ECONOMIC SECURITY THREAT MODELLING OF A COMMERCIAL BANK IN A GLOBALIZED ECONOMY

Olena Dymchenko; Olha Rudachenko; Patrizia Gazzola

doi:10.21272/mer.2020.89.11

Olena Dymchenko O. M. Beketov Kharkiv National University of Urban Economy
Olha Rudachenko O. M. Beketov Kharkiv National University of Urban Economy
Patrizia Gazzola University of Insubria

DOI: https://doi.org/10.21272/mer.2020.89.11

Keywords: commercial bank, threats, economic security, modelling, neural networks, management solutions

Abstract

In the paper, one develops a set of models for diagnosing threats to the economic security of a commercial bank, which allows improving the quality of decisions forming and making on managing the safe functioning and development of the bank. The bank's economic security research system has been developed, it includes 3 main blocks: research information space creation; assessment and analysis of the security of a commercial bank; generalization, and formation of decisions on the economic security of a commercial bank. The research made it possible to draw an inference of a theoretical, methodological, and applied nature that reflects the solution of the tasks set following the purpose of the study. A set of models has been built with modern tools of economic and mathematical modelling to improve the quality of decisions made to manage the bank's security and reduce the risks of threats. A model for calculating the bank's economic security indicator has been developed, which includes the following main stages: the construction of a structural scheme taking into account the rules of the theory of banking functioning security, then the terms and their membership functions are set for each input and output variable of the fuzzy inference system under consideration. Results of the response surface for the model are shown in the figure on the graphs of the dependence of the bank's economic security indicator on various input components. The paper requires that it is convenient to diagnose the state of economic security of a bank using fuzzy logic, this allows getting a clear quantitative representation of economic security state of the bank, as the indicators used for diagnostics may be indistinct and approximate and this a priori cannot give an adequate result when accurately calculated.

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