ASSESSMENT AND FORECASTING OF STRESS RESISTANCE OF THE RUSSIAN BANKING SECTOR WITHIN THE FRAMEWORK OF RESTORING GROWTH UNDER CHANGED EXTERNAL AND INTERNAL CONDITIONS

Abstract

Relevance of the topic. In the conditions of increasing turbulence of the global business environment and instability of the financial system, rapid quantitative and qualitative transformations in the credit system under various financial, economic, social, political and other factors, banking supervision and regulation authorities, as well as the management of credit institutions are forced to constantly improve traditional approaches to assessing financial risks and develop new methods of early detection. In this regard, more and more attention is paid to a variety of stress testing methods that can determine the vulnerabilities of certain areas of banking and the banking system as a whole. The project was carried out as part of the research work carried out by the Laboratory for Structural Research of the Institute of Applied Economic Research of the Russian Presidential Academy of National Economy and Public Administration in 2021. Research method or methodology. The research work is based on the principle of consistency in the study of various economic phenomena, as well as the appropriate selection methods for the object of research. This use case assumes a variety of scientific and methodological tools: the use of methods of scientific abstraction, economic and statistical analysis, functional and structural analysis, a systematic approach, comparison methods, graphical and tabular techniques for visualizing statistical and other data, methods of expert analysis, methods of graphical modeling and others. Research results: an analysis was carried out to systematize approaches to stress testing, to develop criteria for ranking stress testing methods by areas of banking and by risk factors; stress testing models in the Russian banking system were optimized, tested and validated; prepared a scientific basis for the stability of the banking system in the event of extreme yet likely events.

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