Review of Machine Learning Approach on Credit Card Fraud Detection

Massive usage of credit cards has caused an escalation of fraud. Usage of credit cards has resulted in the growth of online business advancement and ease of the e-payment system. The use of machine learning (methods) are adapted on a larger scale to detect and prevent fraud. ML algorithms play an es...

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Bibliographic Details
Published in:Human-Centric Intelligent Systems 2022-06, Vol.2 (1-2), p.55-68
Main Authors: Bin Sulaiman, Rejwan, Schetinin, Vitaly, Sant, Paul
Format: Article
Language:English
Subjects:
Artificial neural network (ANN)
Computer Science
Credit card fraud
Federated learning
Privacy-preserving
Random forest (RF) method
Review Article
Support vector machine (SVM)
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Summary:Massive usage of credit cards has caused an escalation of fraud. Usage of credit cards has resulted in the growth of online business advancement and ease of the e-payment system. The use of machine learning (methods) are adapted on a larger scale to detect and prevent fraud. ML algorithms play an essential role in analysing customer data. In this research article, we have conducted a comparative analysis of the literature review considering the ML techniques for credit card fraud detection (CCFD) and data confidentiality. In the end, we have proposed a hybrid solution, using the neural network (ANN) in a federated learning framework. It has been observed as an effective solution for achieving higher accuracy in CCFD while ensuring privacy.
ISSN:2667-1336
2667-1336
DOI:10.1007/s44230-022-00004-0