This paper is published in Volume-7, Issue-4, 2021
Area
Machine Learning
Author
Yash Rajesh, Thyagaraj Tanjavur
Org/Univ
BMS Institute of Technology and Management, Bengaluru, Karnataka, India
Pub. Date
19 July, 2021
Paper ID
V7I4-1435
Publisher
Keywords
Credit Card Fraud, Extra Security Layer, Machine Learning Systems, Isolation Forest Algorithm Automated Fraud Prediction

Citationsacebook

IEEE
Yash Rajesh, Thyagaraj Tanjavur. Credit Card Fraud Prediction, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Yash Rajesh, Thyagaraj Tanjavur (2021). Credit Card Fraud Prediction. International Journal of Advance Research, Ideas and Innovations in Technology, 7(4) www.IJARIIT.com.

MLA
Yash Rajesh, Thyagaraj Tanjavur. "Credit Card Fraud Prediction." International Journal of Advance Research, Ideas and Innovations in Technology 7.4 (2021). www.IJARIIT.com.

Abstract

Fraud detection by credit companies is essential in this digital era where the majority of financial transactions are made online. Fraudsters use loopholes in the payment systems to their benefit. Such problems can be solved to a large extent if the companies add an extra layer of security before confirming the transactions using machine learning algorithms. This project intends to use the Isolation Forest algorithm to enhance the security of credit card transactions by predicting the credibility of the transaction before authorization. Detecting 100% of the fraudulent transaction, minimizing the incorrect fraud classifications, and making the process automated is our objective.