Banking failure prediction: a boosting classification tree approach

Abstract

The recent financial crisis shows that failure of some financial institutions can cause other banks to fail and ultimately cause damage to the financial system worldwide. Eurozone banks that experienced either liquidity or solvency problems during the finan- cial markets turmoil were bailed out by their national governments with the financial support and supervision of the European Union. This paper applies the boosted classification tree methodology to predict failure in the banking sector and identifies four key scor- ecard variables that are worth tracking closely in order to anticipate and prevent bank financial distress. The data used in this study comprises 2006-2012 annual series of 25 financial ratios of 155 banks in the Eurozone. The findings indicate that the greater the size and the higher the income from non-operating items and net loans to deposits, the more likely is bank failure; conversely, the higher the Interbank ratio the lower the chances of bank financial distress. For the sake of their own financial soundness, banks should fund lending activities through clients' deposits and should avoid relying excessively on non-recurring sources of income