Fears of a private credit-led crisis have been “overstated” and the growth of private credit does not pose a systemic risk to the economy, according to analysts at JP Morgan Private Bank.
They observed that while private credit assets under management grew at more than 14 per cent compound annual growth rate over the past decade, the sector still only accounts for around nine per cent of total corporate borrowing.
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Their view on private credit has also been informed by the fact that levels of US “risky credit” outstanding has “hovered” at approximately 20 per cent of GDP for a decade.
“There has not been an explosion in US risky credit; private credit has taken share from other risky credit types,” analysts wrote.
Market jitters around private credit’s exposure to software have triggered redemption requests at business development companies recently, prompting some funds to limit outflows.
However, this issue has only impacted the wealth channel so far and JP Morgan analysts highlighted private credit’s primarily institutional investor base, which stood at around 80 per cent at the end of 2024.
“Institutional capital is typically longer-duration and less redemption sensitive, reducing the likelihood of rapid outflows, forced asset sales, or fund gating during periods of market stress,” according to the private bank’s analysts.
They also downplayed the risks from private credit’s exposure to software, amid concerns that artificial intelligence (AI) could upend the software sector.
The analysts said that “not all software or services are equally exposed, and understanding the nuances is critical”, calling recent volatility “a sector-led reset rather than the start of a macro default cycle”.
They did, however, acknowledge that AI-related disruption is “creating cracks in pockets of software” and that software exposure has steadily increased in the leveraged loan market over the past 15 years.
Private credit has approximately 21 per cent exposure to software, rising to 40 per cent when including broader tech/business services – the highest among extended credit markets.
They identified that, within services, the risk is at “the task level”, with standardised, repeatable work likely to be most vulnerable, while tasks requiring trust, accountability, or physical execution are “more defensible”.
In software-as-a-service, “the question is whether AI erodes the product’s moat”.
“Deeply embedded, data-rich, mission-critical software is safer. Generic, labour-scaled, or easily replaced tools are at risk. Seat-based revenue models are more at risk than usage-based,” the firm’s analysts wrote.
Read more: KBRA: AI risks to private credit extend beyond tech companies
