Express Diagnostics of Bankruptcy Risks Based on a Selective-Indicative Model

Abstract

Effective bankruptcy risk diagnostics may prevent a financial crisis in Russia’s national economy. The article introduces a novel express tool for bankruptcy diagnostics based on early recognition of alert signs, crisis fields, and preliminary pre-crisis assessment. The tool is a selective-indicative model with regional and industrial specifications. Regional and industrial exhibitors served as benchmark indicators. The empirical material included statistics, reference materials, and financial reports from agricultural organizations in the period of external economic shocks (2014–2022), Kemerovo region, Russia. First, the alert signals of bankruptcy risk were identified based on 22 original methods of financial crisis forecasting. After that, they were assessed for practical popularity. The identified default risk signals were linked to the existing criteria of financial insolvency, subjected to economic interpretation, and classified. After fixing the analytical reference vectors, the authors identified the share of each indicator. By determining the latest results of model exponents, they ensured the direction of analytical reference vectors to maximize the disabled function. The next stage involved systematization and synthesis of alert signals into a diagnostic model to be developed into a gradation indicator. After fixing the signal analytical base, the model was tested to formulate conclusions about its adaptability in the current economy. The resulting model relied on the share of each alert signal of bankruptcy risk in the rating number. It may improve the quality of predictive diagnostics. As the model needs few exponents, it provides a high-speed crisis analysis.