Credit Card Fraud Detection: Analyzing the Performance of Four Machine Learning Models

Abstract

In the era where most of our transactions whether it is for shopping, electricity bills, insurance payments, school and college fees are paid using plastic money through wireless and various online modes. Increase in both online transactions and ecommerce platforms has given rise to many online frauds these days and also security threats. To detect these fraudulent activities, we created a machine learning model. In this research we modeled a dataset using Machine Learning Algorithms. It is proposed to predict fraudulent transactions made by users. It is a real-life example of a binary Classification problem. This research emphasizes on analyzing and pre-processing the dataset and implementing various python libraries, and used concepts like Exploratory Data Analysis, Data Modeling, Feature Extraction etc. and implemented a fraud detection process using the four algorithms.