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A credit risk model with an automatic override for innovative small and medium-sized enterprises

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  • Silvia Angilella
  • Sebastiano Mazzù

Abstract

The goal of this paper is to build an operational model for assessing creditworthiness of innovative small and medium-sized enterprises. To this purpose, a novel multicriteria methodology is implemented through a simulation approach within the context of the ELECTRE TRI-based framework. The model is applied to a database, retained from AIDA, involving a sample of Italian innovative small and medium-sized enterprises. The main finding is twofold. From a theoretical point of view, the credit rating model proposed allows to incorporate an override in the credit class, as required by Basel II in all the cases in which the availability of data is insufficient to describe the risk factors or a judgmental rating model is advised, as well as in innovative small and medium-sized enterprises. From an operational point of view, this methodology could be a useful tool for banks’ innovative lending processes, because of the lack of a credit model in this context.

Suggested Citation

  • Silvia Angilella & Sebastiano Mazzù, 2019. "A credit risk model with an automatic override for innovative small and medium-sized enterprises," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1784-1800, October.
    • Handle: RePEc:taf:tjorxx:v:70:y:2019:i:10:p:1784-1800
    DOI: 10.1080/01605682.2017.1411313
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    Cited by:

    1. Francesco Ciampi & Alessandro Giannozzi & Giacomo Marzi & Edward I. Altman, 2021. "Rethinking SME default prediction: a systematic literature review and future perspectives," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2141-2188, March.
    2. Jiang, Cuiqing & Yin, Chang & Tang, Qian & Wang, Zhao, 2023. "The value of official website information in the credit risk evaluation of SMEs," Journal of Business Research, Elsevier, vol. 169(C).
    3. D’Apolito, Elisabetta & Galletta, Simona & Iannuzzi, Antonia Patrizia & Labini, Stefania Sylos, 2024. "Sustainability and bank credit access: New evidence from Italian SMEs," Research in International Business and Finance, Elsevier, vol. 69(C).
    4. Marco Corazza & Giovanni Fasano & Stefania Funari & Riccardo Gusso, 2021. "MURAME parameter setting for creditworthiness evaluation: data-driven optimization," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 295-339, June.
    5. Yu Zhao & Huaming Du & Qing Li & Fuzhen Zhuang & Ji Liu & Gang Kou, 2022. "A Comprehensive Survey on Enterprise Financial Risk Analysis from Big Data Perspective," Papers 2211.14997, arXiv.org, revised May 2023.
    6. Taghizadeh-Hesary, Farhad & Yoshino, Naoyuki & Fukuda, Lisa & Rasoulinezhad, Ehsan, 2021. "A model for calculating optimal credit guarantee fee for small and medium-sized enterprises," Economic Modelling, Elsevier, vol. 95(C), pages 361-373.
    7. Silvia Angilella & Maria Rosaria Pappalardo, 2021. "Assessment of a failure prediction model in the energy sector: a multicriteria discrimination approach with Promethee based classification," Papers 2102.07656, arXiv.org.

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