Identify Theft Detection on e-Banking Account Opening

Roxane Desrousseaux, Gilles Bernard, Jean-Jacques Mariage

2019

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.

Paper Citation

in Harvard Style

Desrousseaux R., Bernard G. and Mariage J. (2019). Identify Theft Detection on e-Banking Account Opening. In Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: NCTA; ISBN 978-989-758-384-1, SciTePress, pages 556-563. DOI: 10.5220/0008648605560563

in Bibtex Style

@conference{ncta19,
author={Roxane Desrousseaux and Gilles Bernard and Jean-Jacques Mariage},
title={Identify Theft Detection on e-Banking Account Opening},
booktitle={Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: NCTA},
year={2019},
pages={556-563},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008648605560563},
isbn={978-989-758-384-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: NCTA
TI - Identify Theft Detection on e-Banking Account Opening
SN - 978-989-758-384-1
AU - Desrousseaux R.
AU - Bernard G.
AU - Mariage J.
PY - 2019
SP - 556
EP - 563
DO - 10.5220/0008648605560563
PB - SciTePress