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BUSINESS INFORM №1-2018

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21

Section: Economic and Mathematical Modeling
UDC 004.032.26:336.71
Markov M. Y.
Using the Artificial Neural Networks for Forecasting the Risk of Bankruptcy of Banks (p. 146 - 151)

The article is aimed at finding the optimal structure of artificial neural network to solve the problem of forecasting the bankruptcy of banks and researching the efficiency of use of the neural networks model for the realities of Ukrainian banking sphere. Results of the research testify that the best accuracy of forecasts for 1-1,5 years showed the model on the basis of the multilayer perceptron with 10 and 2 neurons in the hidden layers. The developed neural networks model can be used as an alternative to statistical methods, as it has shown better results. Prospect for further research in this direction is development of a complex system of support for decision-making for banking institutions, which would include forecasting risks for bank, analysis of the bank’s financial condition and identification of financial problems using innovation instruments and technologies, ensuring the monitoring and control of risks of banking institution. The developed neural networks model can become one of elements of the complex system.
Keywords: banks, forecasting, bankruptcy, risk, modeling, artificial neural networks, neural networks model.
Fig.: 3. Tabl.: 6. Formulae: 1. Bibl.: 8.

Markov Mykhailo Ye. – Postgraduate Student, Volodymyr Dahl East Ukrainian National University (17 Ioanna Pavla II Str., Kyiv, 01042, Ukraine)
Email: [email protected]

Article is written in Ukrainan
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Reference to this article:
Markov, Mykhailo Ye. (2018) “Using the Artificial Neural Networks for Forecasting the Risk of Bankruptcy of Banks.” Business Inform 1:146–151.


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