US private credit default rates could rise to levels not seen since the Financial Crisis. UBS: In a worst-case scenario of rapid AI disruption, defaults could reach 14–15%

US private credit default rates could rise to levels not seen since the Financial Crisis. UBS: In a worst-case scenario of rapid AI disruption, defaults could reach 14–15%

Analysts at UBS Group AG have revised their worst-case scenario for U.S. private credit defaults, projecting rates could surge to 14–15% if rapid artificial intelligence advancements disrupt corporate borrowers, particularly in the software sector according to UBS analysis. This represents a two-percentage-point increase from their previous forecast less than a month ago, driven by heightened concerns over AI's potential to render certain business models obsolete. The private credit industry, valued at $1.8 trillion, has drawn comparisons to the 2008 financial crisis due to its heavy concentration in software and services, with estimates suggesting 40% of sponsor-backed loans are tied to the sector.

Current default rates in private credit stand at 3–5%, but signs of stress are emerging, including rising interest paid-in-kind (PIK) payments nearing post-pandemic highs. Recent actions by firms like Blue Owl Capital Inc.—which halted redemptions and sold assets—have amplified market unease, triggering a $2.4 billion drop in its market value and spooking peers such as Ares Management Corp. and Apollo Global Management Inc. According to Bloomberg reporting. UBS warns that AI-driven disruption could trigger cascading defaults, with software firms particularly vulnerable due to high leverage and weak covenants.

While some experts argue the risks are overstated, citing robust corporate balance sheets and diversification opportunities, others caution that contagion could spread to leveraged loans and high-yield bonds, with UBS raising default forecasts for those sectors to 10% and 6%, respectively. Jamie Dimon of JPMorgan Chase & Co. has reiterated warnings about "credit market cockroaches," drawing parallels to pre-2008 excesses. Conversely, figures like Third Point's Dan Loeb emphasize that private credit's asset-liability match reduces systemic risk, though he acknowledges significant loan impairments are likely.

The debate underscores broader tensions between AI's transformative potential and its risks to leveraged industries, with investors closely monitoring defaults, covenant breaches, and liquidity pressures in the coming months.