The rationale for the hierarchy of correlation between the key rate and the level of financial risks of a corporation: theoretical and practical aspects

Abstract

Introduction. The high key rate of the Bank of Russia leads to an increase in the cost of borrowed capital for the activities of con­struction corporations, negatively affecting their financial results, which justifies the need for a well-founded choice of methods for assessing its im­pact on the manifestation of financial risks in the corporation, proposing measures for their regulation. Goal. The study intends to develop a toolkit for regulating and assessing the impact of the key rate on the level of financial risks of a construction corporation that make a hierarchical correlation. Materials and methods. Analysis (comparative, financial), synthesis, financial ratios method, logical, etc. Results and discussion. The article evalu­ates interconnected absolute (revenue, interest expense, profit before tax, profit before interest on loans, income tax: EBIT, profit before interest on loans, taxes, depreciation of fixed assets, intangible assets: EBITDA, long-term / short-term debt obligations, net debt), relative (share of long-term / short-term liabilities in liabilities, interest coverage ratio, net debt / EBITDA) indicators characterizing the state of different types of profit, the impact of interest expenses on the financial result of a construction corporation under the influence of changes in the key rate; the main proposals for regulat­ing financial risks at the micro level are formulated. Conclusion. The following key proposals are formulated for regulating financial risks caused by the high key rate of the Bank of Russia at the micro level: 1) changing the composition and structure of the debt portfolio towards increasing long­term debt; 2) hedging financial risks using interest rate swaps; 3) accelerating the construction cycle; 4) creating a reserve liquidity fund; 5) develop­ing a digital ecosystem, use of BIM design, creation of predictive analysis tools using artificial intelligence and machine learning technologies; 6) business diversification. Their effective implementation is achieved through comprehensive application.