicators and anomaly detection. The team developed statistical models to create risk scores that brought to light unusual changes in billing behaviors, abnormal patterns of services provided compared to peers, and other factors. These provided analysts data-driven leads with a high probability for fraud.
The model’s results are delivered in an easy-to-use visualization tool called RADR which presents color coded risk scores ranging from 0 (lowest risk) to 100 (highest risk). RADR enables analysts to explore data aggregated by service providers, claimants, and services, as well as drill down to transaction details.
The client’s fraud analysts use the RADR analytics platform to efficiently analyze unusual and highly suspicious behavior to prioritize investigative workload and discover new fraud schemes. Forensic analysis that took hours can now be completed in minutes making the most efficient use of limited and valuable resources.