Consideration of Uneven Misclassification Cost and Group Size for Bankruptcy Prediction

Abstract

Despite a larger number of approaches developed for predicting bankruptcy over the past three decades, rare research has considered the effects of misclassification cost and group size. Uneven cost of misclassification results from Type I (misclassify a healthy company as a failure) and Type II errors (misclassify a failed company as healthy), which are seldom considered. Without accounting for unevenness in misclassification cost, the classifier is developed based on minimizing total misclassification errors to improve the hit-ratio for classification performance. This not only results in poor decision capability, but also causes bias towards the larger group. This paper explores the issues of uneven misclassification costs and imbalanced group size by applying an asymmetric-stratified data envelopment analysis to bankruptcy prediction. The results show a tradeoff between hit-ratio and misclassification cost when Type II error cost is ten times over that of Type I, that is, the higher the hit-ratio is, the greater the resulting misclassification costs are. By incorporating different proportions of Type II error costs to Type I into the classification procedures, the proposed approach provides greater flexibility to decision makers for credit evaluation or bankruptcy prediction based on different risk attitudes and situations.

Predictive Potential and Risks of Selected Bankruptcy Prediction Models in the Slovak Business Environment

“…When making decision on what model is the most appropriate we have to look on the costs of wrong prediction. As the error of Type I (prediction of bankrupt company as a non-bankrupt) is higher than the error of Type II (prediction of non-bankrupt company as a bankrupt one) we should put emphasize on bankruptcy prediction accuracy (Bellovary et al 2007;Kuo 2013;Gepp, Kumar 2008;etc.). In spite of this, many authors evaluate models only on the level of total accuracy.…”

“…While validating the selected models: Altman model, indexes IN01 and IN05 and Ohlson model, we concluded that the Ohlson model is inappropriate in predicting the financial situation of enterprises in the Slovak Republic despite the fact, that its overall predictive ability is high. Its uselessness results from the insufficient level of bankruptcy prediction accuracy, resulting in the formation of errors type I with high costs (Bellovary et al 2007;Kuo 2013;Gepp, Kumar 2008;etc.). This conclusion is supported also by findings of research conducted by Robertson and Mills (1991), Morris (1997), Giacosa et al (2016), etc.…”

“…-Auditors can spend more costs for peer review of financial problems to avoid bankruptcy. When comparing the costs associated with the error type I and II it is clear that the error type I is associated with higher costs compared to the error type II (Bellovary et al 2007;Kuo 2013;Gepp, Kumar 2008;etc. ).…”