Development of a model of comprehensive assessment of enterprise bankruptcy risk level
DOI:
https://doi.org/10.15587/2706-5448.2025.330650Keywords:
business processes, enterprise, bankruptcy risk, model, assessment, expert, fuzzy setsAbstract
The object of this study is the process of assessing the risk level of enterprise bankruptcy based on a comprehensive analysis of both quantitative and qualitative characteristics of its business processes. The problem addressed in this work concerns the improvement of bankruptcy risk prediction models. Existing approaches suffer from several significant drawbacks. In particular, the BR model lacks sufficient flexibility. It requires strict preliminary ranking of influencing factors and relies on formalized weighting systems. This limits the individualization of the analysis and reduces the accuracy of the assessment.
The essence of the obtained results lies in the development of a model of comprehensive assessment of enterprise bankruptcy risk level (MCAEBRL). This model implements a comprehensive analysis of the enterprise's business processes using both quantitative and qualitative characteristics. Ranking of factors is not mandatory. Instead, the model uses actual normalized weights determined by experts. It supports flexible rating scales for various indicator types, enables fuzzification of data to handle linguistic evaluations of indicators, and allows a group of experts to be involved to enhance the objectivity of the results.
The importance of the obtained results is explained by the features of the MCAEBRL construction. A process-based and integrated approach was used to analyze the enterprise’s activities. A multi-level hierarchy of business processes was employed, as well as quantitative and qualitative indicators for their characterization. Assessments were conducted using broad rating scales. The model uses fuzzy set theory to handle both precise and imprecise data.
The proposed model can be practically applied to assess the financial stability of enterprises across various industries. It is especially useful in unstable economic environments. The model is suitable for working with data of different nature and accuracy levels. It can also be used in cases where expert knowledge needs to be taken into account, thus improving the objectivity of bankruptcy risk assessment.
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