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Die Hard: Probability of Default and Soft Information

Author

Listed:
  • Giampaolo Gabbi

    (Banking and Insurance Department, SDA Bocconi School of Management, 20136 Milan, Italy)

  • Michele Giammarino

    (Banca Monte dei Paschi di Siena, 53100 Siena, Italy)

  • Massimo Matthias

    (Department of Business and Law, University of Siena, 53100 Siena, Italy)

Abstract

The research aims to verify whether the credit risk of small and medium-sized enterprises can be estimated more accurately using qualitative variables together with financial information from reports. In our paper, we select qualitative variables within the conceptual framework of the balanced scorecard to assess the credit quality of Italian companies of various sizes, from micro to medium. Data were collected to estimate the company’s resilience following the shock of the financial crisis of 2007–2008. The analysis based on customer size, processes, knowledge, and corporate finance, synthesized with balanced scorecard methodology, allows us to estimate the resilience of companies in a period of crisis. The research highlights the important contribution of qualitative variables for the estimation of credit risk. The implications concern both financial intermediaries and their supervisory functions, and regulators for rating models based on soft forward and countercyclical variables.

Suggested Citation

  • Giampaolo Gabbi & Michele Giammarino & Massimo Matthias, 2020. "Die Hard: Probability of Default and Soft Information," Risks, MDPI, vol. 8(2), pages 1-12, May.
    • Handle: RePEc:gam:jrisks:v:8:y:2020:i:2:p:46-:d:357662
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    References listed on IDEAS

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    1. Carole Howorth & Andrea Moro, 2012. "Trustworthiness and interest rates: an empirical study of Italian SMEs," Small Business Economics, Springer, vol. 39(1), pages 161-177, July.
    2. Giampaolo Gabbi & Andrea Sironi, 2005. "Which factors affect corporate bonds pricing? Empirical evidence from eurobonds primary market spreads," The European Journal of Finance, Taylor & Francis Journals, vol. 11(1), pages 59-74.
    3. Pietro Vozzella & Giampaolo Gabbi, 2020. "What is good and bad with the regulation supporting the SME’s credit access," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, vol. 28(4), pages 569-586, April.
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    6. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
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    10. Camilla Ferretti & Giampaolo Gabbi & Piero Ganugi & Federica Sist & Pietro Vozzella, 2019. "Credit Risk Migration and Economic Cycles," Risks, MDPI, vol. 7(4), pages 1-18, October.
    11. Godbillon-Camus, Brigitte & Godlewski, Christophe, 2005. "Credit risk management in banks: Hard information, soft Information and manipulation," MPRA Paper 1873, University Library of Munich, Germany.
    12. Grunert, Jens & Norden, Lars & Weber, Martin, 2005. "The role of non-financial factors in internal credit ratings," Journal of Banking & Finance, Elsevier, vol. 29(2), pages 509-531, February.
    13. Jens Grunert & Lars Norden, 2012. "Bargaining power and information in SME lending," Small Business Economics, Springer, vol. 39(2), pages 401-417, September.
    14. Giampaolo Gabbi & Michele Giammarino & Massimo Matthias & Stefano Monferrà & Gabriele Sampagnaro, 2020. "Does face-to-face contact matter? Evidence on loan pricing," The European Journal of Finance, Taylor & Francis Journals, vol. 26(7-8), pages 820-836, May.
    15. Giampaolo Gabbi & Pietro Vozzella, 2013. "Asset correlations and bank capital adequacy," The European Journal of Finance, Taylor & Francis Journals, vol. 19(1), pages 55-74, January.
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    Cited by:

    1. Iotti, Mattia, 2023. "Financial evaluation and credit access of agricultural firms," Economia agro-alimentare / Food Economy, Italian Society of Agri-food Economics/Società Italiana di Economia Agro-Alimentare (SIEA), vol. 25(2), October.
    2. Modina, Michele & Pietrovito, Filomena & Gallucci, Carmen & Formisano, Vincenzo, 2023. "Predicting SMEs’ default risk: Evidence from bank-firm relationship data," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 254-268.
    3. Elżbieta Izabela Szczepankiewicz & Windham Eugene Loopesko & Farid Ullah, 2022. "A Model of Risk Information Disclosures in Non-Financial Corporate Reports of Socially Responsible Energy Companies in Poland," Energies, MDPI, vol. 15(7), pages 1-34, April.
    4. Frank Ranganai Matenda & Mabutho Sibanda, 2022. "Determinants of Default Probability for Audited and Unaudited SMEs under Stressed Conditions in Zimbabwe," Economies, MDPI, vol. 10(11), pages 1-28, November.
    5. Mattia Iotti, 2023. "Financial evaluation and credit access of agricultural firms," Economia agro-alimentare, FrancoAngeli Editore, vol. 25(2), pages 31-67.
    6. Keijo Kohv & Oliver Lukason, 2021. "What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains," Risks, MDPI, vol. 9(2), pages 1-19, January.
    7. Elżbieta Izabela Szczepankiewicz, 2021. "Identification of Going-Concern Risks in CSR and Integrated Reports of Polish Companies from the Construction and Property Development Sector," Risks, MDPI, vol. 9(5), pages 1-31, May.

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