Identify Theft Detection on e-Banking Account Opening

Abstract

Banks are compelled by financial regulatory authorities to demonstrate whole-hearted commitment to finding ways of preventing suspicious activities. Can AI help monitor user behavior in order to detect fraudulent activity such as identity theft? In this paper, we propose a Machine Learning (ML) based fraud detection framework to capture fraudulent behavior patterns and we experiment on a real-world dataset of a major European bank. We gathered recent state-of-the-art techniques for identifying banking fraud using ML algorithms and tested them on an abnormal behavior detection use case.