<span lang="EN-US">Now days, the analysis of behavior cardholders is one important fields in electronic payment. This kind helps to extract behavioral and transaction profile patterns that can help financial systems better protect their customers. In this paper, we propose an intelligent machine learning (ML) system for rules generation. It based on a hybrid approach using rough set theor...

The increase in the volume and velocity of credit card transactions causes class imbalance concept deviation problems data sets where fraud is detected. These make it very difficult for traditional approaches to produce robust detection models. In this study, a different perspective has been developed problem novel approach named Fraud Detection with Image Conversion (FDIC) proposed. FDIC handl...

Available online 18 August 2010

Credit card fraud detection based on machine learning has recently attracted considerable interest from the research community. One of the most important tasks in this area is the ability of classifiers to handle the imbalance in credit card data. In this scenario, classifiers tend to yield poor accuracy on the fraud class (minority class) despite realizing high overall accuracy. This is due to...