Issue |
E3S Web Conf.
Volume 91, 2019
Topical Problems of Architecture, Civil Engineering and Environmental Economics (TPACEE 2018)
|
|
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Article Number | 08065 | |
Number of page(s) | 5 | |
Section | Environmental Management and Environmental Economics | |
DOI | https://doi.org/10.1051/e3sconf/20199108065 | |
Published online | 02 April 2019 |
The use of accounting information for assessing the economic security of commercial banks
1 Volgograd State Technical University, 2 Degtyareva str., Volgograd, Russia, 400006
2 Saint-Petersburg State University of Economics, 21 Sadovaya str., St. Petersburg, Russia, 191023
3 South West State University, 94 50 let Oktiabria str., Kursk, Russia, 305040
4 Volgograd State Agricultural University, 26 Universitetsky av., Volgograd, Russia, 400002
* Corresponding author: plotnikov_2000@mail.ru
The authors studied the use of accounting information for assessing the level of economic security of commercial banks. The article substantiates the choice of financial indicators of credit institutions as input parameters of the neural network. The analytical platform Deductor Studio Academic was chosen as the instrumental environment for assessing the level of economic security of banks. With its help, cluster analysis was performed. The division of the initial set of credit institutions into subsets (economic security classes) used the k-means method with splitting into three clusters: cluster 0 - “Optimal level of economic security”, cluster 1 -“Conditionally optimal level of economic security”, cluster 2 - “Low level of economic security”. The proposed data model with the results of the division of credit institutions into clusters according to the financial indicators of International Financial Reporting Standards made it possible to draw conclusions about the level of economic security of credit institutions and justify the choice of accounting information indicators for implementing a neural network approach to banking research.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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