loading
Documents

Research.Publish.Connect.

Paper

Authors: Roxane Desrousseaux ; Gilles Bernard and Jean-Jacques Mariage

Affiliation: LIASD Laboratory, Paris 8 University and France

ISBN: 978-989-758-384-1

ISSN: 2184-2825

Keyword(s): Machine Learning, Fraud Detection, Behavior, Pattern, Banking, Identity Theft.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Learning Paradigms and Algorithms ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

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.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.208.132.33

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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 - Volume 1: NCTA, (IJCCI 2019) ISBN 978-989-758-384-1, ISSN 2184-2825, pages 556-563. DOI: 10.5220/0008648605560563

@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 - Volume 1: NCTA, (IJCCI 2019)},
year={2019},
pages={556-563},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008648605560563},
isbn={978-989-758-384-1},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2019)
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

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.