Early Warning Signals to Predict Islamic Bank Failure

Abstract


 The paper empiricialy tests the use of various stability factors as early warning signals that can effectively predict the failure in Islamic banking institutions. These early warning signals enable the regulatory and supervisory authorities to take timely corrective action to safeguard the interest of fund providers such as depositors, investment account holders, creditors as well as other stakeholders. Using a 10-year panel data of 65 Islamic banks from 13 banking systems in the Middle East, North Africa, Asia and Europe, this study uses six stability indicators of CAMELS supervisory framework in a logistic model to see their effecitveness in predicting distress in Islamic banks. The model is then extended with the alternative capital are leverage ratios as well as macroeconomic variables in order to see whether simple leverage ratio offers better estimation results than the complex, risk weighted measures as debated by (Haldane, 2012).