Reducing False Positives in Fraud Monitoring Systems Using Behavior-Driven  Feature Engineering and Synthetic Data Generation

Adarsh Naidu

Reducing False Positives in Fraud Monitoring Systems Using Behavior-Driven Feature Engineering and Synthetic Data Generation

Authors

Adarsh Naidu

Keywords:

Abstract

Fraud monitoring systems have become an indispensable component of modern digital financialinfrastructures, safeguarding transactions across banking, e-commerce, and payment platforms.While recent advances in machine learning have significantly enhanced the detection of fraudulent activities, these systems continue to suffer from a critical limitation

References

R. J. Bolton and D. J. Hand, “Statistical fraud detection: A review,” Statistical Science, vol. 17, no. 3, pp. 235–255, 2002

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Published

2023-02-15

How to Cite

Adarsh Naidu. (2023). Reducing False Positives in Fraud Monitoring Systems Using Behavior-Driven Feature Engineering and Synthetic Data Generation . Journal of Computational Analysis and Applications (JoCAAA), 31(2), 756–769. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5178