Can financial ratios detect fraudulent financial reporting

By Kathleen A. Kaminski, T. S. Wetzel, L. Guan. 2004

243 citations recorded by the source corpus.

Subfields: Accounting, Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/bb21cab211f3eae9295e1cd6f90f06496459be81

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Citations in the corpus

MetaFraud: A Meta-Learning Framework for Detecting Financial Fraud (2012, methodology): “We evaluated MetaFraud in comparison with three prior approaches that attained state-of-the-art results: Kirkos et al. (2007), Gaganis (2009), and Cecchini et al.”
Detecting and Predicting Financial Statement Fraud: The Effectiveness of the Fraud Triangle and SAS No. 99 (2008, unknown): “Persons (1995) and Kaminski et al. (2004) developed fraud prediction models using financial ratios; however, their models suffer from high misclassification rates.”
The relation between earnings management and financial statement fraud (2011, background): “However, Fanning and Cogger (1998) find a negative relation between sales to assets and fraud, while Kaminski et al. (2004) find a positive relation.”
CEO demographics and accounting fraud: Who is more likely to rationalize illegal acts? (2011, methodology): “Following prior research (see, for example, Beasley, 1996; Carcello and Nagy, 2004a, 2004b; Dechow et al., 1996; Kaminski et al., 2004; Uzun et al., 2004), a central part of our research design was to identify a control firm, not subject to SEC enforcement action, for each violator in the sample…”
Identification of fraudulent financial statements using linguistic credibility analysis (2011, methodology): “Kaminski et al. [31], focusing on a subset of Analytical Procedures (APs) used by auditors to augment typical audit procedures, found that financial ratios provide limited ability to detect FFR.”
Financial Statement Fraud Detection: An Analysis of Statistical and Machine Learning Algorithms (2011, unknown): “Net proﬁt margin (Chen and Sennetti 2005) was excluded because of its similarity to gross margin. h Inventory to sales (Kaminski et al. 2004) was included in the experiment.”
Fraud Risk Factor Of The Fraud Triangle Assessing The Likelihood Of Fraudulent Financial Reporting (2011, unknown): “Rate of correct classification in the present model is 86.5%, higher than models developed by Persons (1995), Kaminski et al. (2004), and Skousen and Wright (2006).”