The back side of banking in Russia: forecasting bank failures with negative capital

International Journal of Computational Economics and Econometrics. 2017. Vol. 7. No. 1/2. P. 170–209.

Karminsky A. M., Kostrov A.

Since 2013, we have observed an increasing number of failed Russian banks with negative capital and falsified financial reporting. We use previously unavailable data for the period 2010 – 1H2015 to develop a logit model predicting the probability of bank failure with negative capital. In order to do so, we suggest solutions for the class imbalance and variable selection problems. The models chosen are confirmed to be robust and have longer forecasting horizons compared to previous research. Also, we implement a novel probability-based approach to the out-of-sample forecasting evaluation which confirms a good fit of the selected models to data. The model predicts bank failures in three quarters and finds 33% of actual failures among 5% of banks with the highest predicted probability to fail (out-of-sample). In addition, we make available previously unpublished banking data for Russia

Keywords: Central Bank of Russia, financial reporting, probability of default, logit model, Creditors, fraudul, mismanagement

Publication based on the results of: Формирование системы моделей для управления кредитным риском банка в условиях финансовой нестабильности (2016)