• K. Meena
• R. Gayathri

The Credit card usage is the one of the important part in today’s economy. With the wide use of credit cards the fraud will appears as a major issue in the credit card business. A large number of fraud transactions are made every day. So many techniques are availed for detecting fraud transactions in credit card. Each and every techniques implies their merits, demerits and principles. Today machine learning plays a major in major activities of Artificial Intelligence. Based on machine-learning techniques detecting credit card fraud is to reduce major issues in this transaction. Under the machine learning approach using Decision tree is used to detect credit card fraud in this paper. The experimental results depicts Decision tree based approaches provides highest accuracy when compared with other techniques and this proposed approach will be very useful for fraud investigators.

Credit Card, decision tree, fraud detection, machine learning

"Detecting of Anomaly Activities in Credit Card Transaction using Machine Learning Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.323-328, May-2019, Available :http://www.jetir.org/papers/JETIR1905D45.pdf

"Detecting of Anomaly Activities in Credit Card Transaction using Machine Learning Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp323-328, May-2019, Available at : http://www.jetir.org/papers/JETIR1905D45.pdf