Abstract

The article proposes an approach to analyzing reliability factors of commercial banks during the 2014–2017 systemic crisis in the Ukrainian banking system, using the Kohonen self-organizing neural networks and maps. As a result of an experimental study, data were obtained on financial factors affecting the stability of a commercial bank in a crisis period. It has been concluded that during the banking crisis in Ukraine in 2014–2017, the resource base of a bank was the main factor of this bank stability. The most preferred sources of resources were funds from other banks (bankruptcy rate of 5.7%) and legal entities (bankruptcy rate of 8%), and the least stable were funds from individuals (bankruptcy rate of 28.5%). The relationship between financial stability and the amount of capital and the structure of bank loans is less pronounced. However, one can say that banks that focused on lending to individuals experienced a worse crisis than banks whose main borrowers were legal entities. The tools considered in the article (the Kohonen self-organizing neural networks and maps) allow for efficiently segmenting data samples according to various criteria, including bank solvency. The “hazardous” zones with a high bankruptcy rate (up to 49.2%) and the “safe” zone with a low rate of bankruptcy (6.3%) were highlighted on the map constructed. These results are of practical value and can be used in analyzing and selecting counterparties in the banking system during a downturn.

Highlights

  • In Ukraine, the banking crisis began in 2014 and continued until mid2017

  • The tools considered in the article allow for efficiently segmenting data samples according to various criteria, including bank solvency

  • In order to analyze the stability factors of commercial banks in a crisis period, the article substantiates the feasibility of using approaches based on the philosophical principle of “from the general to the particular”, which is realized through data clustering with subsequent identification of particular features of the clusters obtained

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Summary

INTRODUCTION

In Ukraine, the banking crisis began in 2014 and continued until mid2017. The formal end to the crisis can be considered a statement made at the beginning of 2017 by the head of the NBU on the transition to the final stage of cleaning the banking system (National Bank of Ukraine, 2017). An analysis of the past crisis provides an opportunity to obtain unique information about the stability factors of Ukrainian commercial banks in the context of economic collapse, to develop methods for identifying reliable banks and forecasting possible failures, and to compare the results with the findings on the stability of foreign banks in similar conditions (LopezIturriaga & Sanz, 2015). Together, this will clarify knowledge about the banking system stability and the genesis of crisis phenomena

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