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Reading: UBS Warns Credit Market May Be ‘Invisible Powder Keg’ Amid AI Disruption
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UBS Warns Credit Market May Be ‘Invisible Powder Keg’ Amid AI Disruption

News Desk
Last updated: February 14, 2026 3:44 am
News Desk
Published: February 14, 2026
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UBS Group has raised significant concerns regarding the credit market, suggesting it may represent an ‘invisible powder keg’ amid the ongoing disruption caused by artificial intelligence (AI). The investment bank’s warnings come as Wall Street grapples with a downturn in software stocks, complicating the market landscape for many companies.

Matthew Mish, Head of Credit Strategy at UBS, stated in a recent research report that the market is undergoing a rapid and aggressive repricing due to unexpected advancements in AI technology. He forecasts a potential spike in defaults within the leveraged loan and private credit sectors, estimating an increase of $75 billion to $1.2 trillion by the end of next year. This figure is grounded in an expected rise of 2.5 percentage points in leveraged loan default rates, translating to approximately $1.5 trillion, alongside a 4 percentage point increase in private credit defaults, amounting to about $2 trillion.

During an interview with CNBC, Mish commented on the market’s slow response to these changes, noting the rapid acceleration in AI development has prompted a significant shift in assessment strategies. Companies developing models like those from Anthropic and OpenAI are forcing investors to reassess risk timelines, indicating that the disruptive effects of AI are not far-off issues but are occurring now.

Investors have begun to redefine their understanding of AI’s impact on technology sectors. The prevailing narrative has shifted from viewing AI as a broad boon for all technology firms to a more cutthroat environment where only select companies thrive. This change has led to sell-offs not only in software stocks but also extending to seemingly unrelated sectors like finance, real estate, and trucking.

Mish categorized companies into three tiers based on their vulnerability to AI disruption:

  • Tier One: Companies developing foundational AI models, such as Anthropic and OpenAI, are viewed as potential future leaders in the industry.
  • Tier Two: Investment-grade firms like Salesforce and Adobe are recognized for their strong balance sheets, positioning them to navigate challenges from emerging competition effectively.
  • Tier Three: Private equity-backed software and data service companies, burdened by high debt levels and dependence on traditional business approaches, are considered at highest risk.

The UBS report also outlines a more concerning ‘tail risk’ scenario. In this situation, default rates could double compared to the baseline estimates, leading many companies to lose access to financing. Mish warned that this could trigger a credit crunch in the loan market, resulting in a broad repricing of leveraged credit. Such a scenario could mirror past events like the junk bond sell-off in the energy sector or the credit freeze experienced during the internet bubble.

Despite these warnings, UBS analysts maintain that the actual outcomes will hinge on several critical factors: how quickly large enterprises adopt AI, the pace of advancements in AI technology, and the refinancing requirements facing the market. Currently, it is estimated that around 20% of leveraged loans and private credit will need refinancing by 2028, suggesting ongoing risks will persist over the coming years.

While UBS is not yet calling for an imminent tail risk scenario, Mish acknowledged that the market is trending in that direction.

Importantly, the concerns raised focus on leveraged loans and private credit, noted for being among the riskiest categories in the corporate credit arena. These financial instruments typically fund lower-grade companies, many of which are highly leveraged and supported by private equity. As AI technologies disrupt traditional Software-as-a-Service (SaaS) models, these entities are feeling unprecedented pressure on their cash flows. There is growing anxiety that those unable to adapt swiftly to the technological evolution may become early casualties in this transformative period, with the credit markets left to absorb their outstanding debts.

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