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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 9, ISSUE 5, MAY 2020

Real-Time Detection of Fraud in Credit Card using Machine Learning

Devu Kumar M S, Narendramurthy J, Nishant K, Akash K

DOI: 10.17148/IJARCCE.2020.9542

Abstract: Credit card payment has become very popular today and it is the easiest payment method along with the greatest increase in the transactions of credit card. credit card also become increasingly rampant in the recent years. Credit card fraud events are takes place recurrently and results in a huge economical loss. there are different ways of modelling credti card fraud detection problem. therefore bank and other financial organizations offers a better suitable application for detecting the fraudulent transactions with much worth and request. Fraud transactions are occurred in different ways. those various type of fraud activities a can be detect by using already applied machine learning algorithms like random forest algorithm to agree if a specific transaction is non-fraud or fraud And K-means to balance the genuine transaction in the imbalance dataset. the data used in our experiments can be taken according to the private disclosure contract.

Keywords: Credit Card, Fraud Detection, K-means Algorithm, Random Forest Algorithm.

How to Cite:

[1] Devu Kumar M S, Narendramurthy J, Nishant K, Akash K, “Real-Time Detection of Fraud in Credit Card using Machine Learning,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2020.9542