Predicting SMEs' default risk: Evidence from bank-firm relationship data

This paper uses a probit model on a unique dataset of 13,081 Italian firms and 111 co-operative banks involved in the lending process to provide empirical evidence suggesting that the use and violations of credit lines and long-term loan overruns predict one-year and two-year probability of default (PD). The analysis controls for balance sheet indicators and time varying bank characteristics, captured by bank-time fixed effects. When combined with accounting data, credit-related indicators obtained from private internal banking sources improve small and medium-sized enterprises' (SMEs) default prediction. The marginal benefit of the bank-firm specific information is also assessed by comparing the default prediction accuracy of a model that incorporates accounting information with that of a full model including private information. In terms of heterogeneity, the association between the balance sheet indicators and data on bank-firm relationships and default probability can vary across sectors and geographies. This highlights the importance for banks of specific analysis to better assess risk at the firm level. (c) 2023 Board of Trustees of the University of Illinois. Published by Elsevier Inc. All rights reserved.