• Dr. Savita Sangam
• Amey Salaskar
• Abhijeet Potale
• Rushikesh Gawde

: Credit card fraud is a growing global concern. It involves use of some other persons credit/debit card for purchasing purposes or withdrawing funds. To address this issue, various fraud detection methods, including rule-based systems, machine learning algorithms, and deep learning models, have been developed. The work presented reviews the existing credit card fraud detection techniques, focusing on their strengths, weaknesses, and performance metrics. Additionally, we propose a fraud detection approach that combines with various machine learning algorithms to enhance fraud detection accuracy. Our experimental results determine the fraudulent results based on user input data. The system detects the fraud based on the data that is fed to the system by individuals. The detection is carried out by using various machine learning algorithms.

Credit card fraud, Fraud detection, fraudulent, Machine learning, Fraud detection rate

"ARA – Credit Card Fraud Detection System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.146-151, June-2024, Available :http://www.jetir.org/papers/JETIRGH06024.pdf

"ARA – Credit Card Fraud Detection System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pp146-151, June-2024, Available at : http://www.jetir.org/papers/JETIRGH06024.pdf