Journal of Financial Services Research

, Volume 44, Issue 1, pp 111–129 | Cite as

Modelling Credit Risk for Innovative SMEs: the Role of Innovation Measures

  • Chiara Pederzoli
  • Grid Thoma
  • Costanza Torricelli


Small-medium enterprises (SMEs) encounter financial constraints when they try to obtain credit from banks. These constraints are particularly severe for innovative SMEs. Thus, developing models for innovative SMEs that provide reliable estimates of their probabilities of default (PD) is important because the PDs can also serve as ratings. We examine the role of innovative assets such as patents in credit risk modelling due to their signaling value. Specifically, we add to a logit model two innovation-related variables in order to account for both the dimension and the value of the patent portfolio. Based on a unique data set of innovative SMEs with default years of 2005–2008, we show that, although the value of the patent portfolio always reduces the PD, its dimension reduces the firm’s riskiness only if coupled with an appropriate equity level.


Innovative small-medium enterprises Default probability Patent value R&D productivity 

JEL classification

G21 G32 C25 O34 



We would like to thank for comments and suggestions an anonymous referee, Kazu Motohashi, Elisabeth Müller, Raffaele Oriani, Francesco Pattarin, Georg Licht, and participants at the CEFIN Workshop (Modena, 2010), 4th CSDA International Conference on Computational and Financial Econometrics (CFE'10, London), 4th ZEW Conference on Economics of Innovation and Patenting (2011, Mannheim), 3rd Workshop on The Output of R&D Activities: Harnessing the Power of Patents Data (2011, Sevilla), International Risk Management Conference (2011, Amsterdam), 15th International Conference on Insurance: mathematics and Economics (2011, Trieste). Authors acknowledge financial support from the Italian University Ministry. Usual caveat apply.


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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Chiara Pederzoli
    • 1
    • 4
  • Grid Thoma
    • 2
    • 4
  • Costanza Torricelli
    • 3
    • 4
  1. 1.Department of Quantitative Methods for Economics and BusinessUniversity of Milano-BicoccaMilanItaly
  2. 2.Department of Mathematics and InformaticsUniversity of CamerinoCamerinoItaly
  3. 3.Department of EconomicsUniversity of Modena and Reggio EmiliaModenaItaly
  4. 4.CEFINCentro Studi Banca e FinanzaModenaItaly

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