Predicting Bank Insolvency in the Middle East and North Africa

Abstract

This paper uses a panel of annual observations for 198 banks in 19 Middle East and North Africa countries over 2001-12 to develop an early warning system for forecasting bank insolvency based on a multivariate logistic regression framework. The results show that the traditional CAMEL indicators are significant predictors of bank insolvency in the region. The predictive power of the model, both in-sample and out-of-sample, is reasonably good, as measured by the receiver operating characteristic curve. The findings of the paper suggest that banking supervision in the Middle East and North Africa could be strengthened by introducing a fundamentals-based, off-site monitoring system to assess the soundness of financial institutions.