Application of Discriminate Function Analysis to Identification of Financially Unstable Banks of Russia

A. P. Chumachenko (), O. L. Kritski and O. A. Belsner
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A. P. Chumachenko: National Research Tomsk Polytechnic University
O. L. Kritski: National Research Tomsk Polytechnic University
O. A. Belsner: National Research Tomsk Polytechnic University

Chapter Chapter 7 in Global Economics and Management: Transition to Economy 4.0, 2019, pp 65-76 from Springer

Abstract: Abstract The article introduces the research in the field of economics, international financial reporting and statistics. In this paper the mathematical regression model of bankruptcy for banks is constructed. Special attention is paid to accounting data. It should be written correctly and accurately applied to the models. Even small ambiguity leads to big error of results. The main advantage of bankruptcy models is the allowance of finding of a point after which the enterprise starts working at a loss, and also forecasting for future period. Data are collected, summary tables, schedules are constructed and the analysis is made. We will try to offer an alternative to these models such that the model is suitable for the Russian reality and branch feature of banks. Changes in the banking legislation of Russia gave impetus to the revocation of licenses of most credit institutions in the country. The article establishes the reasons for such measures on the part of the Bank of Russia.

Keywords: Discriminate analysis; Banking sector of economy; Regression analysis; Probability of bankruptcy; Financial stability (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-26284-6_7

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DOI: 10.1007/978-3-030-26284-6_7

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