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2021 | OriginalPaper | Chapter

Financial Statement Fraud Detection of Ukrainian Corporations on the Basis of Beneish Model

Authors : Serhii Lehenchuk, Tetiana Mostenska, Halyna Tarasiuk, Iryna Polishchuk, Mykola Gorodysky

Published in: The Importance of New Technologies and Entrepreneurship in Business Development: In The Context of Economic Diversity in Developing Countries

Publisher: Springer International Publishing

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Abstract

The article analyzes the level of financial statements fraud in Ukrainian corporations based on the use of the Beneish model. The purpose of the article is to analyze the content of the Beneish model and its modified version to detect fraud of financial statements, as well as their use to identify such abuses by Ukrainian corporations. The study used the assumption that the application of the Beneish model and its modified version based on the improvement of the information base for their calculation can be used to detect fraud of financial statements of enterprises. The system of indicators of Beneish model for determining fraud of financial statements has been identified and analyzed. The 8-factor Beneish model has been analyzed for calculating the values of the M-Score (Beneish). The 5-factor Roxas model has been analyzed for calculating the values of the M-Score (Roxas). The information support for unobstructed application of the Beneish model and it modified by Roxas 5-factor variance in the process of identifying the level of falsification of financial statements has been identified and grounded. An algorithm for applying the Beneish and Roxas models to detect financial statements fraud has been developed. The indicators (variables) of the Beneish model for 30 leading Ukrainian corporations for 2017–2018 have been identified and analyzed. The value of the M-Score indicator according to the Beneish and Roxas models for 30 Ukrainian corporations for 2017–2018 has been calculated and analyzed. M-Score coincidences and differences for the Beneish and Roxas models for 30 Ukrainian corporations for 2017–2018 has been allowed to identify 4 possible interpretations of the results (M-Score (B) < −2.22 and M-Score (R) < −2.76; M-Score (B) > −2.22 and M-Score (R) > −2.76; M-Score (B) > −2.22 and M-Score (R) < −2.76; M-Score (B) < −2.22 and M-Score (R) > −2.76). Based on the comparison of actual and normative values of the M-Score indicator according to the Beneish and Roxas models, the level of reliability and the level of possible financial statements fraud of Ukrainian corporations has been identified.

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Literature
3.
go back to reference Feruleva, N.V., Shtefan, M.A.: detection of financial statements fraud in Russian companies: analysis of the beneish and roxas models applicability. Rossijskij zhurnal menedzhmenta. Tom 14(3), 49–70 (2016) Feruleva, N.V., Shtefan, M.A.: detection of financial statements fraud in Russian companies: analysis of the beneish and roxas models applicability. Rossijskij zhurnal menedzhmenta. Tom 14(3), 49–70 (2016)
4.
go back to reference Aris, N.A., Othman, R., Arif, S.M.M., Malek, M.A.A., Omar, N.: Fraud detection: benford’s law vs beneish model. In: IEEE Symposium on Humanities, Science and Engineering Research, pp. 726–731 (2013) Aris, N.A., Othman, R., Arif, S.M.M., Malek, M.A.A., Omar, N.: Fraud detection: benford’s law vs beneish model. In: IEEE Symposium on Humanities, Science and Engineering Research, pp. 726–731 (2013)
5.
go back to reference Beneish, M.D.: The detection of earnings manipulation. Finan. Anal. J. 55, 24–36 (1999)CrossRef Beneish, M.D.: The detection of earnings manipulation. Finan. Anal. J. 55, 24–36 (1999)CrossRef
6.
go back to reference Golec, A.: Effectiveness of the beneish model in detecting financial statement manipulations. Acta Universitatis Lodziensis. Folia Oeconomica. 2(341), 161–182 (2019)CrossRef Golec, A.: Effectiveness of the beneish model in detecting financial statement manipulations. Acta Universitatis Lodziensis. Folia Oeconomica. 2(341), 161–182 (2019)CrossRef
7.
go back to reference Irwandi, S.A., Ghozali, I., Faisal, P., I.D. : Detection fraudulent financial statement: beneish M-score model. WSEAS Trans. Bus. Econ. 16, 271–281 (2019) Irwandi, S.A., Ghozali, I., Faisal, P., I.D. : Detection fraudulent financial statement: beneish M-score model. WSEAS Trans. Bus. Econ. 16, 271–281 (2019)
8.
go back to reference Kubaščíková, Z.: Applying Benford´s law in financial statement analysis. In: Kubaščíková, Z. IFRS: Global Rules & Local use: Proceedings of the 5th International Scientific Conference, pp. 337–342. Anglo-American University, Prague (2017) Kubaščíková, Z.: Applying Benford´s law in financial statement analysis. In: Kubaščíková, Z. IFRS: Global Rules & Local use: Proceedings of the 5th International Scientific Conference, pp. 337–342. Anglo-American University, Prague (2017)
9.
go back to reference Lehenchuk, S., Velykyi, Y., Belinska, S.: Development of variability concept in accounting: Ukrainian context. Baltic J. Econ. Stud. 4(3), 158–164 (2018)CrossRef Lehenchuk, S., Velykyi, Y., Belinska, S.: Development of variability concept in accounting: Ukrainian context. Baltic J. Econ. Stud. 4(3), 158–164 (2018)CrossRef
10.
go back to reference Roxas, M.L.: Financial statement fraud detection using ratio and digital analysis. J. Leadersh. Accountability Ethics 8(4), 56–66 (2011) Roxas, M.L.: Financial statement fraud detection using ratio and digital analysis. J. Leadersh. Accountability Ethics 8(4), 56–66 (2011)
11.
go back to reference Spătăcean, I.-O.: Testing the beneish model relevance in case of entities with confirmed reputational risk. Acta Marisiensis Seria Oeconomica 13(1), 43–48 (2019)CrossRef Spătăcean, I.-O.: Testing the beneish model relevance in case of entities with confirmed reputational risk. Acta Marisiensis Seria Oeconomica 13(1), 43–48 (2019)CrossRef
14.
go back to reference Talab, H., Hammood, H., Ali, S.I.: Role of beneish m-score model in detecting of earnings management practices: empirical study in listed banks of iraqi stock exchange. Int. J. Appl. Bus. Econ. Res. 15(23, part 2) (2017) Talab, H., Hammood, H., Ali, S.I.: Role of beneish m-score model in detecting of earnings management practices: empirical study in listed banks of iraqi stock exchange. Int. J. Appl. Bus. Econ. Res. 15(23, part 2) (2017)
Metadata
Title
Financial Statement Fraud Detection of Ukrainian Corporations on the Basis of Beneish Model
Authors
Serhii Lehenchuk
Tetiana Mostenska
Halyna Tarasiuk
Iryna Polishchuk
Mykola Gorodysky
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-69221-6_100

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