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Understanding the potential for future failure of a firm is a critical concern within the business domain. This study aims to explore and compare various Machine Learning techniques utilized for predicting financial distress in Small and Medium-sized Enterprises (SMEs). In the paper we consider several Machine Learning models using a restricted dataset comprising selected Italian SMEs from 2017 to 2021, focusing on specific financial indicators. The objective is to evaluate the effectiveness of these models in forecasting financial distress.

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Corporate Financial Distress Prediction with Machine Learning Techniques

  • 章节

  • 发表日期：

    2025年

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  • Claudio Pizzi,
  • Federico Farsura,
  • Marco Corazza,
  • Francesca Parpinel

摘要

Understanding the potential for future failure of a firm is a critical concern within the business domain. This study aims to explore and compare various Machine Learning techniques utilized for predicting financial distress in Small and Medium-sized Enterprises (SMEs). In the paper we consider several Machine Learning models using a restricted dataset comprising selected Italian SMEs from 2017 to 2021, focusing on specific financial indicators. The objective is to evaluate the effectiveness of these models in forecasting financial distress.