Analysis of Credit Card Fraud Detection Using Machine Learning Algorithms

Abstract

For the past decade of year’s credit card holders are facing a problem that the card had been swiped and cash has been withdrawn in an ATM (Automatic Teller Machine) or it has been swiped in a shopping mall by purchasing a product as creating a fake credit card. These transactions are considered as illegal activity, it is also one of the cybercrime theft activities. Credit card fraud detection has been increasing highly in the world. Fake credit cards can be tackled by applying data science along various machine learning algorithms. This research work focus on analysis of various credit card fraud transaction using machine learning algorithms. Also, this research focuses on detecting the fake credit cards by approaching Artificial Intelligence (AI), Data mining and Big data analytics etc. by using machine learning algorithms. Machine learning algorithms are applied by training the dataset which are collected from the fake credit dataset and original credit card dataset. Computer operations are handled by the data as data’s are ruling the world. Predicted card details are stored on the server of the banker. From the server information has been passed to the cybercrime in order to catch the culprit. Different kinds of machine learning algorithms that has been used for credit card fraud detection has been studied on which it gives the more precision.