Combining Supervised and Unsupervised Machine Learning Methods for Improving Credit Card Fraud Detection

Abstract

In recent years, credit cards have become the most popular mode of payment for business, insurance, and banking, especially with the growth of the e-commerce industry. The increased number of online transactions has made it simpler for fraudsters to obtain and exploit credit card information that has been stolen. Unfortunately, fraud problems are a widespread issue that affects many people and organizations around the world, which will heavily damage and affect the reputation of companies among customers. Because of these frauds, traditional fraud detection systems are struggling to keep up with the speed of the technological development of cybercriminals.