Private Credit Default Rates: Historical Analysis and Forward Outlook

1. What the Last 15 Years Tell Us

Our dataset combines manager disclosures, CLO trustee data, and public filings across more than 3,000 middle‑market loans. The headline conclusion is simple: defaults cluster in specific sectors and vintages rather than being evenly distributed over time.

• Peak annual default rate of ~6–7% during 2009–2010 for legacy club deals.
• Post‑GFC “direct lending 1.0” vintages (2012–2015) showed annual defaults closer to 1.5–2.0% with low ultimate loss severity.
• COVID period saw technical stress but realized defaults remained lower than market pricing implied—policy support mattered.

2. Defaults vs. Losses

For investors, defaults are only half the story. Loss severity—the percentage written off after restructurings and recoveries—drives long‑term IRR. We segmented outcomes by seniority, sector, and lender protections.

• Senior secured first‑lien loans with strong covenants historically recover 70–80¢ on the dollar on average.
• Unitranche facilities show a wider distribution, with outcomes heavily dependent on documentation and sponsor support.
• Losses are disproportionately concentrated in cyclical sectors (energy, discretionary retail) and in transactions with add‑on acquisition risks underwritten aggressively.

3. Scenario Analysis Going Forward

We model three macro paths over a five‑year horizon—soft landing, mild recession, and prolonged stagflation—and map them to expected default and loss rates for private credit.

• Soft landing: defaults drift toward long‑run averages (~2%) with modest loss severity.
• Mild recession: defaults rise toward 3–4% for aggressive vintages, with lower severity where structures are conservative.
• Stagflation: pressure comes from both higher base rates and slower growth, exposing weaker interest coverage profiles.

4. How This Shapes Our Portfolio Design

We translate the research into practical portfolio limits: concentration caps by sector and sponsor, leverage ceilings by business model, and minimum covenant and documentation standards.

• Higher required spreads for cyclical sectors where historical loss distributions are fatter in the tails.
• Preference for sponsors with demonstrated workout capabilities and aligned economics.
• Reserving more “risk budget” for vintages where underwriting standards are likely to be looser (late‑cycle periods).

The conclusion is not that private credit is “safe” or “risky”, but that outcomes are highly path‑dependent. A data‑driven view of defaults allows us to size risk in a way that is consistent with the role private credit plays in a client’s broader portfolio.