Analytical Methods for Assessing and Forecasting Financial Standing of Credit Institutions
The objective of the article is to propose a new approach to assessing and forecasting fnancial condition of credit institutions and to early detection of those that have high risks of license revocation. An integrated reliability index of credit institutions has been revealed by the method of the m...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | Russian |
| Published: |
Government of the Russian Federation, Financial University
2019-02-01
|
| Series: | Финансы: теория и практика |
| Subjects: | |
| Online Access: | https://financetp.fa.ru/jour/article/view/820 |
| Summary: | The objective of the article is to propose a new approach to assessing and forecasting fnancial condition of credit institutions and to early detection of those that have high risks of license revocation. An integrated reliability index of credit institutions has been revealed by the method of the main components of the factor analysis. Credit institutions have been clustered by means of the k-average method. It has been established that acting credit institutions at a relatively small Euclidean distance from the mathematical expectation of credit institutions, liquidated at a given moment of time, bear potential risks of engaging in illegal activities, money laundering and terrorist fnancing. Constructed regression models allow forecasting deterioration of credit institutions by the nature of the change in the integrated reliability index. The author concludes that this approach makes it possible to identify potentially problematic credit institutions requiring appropriate measures from the Central Bank of the Russian Federation through prudential supervision functions. |
|---|---|
| ISSN: | 2587-5671 2587-7089 |