Abstract

Fraudulent activities in insurance claims have become a significant challenge for the insurance industry, leading to substantial financial losses annually. This project, titled "Fraud Detection and Analysis for Insurance Claim using Machine Learning" aims to develop a robust and an efficient system to identify and analyze fraudulent claims. The system leverages machine learning techniques to analyze patterns, anomalies, and inconsistencies in claim data, enabling early detection of potentially fraudulent activities.