A Review of Credit Card Fraud Detection Using Machine Learning Techniques

Big Data technologies concern several critical areas such as Healthcare, Finance, Manufacturing, Transport, and E-Commerce. Hence, they play an indispensable role in the financial sector, especially within the banking services which are impacted by the digitalization of services and the evolvement of e-commerce transactions. Therefore, the emergence of the credit card use and the increasing number of fraudsters have generated different issues that concern the banking sector. Unfortunately, these issues obstruct the performance of Fraud Control Systems (Fraud Detection Systems & Fraud Prevention Systems) and abuse the transparency of online payments. Thus, financial institutions aim to secure credit card transactions and allow their customers to use e-banking services safely and efficiently. To reach this goal, they try to develop more relevant fraud detection techniques that can identify more fraudulent transactions and decrease frauds. The purpose of this article is to define the fundamental aspects of fraud detection, the current systems of fraud detection, the issues and challenges of frauds related to the banking sector, and the existing solutions based on machine learning techniques.