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Diameter Capital's analysis reveals a dangerous concentration in private credit, with roughly 50% of loans exposed to AI disruption risk (software, IT services). For a debt instrument with limited upside, this level of single-factor exposure is described as "crazy portfolio management."

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Private credit, a booming financial sector, faces an unmodeled risk from AI-driven job displacement. Current risk models aren't designed for a scenario where high-FICO-score, white-collar professionals—the core of many consumer loan portfolios—face widespread income disruption. This represents a potential systemic vulnerability.

Software, once a defensive haven for credit investors, faces a major threat from AI. AI's ability to standardize data and workflows could disrupt legacy SaaS companies, making the 30% of direct lending portfolios concentrated in software a significant, overlooked risk.

A large concentration of private credit lending is in the software sector, particularly SaaS businesses. The rise of powerful AI tools that can replicate software services cheaply poses a direct threat to the viability of these companies, creating a hidden risk concentration within private credit portfolios where there are few hard assets to recover.

Private credit funds are exposed on two fronts: they are financing the massive debt rounds for AI infrastructure and also hold debt for traditional SaaS companies. As AI companies pitch a future where they render SaaS obsolete, it creates instability and default risk across these private credit portfolios.

Software's heavy presence in leveraged loan (<15%) and private credit (>20%) portfolios makes these markets more vulnerable to AI disruption than high-yield bonds (<5%). This concentration risk is already visible, with the distressed universe of leveraged loans growing 50% year-to-date, a stress not yet seen in the bond market.

A significant portion of private credit portfolios consists of loans to software companies, which were underwritten based on predictable, recurring revenue. AI is now fundamentally disrupting these business models, threatening to devalue the very collateral that underpins billions of dollars in these 'safe' loans.

The rise of powerful AI tools threatens the business models of many software-as-a-service (SaaS) companies. This jeopardizes their future revenue, making it difficult to refinance loans originated at near-zero interest rates. This is a fundamental, technology-driven risk to a large segment of private credit.

Private credit funds have taken massive market share by heavily lending to SaaS companies. This concentration, often 30-40% of public BDC portfolios, now poses a significant, underappreciated risk as AI threatens to disintermediate the cash flows of these legacy software businesses.

A significant portion of private credit is concentrated in software companies. Many of these loans were made when rates were low, often with high leverage and weak terms. The emergent threat of AI-driven disruption to their business models now adds a new layer of fundamental risk to this already vulnerable cohort.

Roughly one-third of the private credit and syndicated loan markets consist of software LBOs financed before the AI boom. Goodwin argues this concentration is "horrendous portfolio construction." As AI disrupts business models, these highly levered portfolios face clustered defaults with poor recoveries, a risk many are ignoring.