Credit Card Fraud Detection Challenges and Solutions: A Review

Authors

  • sumaya saad Sulaiman Computer Science Department, Collage of Science, Al-Mustansiriya University, Baghdad, Iraq / Computer Science Department, Collage of Science, University of Baghdad, Baghdad, Iraq https://orcid.org/0000-0003-1903-940X
  • Ibraheem Nadher Faculty of Basic Education, AL- Mustansiriya University, Baghdad, Iraq https://orcid.org/0000-0002-0986-5487
  • Sarab M. Hameed Computer Science Department, Collage of Science, University of Baghdad, Baghdad, Iraq

DOI:

https://doi.org/10.24996/ijs.2024.65.4.42

Keywords:

Credit card fraud detection, fraudster, class imbalanced, concept drift, verification latency

Abstract

     Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them.  This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, concept drift, and verification latency problems using machine learning and deep learning. It also provides valuable information for academic and industrial researchers and opens new avenues for research aimed at developing robust fraud detection systems.

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Section

Computer Science

How to Cite

Credit Card Fraud Detection Challenges and Solutions: A Review. (n.d.). Iraqi Journal of Science, 65(4). https://doi.org/10.24996/ijs.2024.65.4.42

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