Analytical Methods for Assessing and Forecasting Financial Standing of Credit Institutions
| Autor: | Y. M. Beketnova |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0106 biological sciences
central bank of the russian federation Index (economics) License revocation Economics Econometrics and Finance (miscellaneous) Early detection Development fnancial standing 01 natural sciences 03 medical and health sciences 010608 biotechnology Management of Technology and Innovation Business and International Management Reliability (statistics) 030304 developmental biology method of the main components 0303 health sciences Actuarial science Regression analysis predictive models Money laundering prudential supervision Central bank HG1-9999 Russian federation credit institutions Business anti-money laundering Finance |
| Zdroj: | Финансы: теория и практика, Vol 23, Iss 1, Pp 79-95 (2019) |
| ISSN: | 2587-7089 2587-5671 |
| DOI: | 10.26794/2587-5671-2019-23-1-79-95 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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