Combining Kohonen maps and prior payment behavior for small enterprise default prediction

Francesco Ciampi (), Valentina Cillo and Fabio Fiano
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Francesco Ciampi: University of Florence
Valentina Cillo: Link Campus University
Fabio Fiano: Link Campus University

Small Business Economics, 2020, vol. 54, issue 4, No 6, 1007-1039

Abstract: Abstract 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.

Keywords: Enterprise default; Small enterprises; Kohonen map; Prediction models; Financial ratios; Company payment behaviors; C35; C41; C45; C53; G21; G23; G33; L26 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s11187-018-0117-2

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