CREDIT CARD FRAUD DETECTION BASED ON XGBOOST ALGORITHM

Authors

  • Greeshma Arya[1], Ahmed Hesham Sedky[2], Vikas Rathi[3], Nivriti Pandey[4], Vidushi Pathak[5], Preeti Shubham[6] Author

Abstract

Creditcardfraudisagrowingprobleminthemodernworldandaffectsmillionsofpeopleeachyear.ThisPaperoutlines a credit card fraud detection system that uses machine learning to detect fraudulent activity in real-time. The system employs an ensemble of supervised learning algorithms to build a predictive model that can detect fraudulent transactions. The system detects suspicious transactions and alerts the cardholder and financial institution by utilizing data from different sources, such as credit card transactions and demographic data. The algorithm is designed to be highly accurate, efficient and scalable, and can be easily integrated into existing systems. With this system, credit card companies and financial institutions can take proactive steps to reduce the risk of fraud.

General Terms: Credit Cards, Security, Algorithms

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Published

2023-11-20

Issue

Vol. 5 No. 2 (2023)

Section

Articles