Fraud detection

Health insurance fraud has become a serious problem in the healthcare industry, causing billions of losses to the country each year. We use time-series analysis and machine learning models powered by big data frameworks to achieve unprecedented effectiveness of fraud detection and prevention.

Our strategies briefly include:

• Time-series analysis to identify outliers or significant deviations from moving average for individual profiles.
• Machine learning models built on individual profiles.
• Time-series analysis, clustering or machine learning models to detect anomalies by comparison with a background population.
• Real-time fraud detection and prevention powered by big data techniques.