COMPARATIVE ANALYSIS OF BANKRUPTCY FORECASTING TECHNIQUES FOR EFFECTIVE CRISIS MANAGEMENT OF AN ENTERPRISE

Currently, the issue of choosing a bankruptcy forecasting methodology for enterprises remains relevant. The relevance of the topic under study is due to the fact that in order to respond in a timely manner to signs of deterioration in the financial condition of an organization, crisis managers need effective forecasting methods that not only identify the risk of bankruptcy, but also determine a set of measures to prevent the realization of this risk or minimize its consequences. Despite the availability of a large number of techniques that make it possible to predict the onset of bankruptcy, many problems remain in this area. The existing methods of analyzing financial statements to identify signs of bankruptcy differ from each other in the goals and objectives of the analysis, the information base, the amount of work, the complexity of calculations, the speed of solving analytical and managerial tasks, and other conditions. In addition, as the experience of practical calculations shows, not all currently existing methods for predicting possible bankruptcy of an enterprise are trustworthy. Practical experience shows that not every technique allows you to get adequate results: the same enterprise can simultaneously be recognized as a hopeless bankrupt, as a steadily developing enterprise, and as an enterprise in a pre-crisis state. This article presents the advantages and disadvantages of various bankruptcy forecasting methods, both governmental and proprietary. In addition, within the framework of this study, a comparative analysis of K-forecast models for assessing the probability of bankruptcy was carried out, and the most significant indicators of the financial condition used in predicting bankruptcy were identified.

1. Order of the Federal Tax Service under the State Property Committee of the Russian Federation "On Methodological recommendations for conducting an expert examination on the presence (absence) of signs of fictitious or intentional bankruptcy": dated 08.10.1999 No. 33-r: [expired]. URL: http://www.consultant.ru/ (accessed 20.04.2025). (In Russ.).

2. Order of the Federal Budget Committee under the State Property Committee of the Russian Federation "On some issues of ensuring a unified methodological approach to Analyzing the Financial condition of Enterprises with an unsatisfactory Balance Sheet Structure and declared Insolvent": dated 12.09.1994, No. 56-r (as amended. dated 14.11.1994) URL: http://www.consultant.ru/document/cons_doc_LAW_4875/ (accessed 20.04.2025). (In Russ.).

3. Buivis T.A., Ryabtseva L.V. Ryabtseva L.V. Insolvency (bankruptcy) of legal entities. The procedure for conducting, accounting, analysis and diagnosis of bankruptcy. Moscow: Nauchnoe obozrenie, 2015:140. (In Russ.).

4. Buivis T.A., Batanova M.V. Forecasting the bankruptcy of an organization using the example of JSC Organica. Vektor ekonomiki. 2021;6(60). URL: https://vectoreconomy.ru/ imaes/publications/2021/6/accounting/Buyvis_Batanova.pdf (accessed 20.04.2025). (In Russ.).

5. Kotlyarova O.A. Comparative analysis of domestic and foreign models for assessing and predicting the likelihood of bankruptcy of companies: the need for their application in Russia in modern conditions. Ekonomika i biznes. 2020;9-1(67):155‒158. (In Russ.).

6. Resolution of the Government of the Russian Fed-eration "On Approval of the Provisional Rules for the Verification by the Arbitration administrator of the presence of signs of fictitious and intentional bankruptcy": dated December 27, 2004, No. 855. URL: http://www.consultant.ru/ (accessed 20.04.2025). (In Russ.).

7. Federal Law No. 127-FZ dated 10.26.2002 (as amended on 12.26.2024) "On Insolvency (Bankruptcy)" (with amendments and additions, intro. effective from 03/01/2025). URL: https://www.consultant.ru/ (accessed 20.04.2025). (In Russ.).

8. Ivanova E.V., Efremkova T.I. Methodological prerequisites for the development of the bankruptcy forecasting model. Vestnik Altaiskoi akademii ekonomiki i prava. 2020;4-3:336‒343. EDN: OERCSN. https://doi.org/10.17513/vaael.1092 (In Russ.).

9. Doroshenko N.S. An overview of foreign and domestic factor models for diagnosis and forecasting. In: VII International Scientific Conference on Interdisciplinary Research. Yekaterinburg, September 20, 2024. Yekaterinburg: OOO «Institut tsifrovoi ekonomiki i prava», 2024:25‒28. EDN: SLAANQ. (In Russ.).

10. Karpov S.V. Development of models for predicting the bankruptcy of an organization: a review of the literature. Innovatsionnaya nauka. 2024;2-1:51‒52. EDN: YDGHLC. (In Russ.).

11. Kovalev V.V., Moldobaev T.Sh. Testing of foreign and domestic bankruptcy forecasting models at Rus-sian enterprises. Razvitie territorii. 2021;3(25):10‒19. EDN: NLOFYL. https://doi.org/10.32324/2412-8945-2021-3-10-19 (In Russ.).

12. Tebekin A.V. Assessment of anti-crisis management methods based on qualitative performance indicators of enterprises. Vestnik Moskovskogo universiteta imeni S.Yu. Vitte. Seriya 1 Ekonomika i upravlenie. 2019;2(29):71‒81. (In Russ.).

13. Maksimov N.B., Merkulova N.S. Diagnostics of bankruptcy of enterprises and models of forecasting the possibility of bankruptcy. Nauka i praktika regionov. 2024;2(35):49‒55. EDN: CHRNPJ. (In Russ.).

14. Mal'tseva K.K., Gerasimenko O.A. The practice of using various models of forecasting bankruptcy of organizations. Colloquium-Journal. 2019;7-7(31):23‒25. EDN: VAXPPU.

15. Petrova E.V., Nagovitsyna V.P. Diagnostics of bankruptcy probability: foreign and domestic forecasting models. Vektor ekonomiki. 2023;12(90). EDN WPWQWS. https://doi.org/10.51691/2500-3666_2023_12_3

16. Feizrakhmanova N.M. Applicability of classical bankruptcy forecasting models (Altman, Fulmer and Tafler) for domestic agricultural companies. OpenScience. 2023;1:123‒134. EDN FJZYCG. https://doi.org/10.51632/2658-7939_2023_5_1_123

17. Almamy J., Aston J., Ngwa L.N. An evaluation of Altman ' s Z-score using cash fl ow ratio to predict corporate failure amid the recent fi nancial crisis: Evidence from the UK. Journal of Corporate Finance. 2016; 6:278‒285.

18. Wang Y., Campbell M. Do bankruptcy models really have predictive ability? Evidence using China publicly listed companies. International Management Review. 2010;6(2):77–82.

19. Lifschutz S., Jacobi A. Predicting bankruptcy: Evidence from Israel. International Journal of Busi ness and Management. 2010;5(4):133–141.

20. Bhunia A., Sarkar R. A study of financial distress based on MDA. Journal of Management Research. 2011;3(2):1–11.

21. Maux J.L., Morin D. Black and white and red all over: Lehman Brothers’ inevitable bankrupt cy splashed across its financial statements. International Journal of Business and Social Science. 2010;2(20):39–65.

22. Agrawal К., Maheshwari Y. Efficacy of industry factors for corporate default prediction. IIMB Management Review. 2019;31:71–77.

23. Wu D., Ma X., Olson D. L. Financial distress predic-tion using integrated Z -score and multilayer percep-tron neural networks. Decision Support Systems. 2022;159(March):113814. EDN: LGMGGJ.

24. https://doi.org/10.1016/j.dss.2022.113814

25. Galitskaya Yu.N., Tereshchenko O.O. Forecasting the risk of bankruptcy of an enterprise using domestic models in order to maintain solvency. Journal of Economy and Business. 2019;12-1(58):82‒85. (In Russ.).

26. Popov V.B., Kadyrov E.Sh. Analysis of models for predicting the probability of bankruptcy of enterprises. Uchenye zapiski Tavricheskogo natsional'nogo universiteta imeni V.I. Vernadskogo Seriya «Ekonomika i upravlenie». 2014;1:118‒128. (In Russ.).

27. Postyushkov A.V. Forecasting bankruptcy. Arbitra-zhnyi upravlyayushchii. 2007;6:11‒16. (In Russ.).

28. Bandyopadhyay A. Predicting probability of default of Indian corporate bonds: logistic and Z-score approaches. The Journal of Risk Finance. 2006;7(3):255–272.

29. Bagautdinova G.M. Logistic models (logit models) for assessing the risk of bankruptcy of an enterprise. Innovatsionnye nauchnye issledovaniya. 2021;2-1(4):78‒89. (In Russ.).

30. The official website for the disclosure of accounting (financial) statements. URL: https://bo.nalog.ru/ (accessed 20.04.2025). (In Russ.).