Is The AI Triggered Meltdown In Private Credit Overblown?

The $3 trillion private credit market is experiencing strain as fears over AI’s impact on software companies ripple through lending. While private credit has historically thrived on high yields and lower volatility, the recent selloff in SaaS stocks has exposed vulnerabilities in loans made before 2024, which did not account for AI as a major risk factor. Private credit expanded rapidly post-2008 financial crisis as banks pulled back from middle-market lending, with business development companies (BDCs) offering retail investors high-yield loans to software firms. These loans targeted SaaS companies for their recurring revenue and asset-light models, but the sector’s sudden downturn has left lenders reassessing risk. Equity prices of major private credit firms have fallen sharply, signaling broader market concerns about the stability of the underlying loans. Early signs of stress include surging redemption requests from investors seeking to pull capital from non-traded BDCs and interval funds. Some funds have exceeded their quarterly redemption caps, forcing them to either honor partial withdrawals or sell loans at discounts. This liquidity crunch highlights the mismatch between investor expectations and the illiquid nature of private credit. Industry observers argue the current stress is typical for the asset class, which has historically delivered high yields despite higher volatility. They note that private credit loans are not repriced daily like public markets, meaning the impact of AI-driven selloffs may be overstated for well-structured borrowers. However, the situation underscores the need for lenders to adapt to evolving risks in the tech sector. The broader private credit market remains resilient, with yields outpacing public market alternatives, but the AI-driven downturn has exposed gaps in risk assessment. As lenders tighten gates and reassess portfolios, the sector may see further repricing, though long-term investors may find opportunities in undervalued assets.