Fraud Detection and Analysis for Insurance Claim using Machine Learning

Abstract

Insurance Company working as commercial enterprise from last few years has been experiencing fraud cases for all type of
claims. Amount claimed by fraudulent is significantly huge that may causes serious problems, hence along with government, different
organization also working to detect and reduce such activities. Such frauds occurred in all areas of insurance claim with high severity such as insurance claimed towards auto sector is fraud that widely claimed and prominent type, which can be done by fake accident claim. So, we aim to develop a project that work on insurance claim data set to detect fraud and fake claims amount. The project implements machine learning algorithms to build model to label and classify claim. Also, to study comparative study of all machine learning algorithms used for classification using confusion matrix in term soft accuracy, precision, recall etc. For fraudulent transaction validation, machine learning model is built using PySpark Python Library.