LAUSR

This study aims to verify the potential of combining corporate prior payment behavior and Kohonen maps for small enterprise default prediction. Logistic regression, discrete-time hazard models, and Kohonen maps were applied to a sample of 1200 Italian small enterprises, and two categories of prediction models were calculated: one exclusively based on financial ratios and the other based also on payment behavior-related variables. The main findings are as follows: (1) Kohonen map-based trajectories give significantly higher prediction accuracy rates compared to both logistic and hazard models; (2) the longer the forecast horizon and/or the smaller the firm’s size, the greater are the improvements in prediction accuracy obtainable through Kohonen maps; (3) accuracy rates are higher when company payment behavior-related variables are added to financial ratios as default predictors; and (4) the smaller a firm, the greater is the increase in accuracy obtainable by adding payment behavior-related variables.