• Tejaswini P. Patil
• Kiran S. Khandare

Abstract: Credit card fraud is a significant issue that poses serious threats to financial institutions and customers alike. With the rise of digital transactions, detecting fraudulent activities in real-time has become a critical challenge. Machine learning algorithms have shown promising results in addressing this problem, with Random Forest being one of the most popular choices. This review paper provides an in-depth analysis of credit card fraud detection using the Random Forest algorithm. It covers the fundamentals of credit card fraud detection, the Random Forest algorithm's working principles, and its application in fraud detection. The paper also discusses various techniques for feature engineering, model evaluation, and ensemble methods to improve the performance of the Random Forest algorithm for credit card fraud detection. Additionally, it highlights the limitations and challenges in this domain and explores potential future research directions.

Credit card, Fraud detection, Fraud detection, Random Forest algorithm

"Credit Card Fraud Detection Using Random Forest Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 8, page no.b628-b631, August-2023, Available :http://www.jetir.org/papers/JETIR2308176.pdf

"Credit Card Fraud Detection Using Random Forest Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 8, page no. ppb628-b631, August-2023, Available at : http://www.jetir.org/papers/JETIR2308176.pdf