Fraud analytics: a research

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...

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Bibliographic Details
Published inJournal of Chinese economic and business studies Vol. 21; no. 1; pp. 137 - 141
Main Author Baesens, B
Format Journal Article
LanguageEnglish
Published Abingdon Routledge 02.01.2023
Taylor & Francis Ltd
Subjects
Deployment
Fraud
Humans
Identity theft
Insurance
Money laundering
Organized crime
Tax evasion
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Summary: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. 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.
ISSN:1476-5284
1476-5292
DOI:10.1080/14765284.2022.2162246