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.

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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