Developing a decision rule to predict failure: The case of savings and loan associations

The relative costs of misclassifying institutions by their financial health is an issue that concerns researchers. In this paper, a model and decision rule are developed that improve the probability of identifying those Savings and Loans that are predicted not to fail, but are actually failing. For obvious reasons, stakeholders in those institutions are very much interested in avoiding this type I error. The study also makes available evidence that the examination of Z-scores can be useful in identifying other financial institutions that may experience financial failure.