AI disruption and private credit: what is the risk scenario?

Investing.com -- UBS analyst Matthew Mish stated in a note on Wednesday that investors are increasingly focused on the possibility of a “rapid, severe AI disruption,” outlining how such a tail event could ripple across private credit and broader leveraged finance markets.

While the bank stressed this is “not our baseline,” it said its updated analysis provides a clearer catalyst and new default and spread forecasts.

UBS explained that in a tail scenario, U.S. high-yield, leveraged loan and private credit defaults “could rise to 3–6%, 8–10% and 14–15%, respectively.”

Across these markets, “defaults and losses would approach $420bn and $300bn.” Credit availability would tighten materially, with private credit and loan issuance potentially falling 50–75% year over year.

The bank also warned that financial institutions would be exposed through “NFBI loans, currently $2.5tn.”

In a severe disruption, UBS estimates “$1.6–1.8tn in total drawn exposures,” with 30–40% tied to private equity, private credit, BDCs or structured vehicles that UBS would consider higher risk.

The analyst reiterated that private credit has grown rapidly relative to the economy, now representing 6% of U.S. GDP. Stress signals are said to be visible, with defaults are between 3% and 5%, leverage has climbed to 7.5–8x in some sectors, and interest coverage ratios remain pressured.

Sector concentration amplifies potential shocks, with portfolios heavily weighted toward services, technology and healthcare.

UBS believes technology is “especially vulnerable to disruption from AI adoption or rapid retrenchment.” The interconnectedness between private and public credit markets also means stress is unlikely to remain contained.

While the market is not in crisis, UBS cautioned that “the ingredients are present for a severe credit cycle,” even as idiosyncratic risks continue to create single-name opportunities.

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