DIAGNOSTICS OF THE FINANCIAL STATE OF BUSINESS ENTITIES UNDER CONDITIONS OF UNCERTAINTY AND RISK

Abstract

The article is dedicated to the analysis of theoretical and practical foundations of the impact of uncertainty and risk on the financial condition of business entities in the context of conducting diagnostics and identifying possible directions for improving the methodology, taking into account the mentioned influence. The analysis revealed that modern business entities are exposed to a complex set of uncertainties of various origins, which generate risks and can exert a destabilizing effect on their operations. Among the key uncertainties and corresponding risks, the following are identified and characterized: macroeconomic, market, political, technological, consumer behavior uncertainty, regulatory, and resource access uncertainty. In such conditions, the issue of obtaining up-to-date and reliable information for making effective management decisions becomes especially important. To create a relevant informational foundation, it is essential to conduct diagnostics of the financial condition of business entities, which should consider the current realities—uncertainty and risk. It has been established that conducting comprehensive diagnostics of financial condition in today's realities requires an expansion of the use of formalized tools, along with the addition of non-formalized methods. Based on this, the following directions for the development of financial condition diagnostics have been outlined: risk and uncertainty modeling using the VAR model (Value-at-Risk), Monte Carlo simulation, fuzzy logic methods, etc.; forecasting and early risk warning through in-depth analysis of financial ratios in dynamics with the possibility of risk adjustment, the use of machine learning and Big Data; the application of integrated financial condition assessment systems that include multifactor analysis.