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Credit Card Fraud Detection using Various Machine Learning Algorithms

Abstract: Detecting credit card fraud is probably the most typical problem in the modern day. This is due to a growth in digital shopping as well as electronic-commerce platforms. As digitalization gains popularity in this current world, people are choosing online payment methods for time and transportation ease, among other reasons.Credit card fraud has increased significantly as a result of the tremendous growth in e-commerce use. Fraudsters attempt to exploit the card and the transparency of online payments. Credit card fraud often occurs whenever the card is taken/stolen or when the details of the card are known. As a result, countering fraudsters' activities has become critical. In the modern world, people are facing loads of credit card issues. There are various techniques and Machine Learning Algorithms to overcome this problem such as using Logistic Regression, XgBoost, Naïve Bayesian, K- Nearest Neighbor (KNN), Decision Tree, Random Forest, Support Vector Machine (SVM) etc.The central goal is to safeguard electronic payments, allowing people to use e-banking safely and easily.