Insurance fraud detection: Pre-emptive analysis and prevention

Abstract

Insurance companies have been facing the problem of false insurance claims, costing resources and money in detecting fraudulent claims among the many true ones. Many times, fraudulent claims are mistaken for genuine claims, and genuine ones mistaken for fraudulent claims. This paper aims to develop a Machine Learning algorithm to detect fraudulent claims and distinguish them with genuine claims. This project also aims to compare other algorithms and see which one is the most effective to deal with this growing problem that the insurance industry is facing.