Fraud Claims Detection in Insurance Using Machine Learning

Abstract

Insurance fraud is an illegal activity that is deliberately done for financial gain. In the present era, this is the prime severe problem encountered by various insurance companies all over the globe. In most cases, some shallow or deep holes in process of fraudulent claims investigation have been identified as a major cause. Due to this reason, the need of using computer techniques to curb fraud activities grew as a motivation, providing not only a reliable and robust environment for customers but also reducing fraud claims to a large scale. We presented our research by automating the assessment process of insurance claims through various data techniques, where identification of false claims will be automatized by utilizing Data Analytics and Machine Learning methods. Moreover, the system has the ability to potentially develop heuristics around fraud indicators. Therefore, this model creates a positive impact on the whole insurance industry with increased company credibility as well as customer satisfaction.