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- Title
Taking the hunch out of the crunch: A framework to improve variable selection in models to detect financial statement fraud.
- Authors
Gepp, Adrian; Kumar, Kuldeep; Bhattacharya, Sukanto
- Abstract
Financial statement fraud is a costly problem for society. Detection models can help, but a framework to guide variable selection for such models is lacking. A novel Fraud Detection Triangle (FDT) framework is proposed specifically for this purpose. Extending the well‐known Fraud Triangle, the FDT framework can facilitate improved detection models. Using Benford's law, we demonstrate the posited framework's utility in aiding variable selection via the element of surprise evoked by suspicious information latent in the data. We call for more research into variables that measure rationalisations for fraud and suspicious phenomena arising as unintended consequences of financial statement fraud.
- Subjects
FINANCIAL statements; BENFORD'S law (Statistics); FRAUD; FRAUD investigation
- Publication
Accounting & Finance, 2024, Vol 64, Issue 2, p1569
- ISSN
0810-5391
- Publication type
Article
- DOI
10.1111/acfi.13192