Review of Machine Learning Approach on Credit Card Fraud Detection

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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.

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APA

Bin Sulaiman, R., Schetinin, V., & Sant, P. (2022, June 1). Review of Machine Learning Approach on Credit Card Fraud Detection. Human-Centric Intelligent Systems. Springer Nature. https://doi.org/10.1007/s44230-022-00004-0

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