Insurance Fraud Detection Using Machine Learning

Abstract

Every year, the insurance industry losing billions of dollars due to fraud. The act when a person makes fake insurance claims to gain benefits, compensation & other advantages to which they are not entitled is known as Insurance Fraud. Nowadays insurance fraud detection is becoming a tedious problem for insurance companies to deal with as they need more investment and workforces to keep track of every transaction. In this paper, we are focusing on the major issue faced by insurance companies that is insurance fraud. we use the machine learning technique to detect insurance fraud based on the transactional data given by the insurance company. We build predictive models and compare their performance by calculation of confusion matrix then it is evaluated on various performance measuring parameters like accuracy, precision, recall, F1 score, and on AUC curve. SVM (Support Vector Machine) and XG Boost (Extreme Gradient Boosting) are the machine learning algorithms used. After model evaluation, we select the best model for prediction.