The fraud detection triangle: A new framework for selecting variables in fraud detection research

Adrian Gepp, Kuldeep Kumar, Sukanto Bhattacharya

Research output: Contribution to conferenceAbstractResearchpeer-review

Abstract

The selection of explanatory (independent) variables is crucial to developing a fraud detectionmodel. However, the selection process in prior financial statement fraud detection studies isnot standardized. Furthermore, the categories of variables differ between studies.Consequently, the new Fraud Detection Triangle framework is proposed as an overall theoryto assist in guiding the selection of variables for future fraud detection research. This newframework adapts and extends Cressey’s (1953) well-known and widely-used fraud triangle tomake it more suited for use in fraud detection research. While the new framework wasdeveloped for financial statement fraud detection, it is more broadly applicable to fraud detection in general.
Original languageEnglish
Publication statusPublished - 2015
Event27th Asian-Pacific Conference on International Accounting Issues: Global Perspectives of Accounting Information in the 21st Century - Gold Coast, Australia
Duration: 1 Nov 20154 Nov 2015
Conference number: 22nd
http://www.apconference.org/

Conference

Conference27th Asian-Pacific Conference on International Accounting Issues
CountryAustralia
CityGold Coast
Period1/11/154/11/15
Internet address

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  • Student Theses

    Financial statement fraud detection using supervised learning methods

    Author: Gepp, A., 10 Oct 2015

    Supervisor: Kumar, K. (Supervisor) & Bhattacharya, S. (External person) (Supervisor)

    Student thesis: Doctoral Thesis

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    Cite this

    Gepp, A., Kumar, K., & Bhattacharya, S. (2015). The fraud detection triangle: A new framework for selecting variables in fraud detection research. Abstract from 27th Asian-Pacific Conference on International Accounting Issues, Gold Coast, Australia. http://www.apconference.org/wp-content/uploads/2015/12/27th-APC-Final.pdf