US-EU Credit Defaults Stable in April, Tech Sectors Pressurized by AI Impact

Overview

This is a report published by UBS Global Research team analyzing credit defaults and recovery rates for April 2026. The core conclusion is that despite few credit default events and tightening spreads, structural pressures arising from artificial intelligence (AI) disruptions are spreading within the technology and software industries. While default rates for US and high-yield bond markets show fluctuations, they remain generally manageable, and there were no defaults in the European market in April. However, declines in technology stock prices, reduced issuance volume, and rising private lending leverage ratios in the leveraged loan market suggest an increasing dispersion of future default risks.

Core views

Overall default conditions are stabilizing, yet structural diversification is intensifying. In April, the United States recorded two high-yield bond (HY) defaults, fewer than the three defaults in March; both European high-yield bonds and leveraged loans (LL) saw zero defaults. The short-term default rate decreased across most markets, and the proportion of CCC-rated debt has stabilized globally in the leveraged loan market. Nonetheless, signs of distress haven't entirely dissipated: distressed asset ratios in both the US and Europe rose month-over-month, with the US leveraged loan distressed ratio climbing from 8.5% to 9.5%. AI disruption has become the primary source of stress for the technology and software industry. The analysis explores how AI impacts business models, highlighting vast differences in risk exposure across investment portfolios. In the US leveraged loan market, technology sector prices have dropped below 90 cents on the dollar, with new issuance declining year-to-date by 17% (a drop of 31% in Europe). This pressure manifests not only in secondary market price drops but also reflects weakened ability to secure financing in primary markets. The private lending market presents complexity. Although UBS Evidence Lab data showed no major bankruptcies or 'hard' defaults and collateralized loan obligation (CLO) default rates improved in the first quarter, indicators revealed a substantial rise in private lending portfolio leverage in Q1. Despite slight improvements in interest coverage, higher-profile restructuring cases involving companies such as Medallia and Affordable Care indicate accumulating liquidity pressure and default risks in this segment. Rating migration activities show regional disparities. Driven by Centene’s downgraded rating, the scale of 'fallen angels' (bonds transitioning from investment-grade to junk status) significantly increased in the US in April. Conversely, 'fallen angels' activity was absent in Europe, and the number of global 'rising stars' (those moving from junk to investment-grade status) remained limited.

Analysis framework

UBS employs a combination of high-frequency data tracking and structured segmentation analyses. First, it establishes a baseline credit cycle perspective using statistics from the past twelve months (LTM), including issuer default rates, par default rates, and recovery rates. Second, it cross-validates private and public market default realities through bankruptcy filings tracked by UBS Evidence Lab and Standard & Poor’s CLO data, addressing transparency issues in private credit. Finally, by conducting quantity-price splits (like leveraged loan prices and issuance volumes) and industry attributions (especially comparing technology vs. services vs. healthcare), it identifies micro-level credit deterioration stemming from macro trends such as AI disruption, concluding with 'overall stability amidst localized high-risk areas'.

Methodology notes

• Industry/Industrial Analysis FrameworkSupply-demand framework

  Analysis of supply (issuance volume) and demand (prices/yields) in credit markets

  By observing year-on-year changes in leveraged loan issuances (supply contraction) and declines in secondary market prices (weakened demand/confidence), the report gauges credit tightening within specific industries (such as technology).

• Fixed Income & Credit AnalysisSpread and Asset Quality

  Distressed Ratio as a Leading Indicator

  Defining assets with spreads exceeding 1000 basis points or loan prices under 80 cents as 'distressed,' the report uses this metric to anticipate pre-default financial struggles, especially monitoring technology sectors affected by AI impacts.

• Event Gaming & Behavioral FinanceExpectation Differentials/Expectation Management

  Flow Effects of Fallen Angels and Rising Stars

  Tracking rating transitions across thresholds (e.g., investment-grade to junk status) helps assess forced selling/buying pressures, indicating shifts in market liquidity and re-pricing of individual issuers’ creditworthiness.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• Centene

  Adversely Affected/Negative

  Weaknesses

  Facing a credit rating downgrade that caused its bonds to transition from investment grade to high yield ('fallen angel'), thus raising borrowing costs and increasing market sell-offs

  Risks

  Further rating downgrades or liquidity crunches

• Medallia

  Adversely Affected/Negative

  Weaknesses

  Involvement in notable restructuring cases highlights financial strain within the private lending or software services sector

  Risks

  Failed restructuring or low creditor recoveries

• Affordable Care

  Adversely Affected/Negative

  Weaknesses

  Being part of prominent restructuring cases illustrates credit pressures within the healthcare-related lending sphere

  Risks

  Insufficient operating cash flow to cover debts

Key data

• US HY LTM Issuer Default Rate2.3%An increase of 1.1 percentage points year-on-year, with two defaults recorded in April
• US Leveraged Loan LTM Issuer Default Rate2.2%A decrease of 0.8 percentage points year-on-year, with one default recorded in April
• European HY LTM Issuer Default Rate0.8%A decrease of 1.4 percentage points year-on-year, with no defaults recorded in April
• European Leveraged Loan LTM Issuer Default Rate1.7%An increase of 0.9 percentage points year-on-year, with no defaults recorded in April
• US Leveraged Loan Distressed Ratio9.5%An increase month-over-month from a previous value of 8.5%, driven by concerns over AI disruption
• US HY Recovery Rate35%A decrease of 16 percentage points year-on-year
• 2026 Fiscal Year US LL Default Rate Forecast3.75%Baseline scenario forecast by UBS
• 2026 Fiscal Year EU LL Default Rate Forecast3%Baseline scenario forecast by UBS

Impact & implications

The report posits that the current credit market environment is characterized by surface calm masking underlying currents. For investors, while overall default rates have not surged dramatically, technological advancements spurred by AI are reshaping credit fundamentals in the technology and software sectors, increasing refinancing difficulties (declining issuance volumes) and putting downward pressure on valuations (price declines). High leverage ratios in the private lending sector imply potential sudden and hidden future defaults. Cases like Centene highlight the need to monitor large-scale rating changes and their impact on market liquidity.

Risks

• Beyond expectations, the disruptive impact of AI on business models in the technology and software industries could lead to more implicit defaults
• Continuously rising leverage ratios in private lending may trigger liquidity crises
• Geopolitical incidents and policy shocks could reduce asset returns
• High market volatility and thin liquidity might adversely affect valuations

What to watch

• Price movements and issuance volume changes in the technology segments of US and European leveraged loans
• Subsequent alterations in leverage ratios and interest coverage for private lending portfolios
• Rating migration activities among large issuers (similar to Centene) and their implications on the market
• Data on high-profile bankruptcy filings monitored by UBS Evidence Lab