The landscape of private credit markets is currently shrouded in uncertainty, largely influenced by the emergence of AI-powered tools that are beginning to challenge software companies, a crucial borrower demographic for private lenders. This shift not only affects investor sentiment but could also reshape the financial frameworks within the industry.
Recently, the software sector faced heightened pressures following the announcement of new AI tools by Anthropic, an artificial intelligence company. This revelation triggered a sell-off in shares of software data providers, igniting concerns that these innovations could disrupt traditional software business models by offering complex professional services that companies currently monetize.
In the wake of these developments, stocks for asset managers holding substantial private credit portfolios saw significant declines. Investors are increasingly anxious about the potential ramifications of AI on borrowers’ operational models, which could adversely affect cash flow and elevate default risks. For instance, Ares Management plummeted by over 12% last week, while Blue Owl Capital fell by more than 8%. Similarly, KKR experienced a nearly 10% decline, while TPG lost around 7%. Both Apollo Global and BlackRock saw declines of over 1% and 5%, respectively. In contrast, the S&P 500 experienced a minor downturn of about 0.1%, while the tech-centric Nasdaq index fell by 1.8%.
This situation intensifies existing concerns regarding the private credit market, which must now navigate the implications of AI disrupting the software sector, particularly as many buyouts have been financed with complex, illiquid loans, as noted by industry analysts. According to PitchBook, “Enterprise software companies have been a favored sector for private credit lenders since 2020,” emphasizing that significant unitranche loans—often a preferred financing mode in the private credit landscape—have been tied to software and tech enterprises.
Data from PitchBook indicates that software represents a considerable portion of the loans held by U.S. business development companies (BDCs), accounting for about 17% of all investments by number of deals—second only to commercial services. This exposure could prove financially risky if AI integration outpaces the ability of borrowers to adapt. In an alarming projection, UBS Group has indicated that, under aggressive disruption scenarios, default rates in U.S. private credit could soar to 13%, far exceeding the estimated stress levels for leveraged loans and high-yield bonds, which UBS anticipates could reach around 8% and 4%, respectively.
Jeffrey C. Hooke, a senior lecturer in finance at Johns Hopkins Carey Business School, commented, “Private credit loans to many software companies could lead to significant issues if they encounter difficulties.” However, he also highlighted that liquidity issues and loan extensions have been persistent concerns in private credit before the latest AI developments. “Many private credit funds have encountered challenges in liquidating their loans,” he remarked, suggesting that the recent AI news merely adds another layer of complexity to an already stressed sector.
The mounting list of warnings aligns with earlier concerns about the $3 trillion private credit industry, which grapples with issues of leverage, opaque valuations, and the risk that isolated challenges may reveal systemic vulnerabilities. JPMorgan’s Jamie Dimon previously cautioned about potential “cockroaches” within private credit, indicating that distress in one borrower could hint at broader unseen troubles.
Kenny Tang, head of U.S. credit research at PitchBook LCD, noted that AI disruption could represent a credit risk for private lenders involved with certain Software & Services sector borrowers. He pointed out that some companies may be lagging behind in AI adaptation while others are leading the charge. Additionally, Tang mentioned that software and services firms account for a substantial share of payment-in-kind (PIK) loans, which allow borrowers to defer cash interest payments. While this structure can benefit fast-growing companies by allowing them the time to strengthen revenue and cash flow, it poses risks if a borrower’s financial health declines, potentially transforming deferred interest into a credit complication.
Mark Zandi, chief economist at Moody Analytics, emphasized the difficulties in fully grasping the risks due to the sector’s opacity. He expressed concerns over the rapid rise in AI-related borrowing, rising leverage, and insufficient transparency, labeling them as “yellow flags.” He warned, “There will undoubtedly be significant credit problems. While the private credit industry may currently absorb these losses adequately, this might change within a year if the current trend in credit growth persists.”
In conclusion, the intersection of AI innovation and private credit markets presents both challenges and potential upheaval. As software companies grapple with evolving business demands, lenders must stay vigilant and prepared for the consequences of any significant shifts.
