Indian Journal of Science and Technology

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Objectives: Healthcare fraud costs the country tens of billions of dollars a year. Methods: Fraudulent behaviors of healthcare providers and patients have become a serious burden to insurance systems by bringing unnecessary costs. Insurance companies thus developed methods to identify fraud. Results: In this paper a methodology offered based on data mining approach to discover fraud in healthcare insurance. Applications: To test and evaluate model real-world data set related to healthcare insurance in Iran has been used. Investment result of operation model on this data set indicates proper performance of it.

Keywords

Anomaly Detection, Data Mining, Healthcare Fraud, Outlier Detection, Unsupervised Method.
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