Fraud Detection and Analysis for Insurance Claim using   Machine Learning

Prof. Pradeep Patil; Vishwajeet Mandal; Prathamesh Mahajan; Sujal Narlawar; Sanket Patil

doi:10.65521/ijasret.v9i4.1735

Authors

Prof. Pradeep Patil Professor, Computer Department, Sandip Institute of technology and research Centre, Nashik, India
Vishwajeet Mandal Student, Computer Department, Sandip Institute of technology and research Centre, Nashik, India
Prathamesh Mahajan Student, Computer Department, Sandip Institute of technology and research Centre, Nashik, India
Sujal Narlawar Student, Computer Department, Sandip Institute of technology and research Centre, Nashik, India
Sanket Patil Student, Computer Department, Sandip Institute of technology and research Centre, Nashik, India

DOI:

https://doi.org/10.65521/ijasret.v9i4.1735

Keywords:

Insurance fraud detection Machine learning Predictive modeling Supervised learning Unsupervised learning Decision trees Random forest Logistic regression Fraud prevention Support vector machines (SVM) Claim pattern analysis Model evaluation metrics Data driven fraud detection Insurance claim patterns Financial losses reduction

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.

Fraud Detection and Analysis for Insurance Claim using Machine Learning

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