Predicting multilateral trade credit risks: comparisons of Logit and Fuzzy Logic models using ROC curve analysis

The results show that FL exceeds Logit in terms of overall classification accuracy and prediction accuracy. However, by incorporating measurement in the form of ROC curves, Logit is proven to outperform FL in classifying non-default firms. This suggests that though FL is superior in overall accuracy and in classifying default firms, Logit is preferable in situations where higher accuracy in classifying non-default firms is preferred. The stability of the models is also demonstrated.