Open AccessThe Potential of "numerical approaches" in banking supervision: Possibility of proactive identification by the bank of Russia for problem credit institutions in the banking sector using data science methods
Author(s) -
Anastasiia Sterlikova
Publication year - 2020
Publication title -
kant
Language(s) - English
Resource type - Journals
ISSN - 2222-243X
DOI - 10.24923/2222-243x.2020-37.44
Subject(s) - license , identification (biology) , state (computer science) , business , bank credit , data bank , computer science , finance , actuarial science , accounting , financial system , telecommunications , botany , algorithm , biology , operating system
The article discusses the possibility of machine learning model for analyzing the state of credit institutions by their performance indicators and assessing the likelihood of revoking a license from a single participant. The conclusion is made about the possibility of using the machine learning model in the supervisory activities of the Bank of Russia as an auxiliary tool.