This paper proposes an empirical model to identify and forecast banking fragility episodes using information on the credit funding sources. We predict the probability of occurrence of such episodes 0, 3 and 6 months ahead employing a Bayesian Model Averaging of logistic regressions. The exercises use monthly balance sheet data since the middle of the nineties for the banking system of nine merging economies: Brazil, Colombia, Croatia, Czech Republic, Mexico, Peru, Poland, Taiwan and Turkey. Our findings suggest that the increasing use of wholesale funds to support credit expansion provides warning signals of banking frailness. The in-sample and out-of-sample predictions indicate that the proposed technique is a suitable tool for forecasting short-term financial fragility events. Therefore, monitoring these funds through our tool could become useful in prudential practice.
