UBS analyst Matthew Mish warns that a severe AI disruption could trigger massive losses across private credit markets, with defaults potentially reaching 14-15% in private credit and 8-10% in leveraged loans. The bank estimates total losses could approach $420 billion in defaults and $300 billion in actual losses across high-yield, leveraged loan, and private credit markets.

In this tail scenario, credit availability would tighten dramatically with private credit and loan issuance potentially falling 50-75% year over year. UBS highlights that financial institutions hold $2.5 trillion in non-bank financial institution loans, with $1.6-1.8 trillion in drawn exposures at risk. The analysis shows 30-40% of these exposures are tied to private equity, private credit, BDCs, or structured vehicles considered higher risk.

UBS notes private credit has grown rapidly, now representing 6% of U.S. GDP, with stress signals already visible. Defaults are between 3% and 5%, leverage has climbed to 7.5-8x in some sectors, and interest coverage ratios remain pressured. The bank warns that technology is especially vulnerable to AI disruption, and the interconnectedness between private and public credit markets means stress is unlikely to remain contained.