Credit Card Fraud Detection

Author Name : Tanmoy Sarkar, Ashim Mahajan, Rai Nishant Bipin, Er. Shaifali Sharma, Abhinav Dhanotia, Kunal Roy

ABSTRACT

Detecting credit card fraud is a significant worry within the worldwide financial sector. This paper offers a succinct analysis of current machine learning and data science techniques for detecting credit card fraud, ranging from classical statistical models.

This study provides a focused examination of the shifting fraud detection landscape considering the development of digital payments and the significant financial ramifications of fraud. Our main objective is to evaluate these approaches’ efficacy, computational efficiency, and scalability and provide researchers, practitioners, and financial institutions with clear instructions on how to choose a method. Complex fraud patterns are frequently difficult for traditional rule-based systems to identify, underscoring the need for more flexible detection methods. To illustrate historical tendencies, the review synthesizes research findings, limits, and practical implications.