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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 12, ISSUE 4, APRIL 2023

A Review on Credit Card Fraud Detection Using Machine Learning

Dr. Kiran, Raju Poovarsha, Sanchitha L Anand, Soujanya G V, Samudyata S

DOI: 10.17148/IJARCCE.2023.124136

Abstract: Digitalization enabled all economic opportunities while also perplexing the system with illegal activities. Credit cards are an example of a banking system advancement. The ease of use of credit cards enabled it to attract new users every day. Because of its popularity, the number of fake users, false transactions, and card theft has increased over the years. To puta stop to such illegal acts, fraud detection systems were created.The goal of our proposed paper is to determine whether the completed transaction is true or false. We used ML techniques such as logistic regression and random forest to extract the results. The Random Forest algorithm approach has been shown to provide an accurate estimate of generalization error. The Random Forest algorithm approach was discovered toprovide a good estimate of the generalization error, to be resistant to overfitting, and to be very stable. The obtained results are assessed based on their accuracy, specificity, and precision.

Keywords: credit card, fraud detection, logistic regression, random forest

How to Cite:

[1] Dr. Kiran, Raju Poovarsha, Sanchitha L Anand, Soujanya G V, Samudyata S, “A Review on Credit Card Fraud Detection Using Machine Learning,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.124136