can be obtained using the so-called “reject” option. Namely, the patterns that are the most likely to be misclassified are rejected (i.e., they are not classified); they are then handled by more sophisticated procedures (e.g., a manual classification is performed). However, handling high reject rates is usually too time-consuming for application purposes. Therefore, a trade-off between error an...

Credit scoring models are normally built using only applicants who have been previously accepted for credit. Such non-random sample selection may produce bias in estimated model parameters and accordingly model predictions of repayment performance may not be optimal. Previous empirical research suggests that omission of rejected applicants has a detrimental impact on model estimation and predic...