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While software exposure is a serious concern for credit markets, it is unlikely to cause a systemic crisis. Mitigating factors include low leverage in BDCs (around 2x), minimal direct linkage to the core banking system, and a recent corporate credit cycle characterized by de-leveraging rather than aggressive debt accumulation.
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.
While AI represents the largest segment of corporate debt, the risk is not yet systemic. The current build-out is primarily financed by the massive free cash flow from operations of megacap tech companies, not excessive leverage. The real danger emerges when this shifts to debt financing that cash flow cannot support.
Unlike the public equity markets, software exposure in credit markets is concentrated in private, not public, companies. An estimated 80% of these issuers are private, and 50% are rated B- or lower, creating a unique and more challenging risk profile due to lower credit quality and less transparency.
The greatest systemic threat from the booming private credit market isn't excessive leverage but its heavy concentration in technology companies. A significant drop in tech enterprise value multiples could trigger a widespread event, as tech constitutes roughly half of private credit portfolios.
Unlike the great financial crisis, recent credit cycles have been confined to specific sectors (e.g., energy, and now potentially software) rather than broad, macro-driven downturns. Without the ingredients for a deep recession, current stress in software is unlikely to cause contagion across the wider credit markets.
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.
While MAG7 companies fund AI spending with cash flow, the real danger is other firms using debt, especially private credit. This transforms potential corporate failures from isolated events into systemic risks that can cause broader economic ripple effects.
Once considered safe due to low CapEx and recurring revenue models, the technology sector now shows significant credit stress. Investors allowed higher leverage on these companies, but the sharp rise in interest rates in 2022 exposed this vulnerability, placing tech alongside historically troubled sectors like media and retail.
Evaluating AI-driven disruption in BDC software portfolios is complex because these are private companies with no public financial reporting. Analysts must effectively re-underwrite each investment from scratch to determine which companies are at risk and which might benefit, making traditional risk assessment inadequate.
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.