PREVENTION OF INFORMATION FALSIFICATION FOR ANALYTICAL SUPPORT OF ENTERPRISE MANAGEMENT
Abstract
The purpose of the article is to draw attention of managers of modern enterprises to the need and importance of creating a system of preventive protection and verification of the reliability of analytical information used for its needs, which is extremely relevant for effective functioning in the current conditions of martial law. The most accessible sources of analytical information are revealed for this reason. In particular it is emphasized, what analytical procedures can be carried out on the basis of the balance sheet and the report on financial results of the enterprise. It is determined that such actions may result in preliminary conclusions about the production capabilities of the enterprise. It is noted that the sources of information support for enterprise management can be not only internal, but also external. As for internal sources, they can be accounting and non-accounting. It is emphasized that there are three groups of factors that determine the possibility and motivation of falsification of financial statements. They include the opportunities that determine whether an employee can commit falsification; motive, which acts as both the cause and motivation for falsification; and rationalization - self-justification of the crime. The attention is paid that veiling and falsification are different things, but the enterprise is interested in their absence, since the disclosure of fraud usually has negative consequences. The authors compare the risks that may be caused by the consequences of fraud for internal and external stakeholders. In the article a list of preventive measures to prevent fraud, including compliance control, internal audit and compliance with corporate ethical standards, as well as the differences between them, are provided. The importance of assessing the reliability of financial statements for both internal and external stakeholders is justified. A list of models used to determine the level of risk of transparency and falsification of financial statements is represented. It is substantiated that the most successful among the models is the model of M.D. Benish. The essence of the M.D. Benish model is disclosed in the article, a list of indicators used in it to calculate the integral indicator M-Score is provided. The intervals of values of the M-Score indicating the presence or absence of falsifications in the financial statements of enterprise are presented. It is emphasised that the application of this model in practice is quite justified, but it can detect fraud only in 76 % of cases, therefore, in case of practical application, the authors provide indicators, the analysis of which will give additional information on the presence of manipulations with the financial statements.
References
Артюх-Пасюта О.В. Використання моделі М.Д. Беніша для оцінки достовірності фінансової звітності підприємства. Сучасні напрями розвитку економіки, підприємництва, технологій та їх правового забезпечення : матер. Міжнар. наук.-практ. конф. (м. Львів, 01–02 черв. 2022 р.). Львів : вид-во Львівського торговельно-економічного університету, 2022. С. 128–129.
Вигівська І.М., Барчак Т.П. Методи оцінки достовірності фінансової звітності.URL:https://conferences.vntu.edu.ua/index.php/fiip/fiip2021/paper/viewFile/11282/9391 (Дата звернення 24.02.2024)
Вигівська І.М., Скрипник МІ., Григоревська О. О. Поняття достовірності фінансової звітності та фактори впливу при її визначенні. Економічний вісник Дніпровського державного технічного університету. 2017. № 1 (79). С. 11–14.
Єфремов С. Психологія шахрайства (частина 2) URL: https://news.finance.ua/ua/news/-/443087/v-gpu-povidomyly-skilky-sprav-shhodo-habarnytstva-napravyly-do-sudu-u-2018-rotsi (Дата звернення 23.02.2024)
Калабухова С., Токарева Т. Транспарентність облікової інформації Economic Analysis, Volume 32. No. 4. 2022.
Петряєва З.Ф., Іващенко Г.А. Обліково-аналітичне забезпечення економічної безпеки : навч.-практ. посіб. Харків : ХНЕУ ім. С. Кузнеця, 2017. 242 с.
Ball R., & Shivakumar L. The role of accruals in asymmetrically timely gain and loss recognition. Journal of Accounting Research. 2006. Vol. 44, Iss. 2. P. 207–242
Burgstahler D., Dichev I. Earnings management to avoid earnings decreases and losses. Journal of accounting and economics. 1997. Vol. 24, No. 1. P. 99–126.
Beneish M. D. (1999). The detection of earnings manipulation. Financial Analysts Journal. 1999. Vol. 55, No. 5. P. 24–36. file:///C:/Users/admin/Downloads/FAJ.SepOct99.Beneish-cor.04.pdf (Дата звернення 24.02.2024)
Beneish M.D., Lee C.M., Nichols D.C. To Catch a Thief: Can Forensic Accounting Help Predict Stock Returns? August 15, 2011. http://csinvesting.org/wp-content/uploads/2015/04/Can-Forensic-Accounting-Predict-Stock-Returns.pdf
Golec A. Effectiveness of the Beneish Model in Detecting Financial Statement Manipulations. Acta Universitatis Lodziensis. Folia Oeconomica. 2019. Vol. 2, No. 341. P. 161–182.
Maria L. Roxas. Financial Statement Fraud Detection Using Ratio and Digital Analysis. Journal of Leadership, Accountability and Ethics vol. 8(4) 2011
Artiukh-Pasiuta O.V. (2022) Vykorystannia modeli M. D. Benisha dlia otsinky dostovirnosti finansovoi zvitnosti pidpryiemstva. [Use of M.D. Benish's model to assess the reliability of the company's financial statements.] Suchasni napriamy rozvytku ekonomiky, pidpryiemnytstva, tekhnolohii ta yikh pravovoho zabezpechennia: mater. Mizhnar. nauk.-prakt. konf. University of Trade and Economics, Lviv, Ukraine, 01-02.2022.pp. 128–129. (in Ukrainian)
Vyhivska I.M., Barchak T.P. Metody otsinky dostovirnosti finansovoi zvitnosti. [Methods of assessing the reliability of financial statements], available at: URL: (in Ukrainian) https://conferences.vntu.edu.ua/index.php/fiip/fiip2021 /paper/view File/11282/9391 (Accessed 24.02.2024)
Vyhivska I.M., Skrypnyk M.I., Hryhorevska O.O. (2017) Poniattia dostovirnosti finansovoi zvitnosti ta faktory vplyvu pry yii vyznachenni. [The concept of reliability of financial reporting and influencing factors in its determination]. Ekonomichnyi visnyk Dniprovskoho derzhavnoho tekhnichnoho universytetu. vol № 1 (79). pp. 11–14. (in Ukrainian)
Yefremov S. Psykholohiia shakhraistva (chastyna 2) [The Psychology of Fraud (Part 2)], available at: URL: https://news.finance.ua/ua/news/-/443087/v-gpu-povidomyly-skilky-sprav-shhodo-habarnytstva-napravyly-do-sudu-u-2018-rotsi (Accessed 23.02.2024)
Kalabukhova S, Tokareva T. (2022) Transparentnist oblikovoi informatsii [Transparency of accounting information], Economic Analysis, Volume 32. No. 4.. (in Ukrainian)
Petriaieva Z. F., Ivashchenko H. A. (2017) Oblikovo-analitychne zabezpechennia ekonomichnoi bezpeky : navch.-prakt. posib. [Accounting and analytical provision of economic security: educational and practical manual] Kharkiv: KhNEU im. S. Kuznetsia,. (Ukraine)
Ball R., & Shivakumar L. (2006) The role of accruals in asymmetrically timely gain and loss recognition. Journal of Accounting Research.. Vol. 44, Iss. 2. P. 207–242
Burgstahler D., Dichev I. (1997) Earnings management to avoid earnings decreases and losses. Journal of accounting and economics.. Vol. 24, No. 1. P. 99–126.
Beneish M.D. (1999). The detection of earnings manipulation. Financial Analysts Journal. Vol. 55, No. 5. P. 24–36. file:///C:/Users/admin/Downloads/FAJ.SepOct99.Beneish-cor.04.pdf (Accessed 24.02.2024)
Beneish M.D., Lee C.M., Nichols D.C. (2011) To Catch a Thief: Can Forensic Accounting Help Predict Stock Returns?, available at: http://csinvesting.org/wp-content/uploads/2015/04/Can-Forensic-Accounting-Predict-Stock-Returns.pdf
Golec A. (2019) Effectiveness of the Beneish Model in Detecting Financial Statement Manipulations. Acta Universitatis Lodziensis. Folia Oeconomica. Vol. 2, No. 341. P. 161–182.
Maria L. Roxas. (2011) Financial Statement Fraud Detection Using Ratio and Digital Analysis., Journal of Leadership, Accountability and Ethics vol. 8(4)
This work is licensed under a Creative Commons Attribution 4.0 International License.