Properties of accounting and finance information and their effects on the performance of bankers and models in predicting company failure

Abstract

When the number of cues provided to a banker for a decision is increased it may (1) increase their information load (number of relevant cues), (2) increase their data load (number of irrelevant cues), and (3) reduce their uncertainty. Models, on the other hand, are not affected by information or data load. The results from this research show that as the number of cues provided to bankers increases, uncertainty reduces, data load increases, but information load is unaffected. The uncertainty reduction increases the decision accuracy of both the bankers and models. Due to the data load experienced by the bankers but not the models, the models have superior performance. The implications for future practice and research are discussed.