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
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DOI:
10.17148/IJARCCE.2023.124136
