МЕТОДОЛОГИЯ ДИАГНОСТИКИ ФИНАНСОВОЙ НЕУСТОЙЧИВОСТИ БАНКОВ
This article is devoted to the issues of timely detection of negative trends in bank’s operation on the basis of data from financial statements. The authors determined that revealing certain sequences of events in credit institutions activities (negative development scenarios) permits to reduce the risk of license withdrawal prediction error. A set of the most common negative scenarios was discovered and described by the authors.
Discovering such scenarios based on the financial statement data allows all interested parties to be proactive in preventing closing down of a credit institution at the initiative of the Bank of Russia or in protecting themselves from negative consequences of this event. The conclusions were confirmed by the mathematical modeling results using classification trees from CART methodology, which have never been applied before to predict license withdrawal.