Journal of Innovation in Computer Science and Engineering
  • Year: 2021
  • Volume: 11
  • Issue: 1

Credit card fraud detection

  • Author:
  • Shenaz Begum1, V B Srinivas1, Usha V Ballolli1, J Vaishnavi1, B Varsha1
  • Total Page Count: 4
  • Page Number: 47 to 50

1Department of Computer Science of Engineering, Ballari Institute of Technology and Management, Ballari, Karnataka, India

*E-mail: shehanazbitm@gmail.com

**b_srinivas274912@gmail.com

***balloli_ushamallabollolli@gmail.com

****j_vaishnavijois2@gmail.com

*****b_varshab@gmail.com

Online published on 04 December, 2021.

Abstract

Due to the increase in fraud leading to global financial losses, many issues and methods designed to detect involves analyzing user activities in order to understand the malicious behavior of users. Cruelty is a broad term that includes Delinquency, Fraud, Intrusion Fraud Detection, and Account Error. This paper introduces a study of current strategies used in detecting credit card fraud. This paper also discusses popular algorithms used for unsupervised and supervised learning.

Keywords

Fraud Behavior, Credit Card