UBS Projects 13% Default Rate in AI Disruption Scenario — What It Means for Crypto‑Lending Yields

UBS modeled an aggressive AI disruption scenario that could push leveraged loan default rates to 13% — a level far above the historical 1‑2% baseline — signaling a sharp rise in credit risk for borrowers reliant on leveraged finance (Crypto Briefing).

Credit Spreads Widens as Lenders Reprice AI Risk — Higher Costs Loom for PE‑Backed AI Firms

Loan investors are demanding stricter covenants and higher interest spreads, reflecting concern that AI breakthroughs could destabilize cash flows of software‑dependent borrowers (Crypto Briefing). This pushback has already moved the average spread on leveraged loans to software firms from roughly 350 basis points to over 450 basis points, a jump not seen since the 2022 rate‑hike cycle (Crypto Briefing).

The widening spread directly raises the cost of new debt for private equity‑backed AI companies, which often rely on leveraged loans to finance growth initiatives and acquisitions (Crypto Briefing). As borrowing expenses climb, these firms may delay expansion plans or seek alternative financing, potentially slowing revenue growth.

UBS analysts note that the spread movement is a leading indicator of deteriorating credit quality, especially when coupled with rising default projections under AI stress scenarios (Analyst view — UBS, per Crypto Briefing).

Debt Deal Delays Signal Borrower Reluctance — Software and Infrastructure Companies Pause Refinancing

Several software firms have voluntarily postponed upcoming debt offerings after deeming current terms unattractive, a clear sign that borrowers are waiting for more favorable conditions (Crypto Briefing). When issuers step back from the market, it reflects a belief that the cost of capital is temporarily too high relative to expected returns.

CoreWeave, an AI infrastructure provider, encountered investor resistance on its proposed loan terms, prompting the company to shelve the deal until lenders adjust their expectations (Crypto Briefing). This reluctance is not isolated; similar delays have been reported across the broader software sector, indicating a broad‑based reassessment of leverage appetite.

The pause in issuance reduces the supply of new leveraged loans, which can further tighten market conditions and contribute to upward pressure on yields for existing debt (Crypto Briefing).

UBS Stress Tests Show Default Rates Could Triple Under Moderate AI Shock — Portfolio Losses Mount

Under baseline conditions, UBS estimates leveraged loan default rates at 1‑2%, consistent with the long‑run average for the asset class over the past decade (Crypto Briefing). A moderate AI‑driven disruption scenario lifts that range to 3‑5%, representing a potential tripling of loss expectations for lenders (Analyst view — UBS, per Crypto Briefing).

In an aggressive scenario where AI adoption rapidly displaces legacy software models, defaults could spike as high as 13%, a level that would erase recent equity cushions in many private credit portfolios (Crypto Briefing). Such outcomes would likely trigger markdowns on loan holdings and increase provisioning requirements for funds.

Investors should monitor whether actual default trends begin to align with the moderate 3‑5% band, as a sustained move toward that range would validate lenders’ current risk pricing (Crypto Briefing).

Funding Costs Cascade Through Private Credit Chain — Banks Raise Rates on Funds, Trickle Down to Portfolio Companies

U.S. banks have responded to heightened perceived risk by increasing the interest rates they charge to private credit funds that originate leveraged loans (Crypto Briefing). When the funds’ cost of capital rises, they pass those expenses onto the portfolio companies they finance, creating a daisy‑chain effect.

This transmission mechanism means that even firms not directly seeking new debt face higher effective borrowing costs when existing loans are refinanced or when funds seek additional leverage for new investments (Crypto Briefing). The cumulative impact can compress EBITDA margins across leveraged portfolios, particularly for companies with thin cash‑flow buffers.

Private credit has grown to roughly $2 trillion in assets over the past decade, with a substantial portion allocated to software and tech‑adjacent lending that historically relied on predictable cash flows (Crypto Briefing). The sector’s size amplifies the potential systemic effect of any widespread repricing of risk.

Equity Market Reaction Reveals Investor Anxiety — Private Credit Managers’ Shares Drop Amid Valuation Concerns

Shares of major private credit managers have reacted negatively to the unfolding credit‑tightening narrative, with Blue Owl Capital falling approximately 10% in early February 2026 as AI concerns weighed on borrower valuations (Crypto Briefing). Ares Management and Blackstone also posted notable declines over the same period, reflecting a broad‑based reassessment of the sector’s earnings outlook.

The equity sell‑off suggests that market participants are pricing in lower future fee income and higher credit losses for these managers, even before any actual rise in defaults materializes (Crypto Briefing). Such valuation pressure can make it more expensive for private credit firms to raise new capital, further constraining their lending capacity.

Investors are advised to watch two key developments: whether the spread widening stabilizes or accelerates, and whether default rates in leveraged software portfolios begin to tick up toward the UBS moderate scenario of 3‑5% (Crypto Briefing).