Abstract
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.
Highlights
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 financing
Summary
Аналитические методы оценки и прогнозирования финансового состояния кредитных организаций. А Н Н ОТА Ц И Я Цель статьи — предложить новый подход к оценке и прогнозированию финансового состояния кредитных организаций и раннему выявлению тех из них, которые имеют высокие риски отзыва лицензии. Методом главных компонент факторного анализа найден интегральный показатель благонадежности кредитных организаций. Позволяющие по характеру изменения интегрального показателя благонадежности прогнозировать ухудшение состояния кредитных организаций. Что приведенный подход позволяет выявлять потенциально проблемные кредитные организации, требующие принятия соответствующих мер со стороны Центрального банка Российской Федерации при осуществлении им функций пруденциального надзора. Ключевые слова: кредитные организации; финансовое состояние; метод главных компонент; прогнозные модели; противодействие отмыванию преступных доходов; Центральный банк Российской Федерации; пруденциальный надзор.
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