Predicting bank performance with financial forecasts: A case of Taiwan commercial banks

Abstract

Data envelopment analysis (DEA) has been used as a tool for evaluating past accomplishments in the banking industry. However, due to a time lag, the results usually arrive too late for the evaluated banking institutions to react timely. This paper makes advanced predictions of the performances of 24 commercial banks in Taiwan based on their financial forecasts. The forecasts based on uncertain financial data are represented in ranges, instead of as single values. A DEA model for interval data is formulated to predict the efficiency. The predictions of the efficiency scores are also presented as ranges. We found that all the efficiency scores calculated from the data contained in the financial statements published afterwards fall within the corresponding predicted ranges of the efficiency scores which we had calculated from the financial forecasts. The results also show that even the bad performances of the two banks taken over by the Financial Restructuring Fund of Taiwan could actually be predicted in advance using this study.