Predicting bank performance: A distributional approach

Data envelopment analysis (DEA) has been used as a tool for evaluating past accomplishment in the banking industry. However, due to a time lag, the results usually arrive too late for the evaluated banking institutions to react. This study makes advanced predictions of the performance of twenty-four commercial banks in Taiwan based on their financial forecasts. The forecasts based on uncertain financial data are represented in ranges and treated as stochastic data. A simulation technique is adopted to obtain the efficiency distribution of each commercial bank. Our finding is that all the efficiency scores calculated from the data published fall within the corresponding predicted ranges of the efficiency scores calculated from the financial forecasts. More importantly, the results show that the bad performance of two of the banks, which were taken over by the Financial Restructuring Fund of Taiwan, had been predicted in advance using the approach of this study.