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.
|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
|Conference||27th Asian-Pacific Conference on International Accounting Issues|
|Period||1/11/15 → 4/11/15|
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Financial statement fraud detection using supervised learning methodsAuthor: Gepp, A., 10 Oct 2015
Supervisor: Kumar, K. (Supervisor) & Bhattacharya, S. (External person) (Supervisor)
Student thesis: Doctoral ThesisFile