The Research on Stability of the Russian Banking System by Machine Learning Methods

Oleg A. Bayuk (), Dmitry V. Berzin and Bogdan A. Timov
Additional contact information
Oleg A. Bayuk: Financial University, Moscow, Russia

Journal of Reviews on Global Economics, 2018, vol. 7, 618-625

Abstract: The problem of stability of the Russian banking system is investigated. To describe the state of a commercial bank, we use a system of indicators, proposed by F.T. Aleskerov and his colleagues. For predicting the development of banking system, the machine learning system implemented in the Azure ML is used. To optimize the work of this software, it is suggested to use integral indicators.

Keywords: Commercial bank; banking system; stability of the banking system; machine learning; decision tree. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.lifescienceglobal.com/independent-jour ... ine-learning-methods

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:lif:jrgelg:v:7:y:2018:p:618-625

Access Statistics for this article

Journal of Reviews on Global Economics is currently edited by Michael McAleer and Chia-Lin Chang

More articles in Journal of Reviews on Global Economics from Lifescience Global
Bibliographic data for series maintained by Faisal Ameer Khan ( this e-mail address is bad, please contact ).