• A.Yugandhara Reddy
• Dr.Sivadi Balakrishna
• Alla Jyothi
• Bethapudi Surekha
• Yammila Sumanjali , Mekapothula Varsha

Fraud is a collection of illicit practices used to steal goods or money under false pretenses. In the realm of finance, credit card transaction fraud is one of the most pressing problems.Banks and suppliers have lost a significant amount of money, and credit card customers have suffered considerably as well. It has been demonstrated that one of the best ways to identify this type of fraud is through machine learning. This paper proposes a random forest-based fraud detection system to tackle this real-world problem. This recommended method can assist identify credit card transaction fraud more precisely. Additionally, the suggested system employs a learning-to-rank methodology to rank the alert, which successfully lowers the quantity alerts produced by FDS and gives the investigator a tiny trustworthy fraud warning.

Credit Card Fraud Detection, Fraud Detection, Fraudulent Transactions, KNearest Neighbors, Super Vector Machine, Logistic Regression, Naïve Bayes.

"IDENTIFYING CREDIT CARD FRAUD WITH SUPERVISED LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 10, page no.314-323, October-2024, Available :http://www.jetir.org/papers/JETIRGN06036.pdf

"IDENTIFYING CREDIT CARD FRAUD WITH SUPERVISED LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 10, page no. pp314-323, October-2024, Available at : http://www.jetir.org/papers/JETIRGN06036.pdf