A Survey of Credit Card Fraud Detection Techniques: Data and Technique Oriented Perspective
SamanehSorournejad, Zahra Zojaji, Reza Ebrahimi Atani, Amir Hassan, Monadjemi

TL;DR
This survey reviews various credit card fraud detection techniques, data sets, and evaluation criteria, categorizing methods into supervised and unsupervised approaches, and discusses their advantages, disadvantages, and open issues.
Contribution
It provides a comprehensive classification and comparison of fraud detection methods, data sets, and evaluation metrics, highlighting challenges and open issues for future research.
Findings
Supervised methods excel in known fraud patterns but struggle with new types.
Unsupervised methods are effective for detecting novel frauds but may have higher false positives.
Various data sets and evaluation criteria are used, affecting method performance comparison.
Abstract
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 damages may be caused by fraudulent activities. Many techniques have been proposed to confront the growth in 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 difficulties of credit card fraud detection, we seek to review the state of the art in credit card fraud detection techniques, data sets 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…
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Taxonomy
TopicsImbalanced Data Classification Techniques · Financial Distress and Bankruptcy Prediction · Advanced Steganography and Watermarking Techniques
