Abstract
<p indent=0mm>Medical insurance fraud causes serious economic losses, which has a great impact on the safety and stability of the medical insurance system. However, existing work does not support the joint analysis and exploration of various types of fraud. Based on the medical insurance data related to multi-dimensional time series, a visual analytics approach for anti-fraud in medical insurance is proposed. It can perform spatio-temporal filtering of medical insurance data, locate fraud quickly, and discover hidden frauds by performing the correlation analysis between different types and different subjects of fraud. We design and develop MedicareVis, a visual analysis system for medical insurance anti-fraud. We demonstrate the usefulness and effectiveness of our approach in helping detect the association of fraud through a case study on real-world medical insurance data and interviews with domain experts.
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