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Fraud analytics: a research agenda

Fraud analytics: a research agenda
Fraud analytics: a research agenda
Fraud is as old as humankind and appears in many types and forms. Popular examples are credit card fraud, tax evasion, identity theft, insurance fraud, counterfeit, click fraud, anti-money laundering, and payment transaction fraud. In earlier research we defined fraud as an uncommon, well-considered, imperceptibly concealed, time-evolving, and carefully organized crime (Baesens, Van Vlasselaer, and Verbeke 2015). Nowadays, fraud is typically tackled using state-of-the-art analytical techniques with many accompanying challenges. It is the purpose of this article to highlight twelve research topics (RTs) that we believe prioritize high on the agenda of contemporary fraud analytics models. We do this by reviewing fraud analytics from a data, model, performance, and deployment perspective.
1476-5284
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0

Baesens, Bart (2022) Fraud analytics: a research agenda. Journal of Chinese Economic and Business Studies. (In Press)

Record type: Article

Abstract

Fraud is as old as humankind and appears in many types and forms. Popular examples are credit card fraud, tax evasion, identity theft, insurance fraud, counterfeit, click fraud, anti-money laundering, and payment transaction fraud. In earlier research we defined fraud as an uncommon, well-considered, imperceptibly concealed, time-evolving, and carefully organized crime (Baesens, Van Vlasselaer, and Verbeke 2015). Nowadays, fraud is typically tackled using state-of-the-art analytical techniques with many accompanying challenges. It is the purpose of this article to highlight twelve research topics (RTs) that we believe prioritize high on the agenda of contemporary fraud analytics models. We do this by reviewing fraud analytics from a data, model, performance, and deployment perspective.

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Fraud Analytics - A Research Agenda (1) - Accepted Manuscript
Restricted to Repository staff only until 7 May 2024.
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Accepted/In Press date: 7 November 2022

Identifiers

Local EPrints ID: 471588
URI: http://eprints.soton.ac.uk/id/eprint/471588
ISSN: 1476-5284
PURE UUID: 7a0c5623-35e6-4067-bc6c-b313893445cd
ORCID for Bart Baesens: ORCID iD orcid.org/0000-0002-5831-5668

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Date deposited: 14 Nov 2022 17:38
Last modified: 19 Nov 2022 02:37

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