The Omega Score: An improved tool for SME default predictions

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.

KEYWORDS:

• Omega Score
• default prediction modeling
• small and medium-sized enterprises
• machine-learning techniques

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ An SME is deemed in default when its bank account is blocked for a period of 30+ or 60+ days due to its inability to fulfill payment obligations to creditors, including suppliers, financial institutions, and the government.

² For brevity, here we report only the 60-day version of the Omega Score. Altman et al. (2022) presented both 60- and 30-day versions of the formula.

³ The first version of the Z Score included five financial ratios: Working Capital/Total Assets, Retained Earnings/Total Assets, EBIT/Total Assets, Market Value Equity/BV of Total Debt, and Sales/Total Assets (Altman, 1968).

Additional information

Funding

This work was supported by the Croatian Science Foundation under the project IP-CORONA-2020-12-1064.