Fuzzy Model for Detection of Fraudulent Financial Statements: A Case Study of Lithuanian Micro and Small Enterprises

Erika Besusparienė and Vesa A. Niskanen
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Erika Besusparienė: Vytautas Magnus University, Kaunas, Lithuania
Vesa A. Niskanen: Vytautas Magnus University, Kaunas, Lithuania

European Journal of Business Science and Technology, 2023, vol. 9, issue 2, 165-185

Abstract: 90 per cent of enterprises in the European Union (EU), including Lithuania, are small enterprises that prepare the abridged financial statements. Verifying the fairness of these reports for stakeholders is challenged due to the lack of data. The aim of this research is to develop a novel model based on fuzzy logic for detecting fraudulent financial statements in micro and small enterprises by using financial ratios suitable for abridged financial statements. The results have shown that the developed fuzzy model enables estimation of the level of fraud in each individual element of accounting. Identifying each fraudulent accounting element allows us to gain insights into the areas where the enterprise has committed fraud. The proposed model has been designed to help small businesses reduce the risk, but it may also be used by public authorities as a tool for achieving greater business transparency.

Keywords: accounting; financial statement; fraud; fuzzy (search for similar items in EconPapers)
JEL-codes: G3 M41 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:men:journl:v:9:y:2023:i:2:p:165-185

DOI: 10.11118/ejobsat.2023.008

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