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Increasing the Predictive Power of Financial Distress models—The Case of the New Alert System Proposed by the Italian Nccaae

In: New Challenges for the Banking Industry

Author

Listed:
  • Federico Beltrame

    (University of Udine)

  • Giulio Velliscig

    (University of Udine)

  • Gianni Zorzi

    (Ca’ Foscari University)

  • Maurizio Polato

    (University of Udine)

Abstract

This chapter develops and tests an alternative alert system to predict firms’ financial distress which combines the benefits of the Z-score’s multivariate discriminant model and the National Council of Chartered Accountants and Accounting Experts’ predictors. Using a sample of 43 viable and 43 non-viable Italian SMEs, the authors compare the predictive accuracy of the mentioned models over the period 2015–2019. Based on the results, they elaborate revised versions of both approaches, aligned to current socio-economic conditions. The authors also provide an alternative combined model. The analysis of the two baseline approaches showed complementary results, with the Z-score overperforming the alert system in predicting non-viable firms, whereas the opposite emerged on viable firms. The revised versions showed enhanced predictive accuracy. The authors’ contribution enriches the post-pandemic debate on financial distress prediction models by pointing out the limits of the NCCAAE alert system and suggesting an alternative and better performing model.

Suggested Citation

  • Federico Beltrame & Giulio Velliscig & Gianni Zorzi & Maurizio Polato, 2023. "Increasing the Predictive Power of Financial Distress models—The Case of the New Alert System Proposed by the Italian Nccaae," Palgrave Macmillan Studies in Banking and Financial Institutions, in: Santiago Carbó-Valverde & Pedro J. Cuadros-Solas (ed.), New Challenges for the Banking Industry, chapter 0, pages 305-335, Palgrave Macmillan.
  • Handle: RePEc:pal:pmschp:978-3-031-32931-9_12
    DOI: 10.1007/978-3-031-32931-9_12
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