XXV Edition

1-2 December 2016"

The Relative Predictive Strength of Different Lending Technologies

Brighi Paola, University of Bologna
Lucarelli Caterina, University of Ancona
Venturelli Valeria, University of Modena and Reggio Emilia

Using a proprietary database of lending decisions to small and medium-sized enterprises (SMEs), the paper investigates how banks cope with adverse selection dilemma. Based on an intertemporal framework spanning over ex-ante decision period and ex-post check period, we qualify wrong and correct lending decisions. To this end, we disentangle the role of hard and soft information within the loan decision processes, and explore the predictive power of the different lending technologies. Empirical evidence suggests that both hard information and relationship lending variables are significant in predicting correct choices, as well as in increasing the probability of errors, because of adverse selection effect and soft budget constraint problems. Findings suggest that adverse selection can be better controlled by a durable bank-firm relationship, as well as by an atomistic loan decision process, at the local level. Differently, a loan decision-making exclusively based on hard-financial information may lead to adverse selection errors.

Area: Banking

Keywords: Adverse selection; Lending technologies; SMEs; Relationship lending; Soft and hard information.

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