Detection of Vehicle Insurance Claim Fraud wi...

Detection of Vehicle Insurance Claim Fraud with a Machine Learning Approach

Author Name : Olin Dilip Dsouza, Shivam Singh, Akshath Kamath, B Krishna Karthik, Ghanta Sai Gautham, Naga Venkata Sriram Gadde, Makuluri Anirudh Raghavendra

ABSTRACT :  Insurance has several issues for the company and the policyholder. The amount claimed by fraud is significantly large. That may cause serious problems. Hence, along with government organizations, detection has become crucial to minimize auto insurance fraud. Although predictive models for the detection of insurance fraud are in active use in practice, there are relatively few documented studies on the use of machine learning approaches to detect insurance fraud. Different organizations are also working to detect and reduce such fraud occurring in all areas of insurance claims with high severity, such as insurance claims for autos. This is a widely claimed and prominent type of fraud that can be caused by faked accidents. The current detection system is costly and inefficient. In this research, we aim to study fraud detection program. Towards this goal we use two different at sets. Our ultimate goal is to use machine learning algorithms to build a model to classify claim.