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Journal articles on the topic 'Bankruptcy forecasting methods'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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1

Blazhevich, O., A. Karachun, and A. Suleymanova. "Comparative analysis and application of methods for predicting bankruptcy." Bulletin of Science and Practice, no. 5 (May 14, 2017): 161–75. https://doi.org/10.5281/zenodo.579745.

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In article methods of forecasting of bankruptcy are considered, their classification, the characteristic, a design procedure is given, merits and demerits are resulted. On an example of data of the accounting reporting of the enterprise–bankrupt the probability of bankruptcy is certain by each of analyzed methods. The analysis of procedures is lead and the most precise models are revealed.

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2

Kopczyński, Paweł. "Bankruptcy risk assessment of Polish listed companies using Asian multiple discriminant analysis models." Zeszyty Teoretyczne Rachunkowości 46, no. 2 (2022): 69–96. http://dx.doi.org/10.5604/01.3001.0015.8810.

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Purpose: The main purpose of this article is to evaluate whether multiple discriminant analysis models developed in Malaysia to forecast the bankruptcy of Malaysian indus-trial companies and Singaporean companies can be useful in assessing the risk of bank-ruptcy of Polish listed companies. Methodology/approach: To test the efficacy of these discriminant models, the finan-cial statements of 25 bankrupt Polish companies and 25 viable companies were used. The accuracy of the classification of these enterprises into two groups (potential bank-ruptcy and companies able to survive on the market) wa

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3

Korol, Tomasz. "Dynamic Bankruptcy Prediction Models for European Enterprises." Journal of Risk and Financial Management 12, no. 4 (2019): 185. http://dx.doi.org/10.3390/jrfm12040185.

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This manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and multilayer artificial neural network, and decision trees. Such a research approach will answer the question of whether changes in indicators are relevant predictors of a

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4

Inam, Fraz, Aneeq Inam, Muhammad Abbas Mian, Adnan Ahmed Sheikh, and Hayat Muhammad Awan. "Forecasting Bankruptcy for organizational sustainability in Pakistan." Journal of Economic and Administrative Sciences 35, no. 3 (2019): 183–201. http://dx.doi.org/10.1108/jeas-05-2018-0063.

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Purpose Considering the economic dimension of sustainability, the purpose of this paper is to analyze the risk of bankruptcy in the Pakistani firms of the non-financial sector from years 1995 to 2017. Design/methodology/approach Three techniques were used which include multivariate discriminant analysis (MDA), logit regression and multilayer perceptron artificial neural networks. The accounting data of firms were selected one year before the bankruptcy. Findings Findings were obtained by comparing and analyzing the methods which show that neural networks model outperforms in the prediction of

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5

KOTZERUBA, N.V. "Methodology for predicting the potential bankruptcy of an enterprise." Market Relations Development in Ukraine №9(256)2022 102 (December 15, 2022): 39–50. https://doi.org/10.5281/zenodo.7441787.

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The subject of the study is a set of methodical features of the implementation of the financial status and forecasting the threat of bankruptcy of the enterprise. The purpose of writing the article is to study the theoretical aspects of the analysis for the purpose of forecasting the bankruptcy of an enterprise based on the results of a decrease in its solvency. Methodology of the work – in the process of writing this article, general scientific and specific methods were used, in particular, economic and logical methods and methods of economic analysis; graphical and tabular methods were

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6

L. H, Solianyk, Shtefan N. M, and Nikolaienko A. O. "Fintech tools for predicting bankruptcy: integration of traditional and innovative approaches." Economic Bulletin of Dnipro University of Technology 81 (June 2023): 128–35. http://dx.doi.org/10.33271/ebdut/82.128.

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Methods. The theoretical and methodological basis of the study is the scientific developments of domestic and foreign scholars related to the issues of determining the role and features of using traditional discriminant models of bankruptcy forecasting and modern FinTech tools. The results of the study were obtained using the methods of abstraction; general and particular – in establishing the unity of existing traditional methods of bankruptcy forecasting and innovative FinTech technologies; the systematic method was used to systematise a wide range of FinTech tools specifically designed to p

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7

Apatova, Nataliya Vladimirovna, and Vitaliy Borisovich Popov. "FORECASTING BANKRUPTCY OF ENTERPRISES USING ARTIFICIAL INTELLIGENCE." Scientific Bulletin: finance, banking, investment., no. 2 (51) (2020): 113–20. http://dx.doi.org/10.37279/2312-5330-2020-2-113-120.

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With increasing competition, the market situation is constantly changing and many enterprises are at risk of bankruptcy. There are various methods for predicting the insolvency of manufacturing enterprises, but artificial intelligence methods allow this to be more accurately. Global data used for the analysis and forecasting of bankruptcy reveal the general patterns of this economic phenomenon. An analysis of publications on predicting bankruptcy of enterprises made it possible to identify frequently used mathematical models constructed for foreign firms and giving high accuracy for Russian on

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8

NEVREDINOV, Aleksandr R. "The instrumental machine learning methods for corporate bankruptcy prediction." Finance and Credit 27, no. 9 (2021): 2118–38. http://dx.doi.org/10.24891/fc.27.9.2118.

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Subject. It is very important for corporate governance and a choice of partners to evaluate the company’s position. Therefore, bankruptcy forecast methods have been actively studied in theoretical and practical proceedings for a long time. Recurring crises and high market dynamics make the subject especially relevant. Objectives. I develop the instrumental method based on machine learning to predict corporate bankruptcy. The study also reviews data sources, the potential of forecasting models, and chooses inputs for company analysis. Methods. I applied methods of analysis and synthesis, and th

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9

Лоханова and Valyentina Lokhanova. "Forecasting in Crisis Management Organization." Administration 4, no. 4 (2016): 91–98. http://dx.doi.org/10.12737/22795.

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The relevance of scientific research in the field of crisis management due to the depressed state of the Russian economy, including its business sector. One of the important directions of the scientific school of the Department of corporate management is forecasting the development of the organization in crisis. The article defines the essence of anti-crisis forecasting, its objective, stages and influencing factors. Special attention is given to forecasting methods, their classification, selection criteria. The contribution of famous Russian and foreign scientist

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10

Kazakova, N. A., A. F. Leshchinskaya, and A. E. Sivkova. "Assessment and forecasting bankruptcy risk of mining companies." Russian Journal of Industrial Economics 11, no. 3 (2018): 261–72. http://dx.doi.org/10.17073/2072-1633-2018-3-261-272.

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Comparative analysis of domestic and foreign methods of bankruptcy diagnostics allowed to offer key determinants for modeling the probability of bankruptcy taking into account the industry specificity of mining and metallurgical companies. On the basis of a generalization of the results of the correlation analysis, a high interrelation between indices of industrial production and indices – indicators of the probability of bankruptcy of these companies was revealed. The possibilities of monitoring the evaluation of indicators obtained on the basis of financial statements. Monitoring of calculat

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11

Исаева, Ш. М., and Х. Г. Гусайниева. "Financial stability as a factor in ensuring the economic security of an enterprise." Экономика и предпринимательство, no. 11(136) (February 27, 2022): 820–23. http://dx.doi.org/10.34925/eip.2021.11.136.163.

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В статье исследована проблема прогнозирования банкротства предприятий в России. Были рассмотрены различные методики оценивания риска наступления несостоятельности, проведено сравнение нескольких моделей прогнозирования банкротства на примере двух дагестанских предприятий. Выявлена тенденция несоответствия методик современным экономическим условиям. The article examines the problem of forecasting bankruptcy of enterprises in Russia. Various methods of assessing the risk of insolvency were considered, several models of bankruptcy forecasting were compared using the example of two Dagestan enterp

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12

Pisula, Tomasz, Grzegorz Mentel, and Jacek Brożyna. "Non-Statistical Methods of Analysing of Bankruptcy Risk." Folia Oeconomica Stetinensia 15, no. 1 (2015): 7–21. http://dx.doi.org/10.1515/foli-2015-0029.

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Abstract The article focuses on assessing the effectiveness of a non-statistical approach to bankruptcy modelling in enterprises operating in the logistics sector. In order to describe the issue more comprehensively, the aforementioned prediction of the possible negative results of business operations was carried out for companies functioning in the Polish region of Podkarpacie, and in Slovakia. The bankruptcy predictors selected for the assessment of companies operating in the logistics sector included 28 financial indicators characterizing these enterprises in terms of their financial standi

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13

Коновалов, М. С. "VERIFICATION OF EXISTING BANKRUPTCY FORECASTING METHODS IN THE MODERN RUSSIAN ECONOMY." Human Progress 10, no. 2 (2024): 11. http://dx.doi.org/10.34709/im.1102.11.

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Статья посвящена методикам прогнозирования банкротства предприятий. Проблема прогнозирования кризисных ситуаций, в частности банкротства, занимает особое место среди теоретических и практических проблем управления и ведения финансово-хозяйственной деятельности предприятия. Современная экономическая среда очень динамична, что особенно наглядно можно увидеть в текущих реалиях нашего государства. Прогнозирование банкротства – это важная область финансового анализа, направленная на раннее выявление признаков финансовых трудностей в организациях, что позволяет предпринять своевременные меры для пре

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14

Sinkovskyi, Artem, and Volodymyr Shulakov. "Development of fuzzified neural network for enterprise bankruptcy risk estimation." Technology audit and production reserves 3, no. 2(77) (2024): 19–22. http://dx.doi.org/10.15587/2706-5448.2024.306873.

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The object of this study is the assessment of the level of enterprise bankruptcy risk. It is a critical component in assessing the financial condition of an enterprise, and also serves as an indicator that allows the management team to reduce potential risks and develop their own strategies to strengthen the financial condition of the enterprise. One of the most challenging aspects of bankruptcy forecasting is the complex financial situations of bankrupt companies. By accurately predicting the risk of bankruptcy, businesses can take preventive measures to mitigate financial difficulties and en

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15

Солодуха, P. Soloduha, Черновалов, A. Chernovalov, Черновалов, and P. Chernovalov. "Development of Forecasting Methods of Firms Insolvency Within Logistics Networks." Auditor 3, no. 8 (2017): 38–45. http://dx.doi.org/10.12737/article_599bf6d1a65809.73741709.

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Th e most recent problems of bankruptcy predictions based on the Z-coeffi cient of Altman are analyzed in this article. As the result of practical usage we compared the results of solvency estimates made by our original method and by the current standards. We have made off ers to use Z-coeffi cient for the companies’ solvency monitoring.

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16

Croquet, Mélanie, Loredana Cultrera, Dimitri Laroutis, Laetitia Pozniak, and Guillaume Vermeylen. "Exploring the Role of Global Value Chain Position in Economic Models for Bankruptcy Forecasting." Econometrics 12, no. 4 (2024): 31. http://dx.doi.org/10.3390/econometrics12040031.

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This study addresses a significant gap in the literature by comparing the effectiveness of traditional statistical methods with artificial intelligence (AI) techniques in predicting bankruptcy among small and medium-sized enterprises (SMEs). Traditional bankruptcy prediction models often fail to account for the unique characteristics of SMEs, such as their vulnerability due to lean structures and reliance on short-term credit. This research utilizes a comprehensive database of 7104 Belgian SMEs to evaluate these models. Belgium was selected due to its unique regulatory and economic environment

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17

БЖАССО, А. А. "ОЦЕНКА РИСКА НАСТУПЛЕНИЯ ВЕРОЯТНОСТИ БАНКРОТСТВА ОРГАНИЗАЦИИ НА ОСНОВЕ РОССИЙСКИХ И ЗАПАДНЫХ МОДЕЛЕЙ ПРОГНОЗИРОВАНИЯ БАНКРОТСТВА В ЦЕЛЯХ УСОВЕРШЕНСТВОВАНИЯ СТРАТЕГИИ ЕЕ УСТОЙЧИВОГО РАЗВИТИЯ". Экономика и предпринимательство, № 10(171) (7 жовтня 2024): 1422–27. http://dx.doi.org/10.34925/eip.2024.171.10.260.

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В статье описана деятельность компаний в современных условиях, их подверженность воздействию кризисных факторов, которые могут привести к вероятности банкротству. Дано определение и раскрыто понятие банкротства. Описаны существующие методы прогнозирования вероятности банкротства. Проведена оценка риска наступления вероятности банкротства организации на основе российских и западных моделей прогнозирования банкротства в целях усовершенствования стратегии устойчивого развития, на основе экономических показателей, ЗАО «Урупский ГОК». Обоснована необходимость прогнозирования вероятности наступления

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18

Butko, Pavel. "USING ARTIFICIAL INTELLIGENCE (AI) IN THE ANALYSIS OF BANKRUPTCY OF COMMERCIAL ORGANIZATIONS." Science & World, no. 1 (July 7, 2024): 16–20. http://dx.doi.org/10.26526/2307-9401-2024-1-16-20.

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In modern business, the use of artificial intelligence (AI) is becoming increasingly common in various areas of company financial activities and in forecasting the likelihood of their bankruptcy. Traditional analytical methods, while having their advantages, are limited in data, linear, and subject to subjectivity. The use of AI allows for more precise and timely analysis, as well as providing reasoned recommendations for decision-making. Various AI approaches, such as natural language processing (NLP) systems, machine learning, and neural networks, enable the automation of processes for analy

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19

Brygała, Magdalena. "Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data." Risks 10, no. 2 (2022): 24. http://dx.doi.org/10.3390/risks10020024.

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This paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances is uncertain. The change of the macroeconomic and microeconomic situation of households requires searching for better and more precise methods. The research relies o

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20

Levandovska, O. "APPLICATION OF ANALYTICAL TOOLS FOR EVALUATING THR PERFORMANCE OF A MANUFACTURING ENTERPRISE." Series: Economic science 5, no. 179 (2023): 9–14. http://dx.doi.org/10.33042/2522-1809-2023-5-179-9-14.

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The article focuses on the use of analytical tools, namely, methods of assessing the bankruptcy of an enterprise, developed by foreign authors. Calculations are made using various models, and it is proved that at the moment there is no "ideal" model that will take into account all the realities of the enterprise. The current unstable situation of Ukraine's economy, namely the full-scale invasion of the aggressor country by the Russian Federation, creates additional difficulties for enterprises for development and normal functioning, so the issue of timely performance assessment and efficiency

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21

Tarasova, Julia A., and Ekaterina S. Fevraleva. "Forecasting of Bankruptcy: Evidence from Insurance Companies in Russia." Financial Journal 13, no. 4 (2021): 75–90. http://dx.doi.org/10.31107/2075-1990-2021-4-75-90.

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This work is devoted to creating a model which could predict bankruptcy of Russian insurance companies. The aim of the study is to build a model based on panel data; its final version should have a good predictive power. Said topic is relevant because the number of revoked licenses has changed a lot over the past few years — this situation may influence both insurance organizations and the population in a negative way. The paper reflects the main characteristics of bankruptcy as well as analyzes the bankruptcy prediction models which have been made by various authors since the 20th century. In

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Reddy, Nallamilli Lakshmi M. Vigneswara. "Next-Gen Hybrid Machine Learning for Bankruptcy Prediction: A Polish Market Analysis." International Journal for Research in Applied Science and Engineering Technology 13, no. 3 (2025): 2037–43. https://doi.org/10.22214/ijraset.2025.67741.

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Bankruptcy forecasting is crucial for financial stability and risk management. This study advances the accuracy of bankruptcy prediction using hybrid machine learning techniques on an imbalanced Polish dataset. The dataset presents challenges typical in real-world financial data, such as class imbalance and noisy features. Our approach combines the strengths of oversampling techniques,ensemble methods to enhance predictive performance. Experimental results demonstrate significant improvements in precision, recall, and F1-score metrics compared to traditional methods. Insights gained from featu

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23

Boyko, N. E., and E. A. Kalinina. "FORECASTING THE PROBABILITY OF BANKRUPTCY OF THE ENTERPRISE RAPID DIAGNOSTIC METHODS." Vestnik Volzhskogo universiteta im V N Tatishcheva 2, no. 1 (2022): 179–90. http://dx.doi.org/10.51965/20767919_2022_2_1_179.

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24

V., Fursova, Havrysh H., and Tymohova H. "UPDATING THE ISSUE OF FORECASTING TRADE ENTERPRISES BANKRUPTCY RISK IN THE CONDITIONS OF CORONAVIRUS PANDEMIC." Scientific Bulletin of Kherson State University. Series Economic Sciences, no. 40 (December 24, 2020): 68–72. http://dx.doi.org/10.32999/ksu2307-8030/2020-40-12.

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Due to the coronavirus pandemic and the implementation of strict quarantine restrictions, the global economy has faced serious challenges that have increased the number of corporate bankrupts around the world. To survive on market under new conditions any enterprise should be able to promptly assess its risks of insolvency. In Ukraine the trade was one of the most affected areas of the domestic economy (nearly one-third of trade enterprises have gone bankrupt), that is why it is very crucial to find out an adequate model for assessing the bankruptcy risk of commercial enterprises. This article

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25

KULAI, Svetlana V., and Evgenii E. SHVAKOV. "Development of MDA and Logit models to predict bankruptcy probability for Russian coal enterprises." Economic Analysis: Theory and Practice 24, no. 3 (2025): 194–216. https://doi.org/10.24891/ea.24.3.194.

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Subject. The study deals with forecasting the probability of bankruptcy for coal enterprises, represented by two variants of mathematical models: the MDA model and the logit model. Objectives. The aim is to develop a methodology for predicting the probability of bankruptcy based on data from Russian coal industry enterprises for 2014–2022. Methods. The study employs the coefficient method, correlation analysis, k-means method, cluster and factor analysis, MDA and logit models. Results. The development of models included several stages: formation of a basic system of financial coefficients; cre

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Kitowski, Jerzy, Anna Kowal-Pawul, and Wojciech Lichota. "Identifying Symptoms of Bankruptcy Risk Based on Bankruptcy Prediction Models—A Case Study of Poland." Sustainability 14, no. 3 (2022): 1416. http://dx.doi.org/10.3390/su14031416.

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The article presents selected Polish early warning models (logit and discriminant models) that allow the assessment of the risk of bankruptcy of a company, and the purpose of the considerations is to indicate their prognostic effectiveness in predicting susceptible Polish companies one year before their declarations of bankruptcy. The limitations of these methods were also indicated in unpredictable situations, such as the outbreak of an economic crisis, e.g., caused by a humanitarian crisis—the COVID-19 pandemic. Another aim chosen in the article is a methodological critical assessment of the

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27

Hubanova, I. V. "Features of Modeling the Probability of Bankruptcy Using Discriminant Models with Application in Economic Forensics." Business Inform 2, no. 517 (2021): 88–93. http://dx.doi.org/10.32983/2222-4459-2021-2-88-93.

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The article is aimed at studying the methodologies of forecasting bankruptcy, their application in forensic economic expertise, which will allow to make managerial decisions substantiated from the point of view of financial security of an enterprise and create opportunities for stable functioning and development of the enterprise. All enterprises are affected by negative factors and may find themselves in a crisis situation. That is why the management of enterprise should apply all existing measures to prevent bankruptcy and overcome crisis situations. Any crisis situation can be corrected if

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28

Herman, Sergiusz, and Bartłomiej Lach. "Czy warto budować modele prognozowania upadłości przedsiębiorstw uwzględniające kryterium przynależności sektorowej?" Wiadomości Statystyczne. The Polish Statistician 2024, no. 10 (2024): 41–58. http://dx.doi.org/10.59139/ws.2024.10.3.

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Forecasting bankruptcy of enterprises is a very important area, and it is of interest to a wide group of stakeholders. For this reason, since the beginning of the last century, continuous work aimed at developing effective tools used to this end has been undertaken. The main goal of the study presented in this article is to verify the legitimacy of constructing industry models for forecasting the bankruptcy of enterprises. The research was conducted on the basis of finan-cial data of 800 Polish companies for the years 2015–2019, drawn from the EMIS Professional database. The analysis used six

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Pitera, Rafał. "Verification of the effectiveness of discrimination models for forecasting bankruptcy of enterprises." Scientific Papers of Silesian University of Technology. Organization and Management Series 2023, no. 178 (2023): 497–511. http://dx.doi.org/10.29119/1641-3466.2023.178.28.

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Purpose: An attempt to evaluate the effectiveness of financial analysis tools used to assess financial health and to forecast bankruptcy. Methodology: The study used 31 of the most popular discriminatory models for bankruptcy prediction. The effectiveness of early warning models has been evaluated on the basis of financial data of economic entities operating on the territory of the Republic of Poland. The sample of the enterprises has comprised a total of 172 entities – both bankrupt and operating in good financial condition, located in 16 provinces. The data period was 2011-2020. The companie

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PETYK, Liubov, and Mykhailo PISIAK. "Methodological approaches to the diagnostic and assessment of the probability of business bankruptcy." Economics. Finances. Law 10/1, no. - (2022): 22–26. http://dx.doi.org/10.37634/efp.2022.10(1).5.

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Introduction. Methodological approaches to forecasting the financial state of enterprises from the point of view of possible bankruptcy are generalized and systematized. The classification of crisis diagnosis methods was studied and the stages of the crisis were considered. The modern practice of using foreign models for diagnosing the probability of the threat of insolvency of business entities is analyzed, with the identification of their advantages and disadvantages. Recommendations for improving approaches to assessing the probability of bankruptcy of national enterprises using foreign met

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31

БАБИЧ, И. С., and А. А. БЕЛОВА. "METHODS OF USING DIGITAL TECHNOLOGIES IN CRISIS MANAGEMENT." Экономика и предпринимательство, no. 1(162) (February 11, 2024): 1083–87. http://dx.doi.org/10.34925/eip.2024.162.1.206.

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В данной статье рассмотрена актуальность применения технологий цифровизации в антикризисном управлении. Та же обоснована необходимость учета фактора цифровизации в методике прогнозирования банкротства, так как эти технологии в долгосрочной перспективе способствуют снижению затрат и выходу из кризиса. This article examines the relevance of the use of digitalization technologies in crisis management. The necessity of taking into ccount the digitalization factor in the bankruptcy forecasting methodology is also justified, since these technologies contribute to cost reduction and recovery from the

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32

Чернявская, С. А., В. А. Драниченкова та В. Д. Пищикова. "Прогнозирование банкротства в агропромышленном комплексе: сравнительный анализ моделей и их применимость". Industrial Economics, № 1 (25 лютого 2025): 90–96. https://doi.org/10.47576/2949-1886.2025.1.1.012.

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Прогнозирование банкротства в агропромышленном комплексе (АПК) является важным инструментом для оценки финансовой устойчивости предприятий в условиях экономической нестабильности. В работе рассматриваются различные модели прогнозирования банкротства, включая финансовые коэффициенты, статистические методы и методы машинного обучения. Оценка ликвидности, рентабельности и финансовой независимости на примере сельскохозяйственных организаций Краснодарского края позволяет выявить уязвимости предприятий и оценить риски банкротства. Особое внимание уделено анализу изменений финансовых показателей, так

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БЖАССО, А. А. "METHODS OF FORECASTING BANKRUPTCY OF COMPANIES: CLASSIFICATION, ESSENCE AND NECESSITY OF DEVELOPING METHODOLOGICAL APPROACHES FOR ASSESSING AND PREDICTING THE PROBABILITY OF BANKRUPTCY IN A CRISIS." Экономика и предпринимательство, no. 1(162) (February 11, 2024): 919–24. http://dx.doi.org/10.34925/eip.2024.162.1.178.

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В статье описана деятельность компаний в современных условиях с учетом влияния факторов внешней и внутренней среды, их подверженность воздействию кризисных факторов, которые могут привести к вероятности банкротству. Рассмотрены основные признаки наступления банкротства, дано определение и раскрыто понятие банкротства. Описаны существующие методы прогнозирования вероятности банкротства компаний, зарубежных и отечественных авторов, их классификация, сущность, сделаны выводы о их достоинствах и недостатках. Обоснована необходимость разработки методических подходов оценки и прогнозирования вероятн

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T. O. MELIKHOVA. "ANALYSIS OF THE FINANCIAL SITUATION AND THE IDENTIFICATION OF THREATS AS A MEANS OF FORECASTING THE PROBABILITY OF BANKRUPTCY OF AN INDUSTRIAL ENTERPRISE." REVIEW OF TRANSPORT ECONOMICS AND MANAGEMENT, no. 1(17) (June 24, 2019): 48–57. http://dx.doi.org/10.15802/rtem.v0i1(17).176496.

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The purpose. The work is devoted to the analysis of the financial condition and the identification of threats as a means of predicting the probability of bankruptcy an industrial enterprise. The methodology. To solve the tasks it`s proposed to apply the methodology for predicting the probability of bankruptcy of an enterprise. The results. The paper considers the existing indicators of financial analysis of an industrial enterprise which are often used in practice. They have certain drawbacks since it`s difficult to choose a convenient methodology for conducting financial analysis through thei

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YUKHNIN, DANILA. "INTRA-GROUP COLLATERAL IN BANKRUPTCY: PROBLEMS AND SOLUTIONS." LEGAL BULLETIN 1, no. 9 (2024): 67–80. https://doi.org/10.5281/zenodo.11190941.

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The relevance of the topic is justified by the lack of sufficient legal regulation of security structures in the framework of bankruptcy proceedings and their scientific development, which creates systemic problems in the interpretation and application of such structures in the bankruptcy of an entrepreneurial group. The main purpose of this study is to analyze the problems that arise in relation to intra-group collateral in bankruptcy and to find solutions to them. The issues under consideration include issues of liability and the legal position of the collateral in the bankruptcy of the main

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VEREVKA, Tat'yana V., and Angelina E. EPICHENKO. "Developing a model for predicting bankruptcy of construction industry enterprises." Economic Analysis: Theory and Practice 23, no. 5 (2024): 878–92. http://dx.doi.org/10.24891/ea.23.5.878.

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Subject. The article considers methods of forecasting bankruptcy of a construction industry enterprise. Objectives. The study aims to develop an industry model to forecast bankruptcy of construction companies. Methods. The study employs general scientific methods of cognition, like analysis, synthesis, comparison, generalization, observation. The main statistical and economic research method is linear multidimensional discriminant analysis (MDA), which is used to perform calculations in the program for statistical data processing, SPSS Statistics. Results. We selected optimal predictors for ea

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Arinichev, Igor V., Lyudmila G. Matveeva, and Irina V. Arinicheva. "Forecasting the bankruptcy of an organization based on metric methods of data mining." Journal of Economic Regulation 9, no. 1 (2018): 061–73. http://dx.doi.org/10.17835/2078-5429.2018.9.1.061-073.

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Краснобокая and Irina Krasnobokaya. "Statistical prediction of probability of financial insolvency of industrial enterprises in the conditions of import substitution." Central Russian Journal of Social Sciences 11, no. 4 (2016): 173–83. http://dx.doi.org/10.12737/21334.

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The problem of diagnosis and prevention of financial insolvency of the domestic enterprises is one of the central problems in the system of anti-crisis financial management. Taking into account the crisis in the economy and the cyclical increase in the number of bankruptcies, it is of particular relevance in theoretical and applied aspects. The most acute problem is the bankruptcy in the industry, the development of which is an essential factor in the growth of the national economy in the context of import substitution.  Every fifth domestic company is on track to bankruptcy. In this sit

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KHANZADI, Mostafa, Ehsan ESHTEHARDIAN, and Mahdiyar MOKHLESPOUR ESFAHANI. "CASH FLOW FORECASTING WITH RISK CONSIDERATION USING BAYESIAN BELIEF NETWORKS (BBNS)." Journal of Civil Engineering and Management 23, no. 8 (2017): 1045–59. http://dx.doi.org/10.3846/13923730.2017.1374303.

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Cash-flow management is very important for contractors given that inadequate cash resources typically are the main causes for bankruptcy of construction companies. In comparison to most other industries, the construction industry is severely plagued by risk, and the success of construction projects usually depends on valuating all risks. However, conventional methods suggested by extant research on cash flow forecasting do not consider comprehensive identification of risk factors, interactions between the factors, and simultaneous occurrences of the factors. This study introduced a simple and

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Kovacova, Maria, and Tomas Kliestik. "Logit and Probit application for the prediction of bankruptcy in Slovak companies." Equilibrium 12, no. 4 (2017): 775–91. http://dx.doi.org/10.24136/eq.v12i4.40.

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Research background: Prediction of bankruptcy is an issue of interest of various researchers and practitioners since the first study dedicated to this topic was published in 1932. Finding the suitable bankruptcy prediction model is the task for economists and analysts from all over the world. forecasting model using. Despite a large number of various models, which have been created by using different methods with the aim to achieve the best results, it is still challenging to predict bankruptcy risk, as corporations have become more global and more complex. Purpose of the article: The ai

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Krichevskiy, Evgeniy Nikitich. "Development of scientific and methodological approaches to identify threats of possible insolvency of legal entities for tax administration purposes." Налоги и налогообложение, no. 3 (March 2025): 1–21. https://doi.org/10.7256/2454-065x.2025.3.74243.

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This article is a study of the possibility of improving scientific and methodological approaches to determining the bankruptcy of insolvent organizations. The paper discusses modern methods of bankruptcy forecasting, as well as the author's methodology for identifying "pre-bankruptcy" for tax administration purposes. The purpose of the presented research is to improve scientific and methodological approaches to determining the situation preceding the onset of insolvency (bankruptcy) of legal entities for the purposes of tax administration. The novelty of the present study lies in the developme

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Kupriushina, Olga M., and Nadezhda F. Scherbakova. "Applying forecast reporting to assess the probability of financial insolvency (bankruptcy)." Vestnik Voronezhskogo gosudarstvennogo universiteta. Ser.: Ekonomika i upravlenie = Proceedings of Voronezh State University. Series: Economics and Management, no. 2 (June 30, 2022): 71–82. http://dx.doi.org/10.17308/econ.2022.1/3916.

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Subject. During the pandemic, contacts between many organisations and their business partners were disrupted: their sales volumes and other sources of financing decreased and non-payments became more frequent. These reasons may result in an increased risk of financial insolvency for economic entities and may lead to bankruptcy. In this regard, financial forecasting is a way to avoid negative consequences.Purpose. The development of a universal analytical tool that allows predicting the probability of financial insolvency (bankruptcy) which has been tested within the PROTEK group of companies.

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Adamowicz, Krzysztof, and Tomasz Noga. "Assessment applicability of selected models of multiple discriminant analyses to forecast financial situation of Polish wood sector enterprises." Folia Forestalia Polonica 59, no. 1 (2017): 59–67. http://dx.doi.org/10.1515/ffp-2017-0006.

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Abstract In the last three decades forecasting bankruptcy of enterprises has been an important and difficult problem, used as an impulse for many research projects (Ribeiro et al. 2012). At present many methods of bankruptcy prediction are available. In view of the specific character of economic activity in individual sectors, specialised methods adapted to a given branch of industry are being used increasingly often. For this reason an important scientific problem is related with the indication of an appropriate model or group of models to prepare forecasts for a given branch of industry. Thu

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Antonowicz, Paweł, and Alicja Antonowicz. "The Capacity to Forecast Enterprise Insolvency on the Polish Market Using the Precursory Altman Z-Score Model (1968)." Annales Universitatis Mariae Curie-Skłodowska, sectio H – Oeconomia 56, no. 5 (2023): 7–26. http://dx.doi.org/10.17951/h.2022.56.5.7-26.

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Theoretical background: Many years have passed since the publication of the first multidimensional model (Z-score) of early bankruptcy warning by E.I. Altman in 1968. New models have since emerged in different countries. In this research stream, the share of econometric modelling based on the assumptions of discriminant analysis, i.e. MDA – Multiple Discriminant Analysis – one of the multidimensional classification methods categorised as empirical-induction methods, plays a particularly important role. Purpose of the article: The article assesses the capacity of the Altman Z-Score to forecast

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Murovana, Tetiana, and Vladyslav Paskhal. "Diagnosis of the crisis possibility and its effectiveness to maintain the financial stability of entrepreneurs." Economic Analysis, no. 29(4) (2019): 121–31. http://dx.doi.org/10.35774/econa2019.04.121.

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Introduction. Transformational changes in the national economy, its high level of dependence on the development trends of developed countries, and unstable financial situation require the search for effective tools for identifying and minimizing regulatory, financial, tax and reputational risks in business entities. The diagnosis of probability of crisis and bankruptcy is an effective tool for maintaining the financial stability of enterprises. Despite the large number of researchers and their achievements, the large number of methods and models for predicting the likelihood of bankruptcy, thi

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Калінеску, Тетяна Василівна, та Вікторія Володимирівна Височина. "ДІАГНОСТИКА ЙМОВІРНОСТІ БАНКРУТСТВА ПІДПРИЄМСТВ". TIME DESCRIPTION OF ECONOMIC REFORMS, № 1 (2 квітня 2024): 50–57. http://dx.doi.org/10.32620/cher.2024.1.06.

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Formulation of the problem. In the period of today's complex challenges - the conduct of military operations on the territory of Ukraine, the consequences of the pandemic, an unfavorable investment climate, and others - the detection of the probability of bankruptcy of enterprises is of particular importance. Timely detection of the onset of crisis phenomena using various methods and models and the adoption of precautionary measures ensure the avoidance of financial instability in the future. Therefore, conducting a timely diagnosis of the probability of bankruptcy is relevant, because there i

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Lvova, Olga. "Possibilities and limitations of the use of bankruptcy prediction models for insolvency prevention." Moscow University Economics Bulletin, no. 4 (August 31, 2021): 73–94. http://dx.doi.org/10.38050/01300105202144.

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The paper provides the solution to the problem of an integrated classification of existing bankruptcy prediction based on the content analysis of 270 relevant foreign and Russian publications issued within a period of 1910-2020. The author identifies two main groups of models– normative and positive, with the latter categorized into expert, mixed and objective including traditional statistical models and artificial intelligent techniques; and considers the specific features of certain predicting models, their advantages and disadvantages. He then reveals the economic content of such models and

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Lvova, Olga. "Possibilities and limitations of the use of bankruptcy prediction models for insolvency prevention." Moscow University Economics Bulletin, no. 4 (August 31, 2021): 73–94. http://dx.doi.org/10.38050/01300105202164.

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The paper provides the solution to the problem of an integrated classification of existing bankruptcy prediction based on the content analysis of 270 relevant foreign and Russian publications issued within a period of 1910-2020. The author identifies two main groups of models– normative and positive, with the latter categorized into expert, mixed and objective including traditional statistical models and artificial intelligent techniques; and considers the specific features of certain predicting models, their advantages and disadvantages. He then reveals the economic content of such models and

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Бжассо, А. А., and О. А. Котлярова. "The impact of the probability of bankruptcy of companies on the economy of the region during the crisis: problems and ways to solve them." Экономика и предпринимательство, no. 1(126) (March 12, 2021): 884–88. http://dx.doi.org/10.34925/eip.2021.126.01.173.

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В статье рассмотрено влияние кризисных факторов на экономику нашей страны и на экономику регионов, причины ухудшения финансового состояния организации и вероятность наступления банкротства компаний. Рассмотрены различные подходы и методы прогнозирования вероятности банкротства организаций. Описано практическое применение моделей прогнозирования вероятности наступления банкротства, на примере ЗАО «Урупский ГОК». Обоснована взаимосвязь финансовой устойчивости компаний, и успешного применение инструментов антикризисного управления региональной экономики. The article considers the impact of the cr

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LAZORENKO, L., and M. NIKIFOROV. "Bankruptcy risk assessment of JSC Ukrtelecom." Scientific Bulletin of the National Academy of Statistics, Accounting and Audit, no. 1-2 (March 31, 2023): 68–76. http://dx.doi.org/10.31767/nasoa.1-2-2023.08.

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The current stage of economic development requires enterprises to constantly improve the efficiency of activities and strengthen their positions. The introduction of a bankruptcy risk assessment system of any enterprise is an integral condition for its successful operation. The issue of applying appropriate methods and models for assessing the risk of bankruptcy of enterprises and developing ways to overcome or prevent them in order to improve the efficiency of enterprises is especially relevant in the current conditions. The purpose of the study is assessing the bankruptcy risk of JSC Ukrtele

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