Real-Time Fraud Detection Using Machine Learning

Abstract

Recent research has shown that machine learning techniques have been applied very effectively to the problem of payments related fraud detection. Such ML based techniques have the potential to evolve and detect previously unseen patterns of fraud. In this paper, we apply multiple ML techniques based on Logistic regression and Support Vector Machine to the problem of payments fraud detection using a labeled dataset containing payment transactions. We show that our proposed approaches are able to detect fraud transactions with high accuracy and reasonably low number of false positives.