Fraud detection in credit card transaction using machine learning techniques

Credit card transactions are nowadays more and more frequent. Using your credit card to buy online, as a mobile wallet or for a simple payment to a merchant has become a daily action for most cardholders. The virtual world and technological development that we know, makes banking transactions become digitized. As a result, a flow of millions of online transactions is subject to various types of fraud. Traditional techniques for detecting fraud cannot detect sophisticated fraudulent techniques. To be limited to an analysis of the cardholder behavior’s, or to static rules of risk management of the frauds, had never stopped the fraudulent to commit their crimes. However, machine-learning techniques have been able to meet this need, as we found in literature [1]. In this paper, we will present a comparative study of some machine learning techniques, which gave the best results, according to our state of art [1] but applied to the same set of data. The objective of this study is to choose the best credit card fraud detection techniques to implement in our future work.