A Survey of Credit Card Fraud Detection Techniques: Data and Technique Oriented Perspective

Credit card plays a very important rule in today's economy. It becomes an unavoidable part of household, business and global activities. Although using credit cards provides enormous benefits when used carefully and responsibly,significant credit and financial damagesmay be causedby fraudulent activities. Many techniques have been proposed to confront thegrowthin credit card fraud. However, all of these techniques have the same goal of avoiding the credit card fraud; each one has its own drawbacks, advantages and characteristics. In this paper, after investigating difficultiesof credit card fraud detection, we seek to review the state of the art in credit card fraud detection techniques, datasets and evaluation criteria.The advantages and disadvantages of fraud detection methods are enumerated and compared.Furthermore, a classification of mentioned techniques into two main fraud detection approaches, namely, misuses (supervised) and anomaly detection (unsupervised) is presented. Again, a classification of techniques is proposed based on capability to process the numerical and categorical datasets. Different datasets used in literatureare then described and grouped into real and synthesized data and the effective and common attributesare extracted for further usage.Moreover, evaluation employed criterions in literature are collected and discussed.Consequently, open issues for credit card fraud detection are explained as guidelinesfor