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 language | English |
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Publication status | Published - 2015 |
Event | 27th Asian-Pacific Conference on International Accounting Issues: Global Perspectives of Accounting Information in the 21st Century - Gold Coast, Australia Duration: 1 Nov 2015 → 4 Nov 2015 Conference number: 22nd http://www.apconference.org/ |
Conference
Conference | 27th Asian-Pacific Conference on International Accounting Issues |
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Country/Territory | Australia |
City | Gold Coast |
Period | 1/11/15 → 4/11/15 |
Internet address |
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Dive into the research topics of 'The fraud detection triangle: A new framework for selecting variables in fraud detection research'. Together they form a unique fingerprint.Student theses
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Financial statement fraud detection using supervised learning methods
Author: Gepp, A., 10 Oct 2015Supervisor: Kumar, K. (Supervisor) & Bhattacharya, S. (External person) (Supervisor)
Student thesis: Doctoral Thesis
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