Registration Number
2125U011305, Article
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Article, Стаття
Title
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Mamyrbayev Orken
Azarova Anzhelika
Nikiforova Liliia
Kalizhanova Aliya
Shyian Anatolii
Ruzakova Olga
Savina Natalia
Азарова А. О.
Нікіфорова Л. О.
Шиян А. А.
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28-01-2025
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Вінницький національний технічний університет
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https://ir.lib.vntu.edu.ua/handle/123456789/44017
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RWTH Aachen University
Description
To assessfinancial risk, it is necessary to restore a large set of many initial parameters, which aren’t only determined by the criteria of authority, efficiency, and minimum capabilities, but also by using special information and their display functions. The authors propose a model of financial risk assessment of the enterprise, developed on the basis of mathematical apparatus of certain elements of decomposition functionsto coordinate parameters and functions of determining the level of risk of a potential investor, which is a more accurate, unambiguous, and categorical during the assessment of financial risk by using rigidly defined threshold elements of input parameters loaded into response classes. The solution to the complex problem of accurate financial risk assessment becomes possible by obtaining several quantitative estimates of all separate classes of input data. The accuracy of financial risk assessment for the computer model developed in the article has been experimentally tested in small enterprises and is the highest in comparison to the normative methods of financial risk assessment. The special proposal of the proposed model consists of the restoration of many fundamental initial parameters aimed at assessing the financial risk, which is determined by the relevant capabilities of the enterprise and expert information. The model also uses the function of conversion of initial parameters for the assessment and a set of functional decompositions for compiling parameters, to influence the identification of financial risk which makes it universal for the use of enterprises operating in different sectors of the economy. Also, the developed computer model can be used both offline and when using a cloud environment.
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2026-10-26
