Introduction. Bankruptcy is the most important element of legal regulation of modern market relations. National economy has to be able to predict a potential default in the general system of anti-crisis management. Therefore, it needs advanced techniques and tools of anti-crisis diagnostics for the timely management solutions.
Study objects and methods. The analytical information presented in this work is multi-tiered and reflects the all-Russian, industrywide, regional, regional-industry, and corporate levels. The research featured agricultural enterprises of the Kemerovo region. The information underwent three types of formatting: legislative, statistical, and diagnostic.
Results and discussion. During the first stage, the authors assessed external factors and trends in individual components of anti-crisis diagnostics in a given economy sector against the background of all-Russian and industry-wide trends. Enterprises appeared sensitive to bankruptcy risk; the trend decreased in 2014–2018. The second stage involved developing of a selective-indicative model for diagnosing insolvency of Russian organizations. The model took into account regional and industrial traits and focuses on large and medium-sized agricultural enterprises in the region. The model selected general indicators from a set of studied parameters, formed from fifty financial ratios presented in twenty-two of the most well-known methods of anti-crisis analysis. Bankruptcy was diagnosed on the basis of preference matrix, according to the criterion of the active use of coefficients in analytical practice. A comparative analysis of bankruptcy criteria and indicators made it possible to define the degree of adequacy of the set of indicators. Four analytical vectors were defined after thematic grouping of the identified indicators: balance sheet liquidity (current liquidity ratio), property and capital structure (financial dependence and asset mobility ratios), security (working capital ratio with own circulating assets), efficiency (economic profitability, or loss ratio, and the ratio of business activity in the market). The equation of rating assessment of the insolvency probability demonstrated the total impact of these indicators, taking into account their individual “equity participation” in the aggregate of key parameters.
Conclusion. The final set of general exponents of the diagnostic model can be qualified as a neuro-analogue of “classical” models that ignores the values of the regression coefficients, which are usually not adapted to Russian realities. The model built on the basis of bankruptcy indicators, taking into account their individual “equity participation” in the rating number, can be used as a flexible methodological tool for diagnosing bankruptcy in the national economy of Russia.
Practice of crisis management in agricultural enterprises
