Performance Evaluation of Machine Learning Methods for Detecting Credit Card Fraud
Anuj Yadav, Arpajit Adhikary, Aryan Kainth, Rohit Kumar · 2023
Fraud regarding Credit card transactions is a growing concern for both consumers and financial institutions. Traditional methods of detection, such as rule-based systems and manual review, are often time-consuming and ineffective. Machine learning algorithms offer a potential technique for identifying fraudulent transactions regarding credit cards. These algorithms can learn from past transactions and detect patterns that indicate fraudulent activity. In this paper, we review different machine learning methods that have been used to identify credit card frauds, including decision trees, neural networks, and clustering algorithms. We also discuss the challenges associated with using these techniques, such as handling imbalanced data and ensuring robustness to changing fraud patterns. Ultimately, this article reflects the need for more research in this field and shows how machine learning approaches might be used to predict fraud using credit cards.