Business Environment Resilience Control Using Trainable Analytical Models
DOI:
https://doi.org/10.17308/econ.2026.1/13604Keywords:
socio-economic systems, trainable models, targeted managerial intervention, pre-crisis statesAbstract
Subject. Enhancing the resilience of the business environment and reducing the scale of crisis phenomena are among the key objectives of socio-economic development under conditions of high heterogeneity of enterprises that constitute this environment and limited resources for managerial influence. Universal regulatory measures often fail to ensure the desired effectiveness of managerial impact, which necessitates the use of more precise and targeted management instruments based on the early identification of pre-crisis states of individual economic entities.
Purpose. The purpose of the study is to demonstrate the possibility of applying trainable analytical models to manage business environment resilience through forecasting the financial insolvency of enterprises as its key elements.
Methodology. To achieve this purpose, we used trainable analytical models based on machine learning methods and applied them to open data arrays from accounting (financial) statements. We applied data preprocessing procedures and accounted for their temporal structure, which allowed us to improve the stability and practical applicability of the resulting predictive estimates.
Results. The study demonstrates that the use of trainable analytical models makes it possible to generate predictive estimates of financial insolvency of enterprises that can be used to refine the directions of managerial intervention and to account for potential systemic consequences of financial instability of individual participants in the business environment.
Conclusions. The results of the study can be applied in systems for monitoring business environment resilience, as well as in the development and implementation of economic policy measures and managerial decisions aimed at targeted intervention and prevention of systemic crisis phenomena.
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