Review of Machine Learning Approach on Credit Card Fraud Detection

Abstract 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 p...

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Bibliographic Details
Main Authors: Rejwan Bin Sulaiman, Vitaly Schetinin, Paul Sant
Format: Article
Language:English
Published: Springer Nature 2022-05-01
Series:Human-Centric Intelligent Systems
Subjects:
Online Access:https://doi.org/10.1007/s44230-022-00004-0
Description
Summary:Abstract 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