Lifting the Numbers Game: Identifying key input variables and a best-performing model to detect financial statement fraud

Adrian Gepp, Kuldeep Kumar, Sukanto Bhattacharya

Research output: Contribution to journalArticleResearchpeer-review

Abstract

This study enables practitioners and researchers to make an informed choice for a financial statement fraud detection model, rather than defaulting to popular, yet dated, models. Using a specifically devised performance criterion, our newly configured ensemble outperforms 31 others in the most comprehensive comparison to date spanning parametric, non‐parametric, big data and ensemble techniques. We use a large set of input variables and holdout data relative to prior studies. We find empirical support for financial and non‐financial variables covering the three Fraud Triangle factors. New findings include fraud risk being reduced with more debt, likely from increased monitoring by creditors.
Original languageEnglish
Pages (from-to)4601-4638
JournalAccounting and Finance
Volume61
Issue number3
Early online date26 Dec 2020
DOIs
Publication statusPublished - Sep 2021

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