#2764. Machine-learning models for bankruptcy prediction: do industrial variables matter?

November 2026publication date
Proposal available till 30-05-2025
5 total number of authors per manuscript4030 $

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Journal’s subject area:
Economics, Econometrics and Finance (all);
Statistics, Probability and Uncertainty;
Geography, Planning and Development;
Earth and Planetary Sciences (miscellaneous);
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Abstract:
The paper proposes a predictive model specifically designed for the Italian economy that classifies solvent and insolvent firms a year ahead using the AIDA Bureau van Dijk dataset for the period 20XX to 2015. We apply a full set of bankruptcy forecasting models, including both traditional and more sophisticated machine learning methods, and add a set of industry/regional variables to the financial ratios used in the literature.
Keywords:
firm distress analysis; industrial variables; logistic regression; machine learning

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