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The Omega Score: An improved tool for SME default predictions

Author

Listed:
  • Edward I. Altman
  • Marco Balzano
  • Alessandro Giannozzi
  • Stjepan Srhoj

Abstract

The Omega Score, a novel small and medium-sized enterprise (SME) default predictor developed by Altman et al. in 2022, combines indicators related to financial ratios, payment behavior, and management and employees variables that play an important role in predicting SME defaults. Built with machine-learning techniques and rich dataset information, the Omega Score can be used to categorize an SME into one of the following three groups: healthy, moderate-risk, and high-risk. The Omega Score can be utilized by financial institutions to reduce lending errors and minimize loan defaults, support policy makers in implementing effective restructuring policies, assist credit analytics firms in assessing creditworthiness, assist investors in allocating funds, and asset managers to support decision-making processes.

Suggested Citation

  • Edward I. Altman & Marco Balzano & Alessandro Giannozzi & Stjepan Srhoj, 2023. "The Omega Score: An improved tool for SME default predictions," Journal of the International Council for Small Business, Taylor & Francis Journals, vol. 4(4), pages 362-373, October.
    • Handle: RePEc:taf:ucsbxx:v:4:y:2023:i:4:p:362-373
    DOI: 10.1080/26437015.2023.2186284
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    Cited by:

    1. Alessandro Bitetto & Paola Cerchiello & Stefano Filomeni & Alessandra Tanda & Barbara Tarantino, 2024. "Can we trust machine learning to predict the credit risk of small businesses?," Review of Quantitative Finance and Accounting, Springer, vol. 63(3), pages 925-954, October.

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