Abstract— All economic opportunities were made possible by digitalization, which also confused the system with illegal activity. One improvement in the banking system is credit cards. Credit cards were able to draw new users every day because of how simple they were to use. Due to its popularity, there have been more fraudulent users, erroneous transactions, and card theft over time. Systems for detecting fraud were developed in order to stop these illicit activities. Our suggested article seeks to establish the truth or falsity of the completed transaction. To extract the results, we employed ML methods like logistic regression and random forest. It has been demonstrated that the Random Forest algorithm technique delivers an accurate generalisation error estimate. It was discovered the Random Forest algorithm technique. The Random Forest algorithm technique was found to be relatively stable, to resist overfitting, and to give a decent estimate of the generalisation error. Based on their precision, specificity, and accuracy, the results are evaluated.
Keywords— credit card, fraud detection, logistic regression, random forest, machine learning
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DOI:
10.17148/IJARCCE.2023.125146
