The article is devoted to the theoretical substantiation and development of methodological approaches and practical recommendations for modeling the assessment of the financial stability of a service sector enterprise. To assess the financial condition of the hotel industry, a visual interpretation of the neural network, a model of self-organizing Kohonen map, was used. It is proven that by the method of Kohonen maps for each service provided by the hotel industry, in a certain period of activity, it is possible to establish certain objective limitations of structural characteristics that will prevent the transition to problem clusters or ensure the transition to better ones. The authors propose an economic and mathematical model of the process of assessing financial stability by calculating the integral indicator of financial stability of the service sector. The types of control maps for each of the coefficients that have a significant impact on the assessment of the financial stability of the enterprise in the service sector were identified. Control maps were constructed for each coefficient, which are part of the integrated indicator of financial stability, and their analysis was carried out for the presence of special reasons for the variability of the process of financial stability assessment. The concept of modeling a system for assessing the financial stability of service enterprises is developed in the article, which is based on the collection of financial data, a comprehensive analysis of factors influencing the financial condition, a study of the controllability of the process of assessing financial stability, building a model of an integral indicator of financial stability, and its program implementation.

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This article deals with the issue of managing bank credit risk using a cost risk model. Modeling of bank credit risk management was proposed based on neural-cell technologies, which expand the possibilities of modeling complex objects and processes and provide high reliability of credit risk determination. The purpose of the article is to improve and develop methodical support and practical recommendations for reducing the level of risk based on the value-at-risk (VaR) methodology and its subsequent combination with methods of fuzzy programming and symbiotic methodical support. The model makes it possible to create decision support subsystems for nonperforming loan management based on the neuro-fuzzy approach. For this paper, economic and mathematical tools (based on the VaR methodology) were used, which made it possible to analyze and forecast the dynamics of overdue payment; assess the quality of the credit portfolio of the bank; determine possible trends in bank development. A scientific and practical approach is taken to assess and forecast the degree of credit problematicity by qualitative criteria using a mathematical model based on a fuzzy technology, which can forecast the increased risk of loan default at an early stage in the process of monitoring the loan portfolio and model forecasting changes in the degree of credit problematicity on change of indicators. A methodology is proposed for the analysis and forecasting of indicators of troubled loan debt, which should be implemented as software and included in the decision support system during the process of monitoring the risk of the bank’s credit portfolio.

The paper defines the scientific provisions on the feasibility and effectiveness of using e-learning under conditions of quarantine restrictions related to the COVID-19 pandemic. It was proved that within the use of e-learning there has been a convergence between the scientific and methodological bases and the learning process itself, and new approaches to the general didactic and information content of e-learning courses within the education process have been formed. Modern platforms of e-learning are examined and a scheme involving the synchronous technology of e-learning was formed. Within the framework of the suggested learning platform, effective learning tools under conditions of quarantine restrictions were identified, the use of which allows the most successful solution of didactic tasks facing e-learning to be ensured on the basis of the everyday use of digital media and electronic devices for learning purposes. The fractal-cluster technology of an e-learning organization was suggested for an introduction. The functional dependencies on the forms and technologies of the educational process for the efficiency of higher education were obtained. The expediency of introducing fractal-cluster structures into the organizational component of the educational process was determined. Based on the tools of the fractal-cluster approach, a model of organization of the educational process in the information-entropy format was formulated.