Defaulting alone: SME owner numbers and credit risk in Hungary

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Article Date: 03 Jun 2025
Article URL: https://www.tandfonline.com/doi/full/10.1080/00472778.2025.2502090?af=R
Article Image: https://www.tandfonline.com/action/showCoverImage?journalCode=ujbm20

Summary

This paper uses the Hungarian National Credit Registry (2007–2019) to examine how the number of owners in SMEs affects credit default probability. The author finds that micro-enterprises with a single owner have roughly twice the default probability of micro firms with four or more owners. The protective effect of multiple owners weakens as firm size grows.

The study also shows that changes in owner numbers increase credit risk in the short term (immediately after the change). Over the longer term, however, surviving firms tend to exhibit lower default probabilities — suggesting that ownership adjustments ultimately lead to better-managed firms. Methodologically, owner counts are grouped as 1, 2, 3 and 4+ and the paper argues that precision/recall metrics are preferable to AUROC when dealing with rare default events.

Key Points

Data source: comprehensive National Credit Registry of Hungary covering 2007–2019.
Micro-enterprises with one owner face about double the default probability versus micro firms with four or more owners.
The beneficial effect of having multiple owners diminishes as firm size increases.
Owner-number changes raise credit risk in the short run but survivors show lower default rates in the long run.
Owner counts analysed in four categories: 1, 2, 3, and 4+.
The paper recommends precision and recall over AUROC for evaluating default-prediction models in rare-event settings.
Findings are relevant for lenders, credit-scoring design and SME governance policy.

Context and relevance

This research is important for credit risk practitioners, regulators and policy-makers. It links corporate governance (owner structure) to measurable lending outcomes and suggests that ownership structure and recent ownership changes should be considered in credit assessment models. The long-run improvement among survivors also speaks to firm selection and post-change adaptation processes, relevant in post-crisis SME support and resilience planning.

Author style

Punchy: clear, data-driven and policy-relevant. Because the paper uses near-complete registry data, its conclusions carry weight for lenders and regulators designing SME credit policies — so the details are worth a careful read if you work in risk, supervision or SME finance.

Why should I read this?

Short version: if you take or underwrite SME risk, this tells you a simple but powerful fact — single-owner micro firms are riskier, changes in ownership spike risk short-term, but survivors tend to improve. Read it to tweak scoring models, lending criteria or SME support programmes — saves you guessing and could improve decision-making.