Private Credit Fears Deepen With UBS Warning of 15% Defaults

UBS has raised its worst‑case forecast for private credit defaults to about 14–15%, mainly in a scenario where AI causes rapid, severe disruption to corporate borrowers, especially in tech and software.

What UBS is actually saying

• UBS strategists, led by Matthew Mish, now see private credit defaults reaching up to 15% in a tail scenario, up from roughly 13% they outlined only weeks ago.

• The “new” catalyst is an explicit shock: rapid, severe AI-driven disruption that compresses margins and cash flows for a large cohort of borrowers.

• This is framed as a stress test, not a base case, with parallel worst‑case default ranges of roughly 3–6% for U.S. high‑yield, 8–10% for leveraged loans, and 14–15% for private credit.

Where we are today vs 15%

• Reported private credit default rates are currently around 2.5% (Q4 2025 estimate ≈2.46%), far below the 14–15% tail outcome UBS is flagging.​

• The gap between current reality and the UBS ceiling is the “expectation gap” they emphasize: fundamentals still look benign, but the worst‑case ceiling just moved higher.

• UBS and others point to warning signs: more “bad PIK” structures, looser documents, and emerging liquidity issues (e.g., retail‑oriented vehicles tightening or freezing withdrawals).

Why AI is central to the tail risk

• UBS’s revision is specifically tied to a scenario where AI adoption leads to aggressive disruption, putting pressure on revenues and employment in affected sectors.

• Direct lenders heavily exposed to software and tech‑enabled companies are viewed as particularly vulnerable if AI accelerates competitive shake‑outs and business model obsolescence.

• A separate bearish note cited by markets research suggests AI could push U.S. unemployment into double digits by late this decade, which would amplify credit stress across segments.

How to interpret the risk for private credit

• A 15% default rate would be far above historical stressed outcomes in broadly syndicated loans and high yield, implying a very painful scenario for late‑vintage private credit funds, NAV lenders, and BDCs.

• Concentrated exposures (software, venture‑backed growth, cyclical sponsors) and weaker underwriting vintages would likely drive a disproportionate share of losses.

• At the same time, UBS and others stress this is not the central forecast; it is a tail‑scenario stress meant to capture a specific AI shock rather than a generic cyclical recession.

Segment comparison (UBS tail scenario)