
The clash underscores how divergent default forecasts can sway investor confidence and affect capital flows in the $1.8 trillion private‑credit market, influencing risk pricing and fund liquidity strategies.
The private‑credit market, now valued at roughly $1.8 trillion, has come under heightened scrutiny as analysts grapple with the potential impact of rapid AI‑driven disruption on corporate borrowers. UBS Group’s recent note warned of a worst‑case default rate of 15%, a figure that would signal severe stress across the asset class. While the forecast is anchored in a scenario where AI accelerates credit deterioration, the broader consensus anticipates a more modest 5% uptick in defaults, with stabilization projected by late 2026. This divergence highlights the challenge of modeling risk in an evolving technological landscape.
Ares Management’s chief executive, Mike Arougheti, pushed back hard against the UBS outlook, citing historical resilience within private‑credit portfolios. During the 2008 financial crisis, default rates in this segment hovered between 8% and 10%, far below the 15% scenario now being floated. Arougheti argued that such a spike is “absolutely wrong” and would be catastrophic for any fund exposed to those losses. His confidence rests on the sector’s track record of weathering macro‑economic shocks and the expectation that AI‑related defaults will be contained rather than systemic.
The debate has practical implications for retail‑focused private‑credit funds, which have recently faced record redemptions at firms like Blue Owl and Blackstone. Investors often misinterpret these products as liquid, despite their design for longer‑term capital commitments. Misaligned expectations can trigger runs that exacerbate market stress, even when underlying credit quality remains sound. Accurate default projections are therefore critical not only for pricing but also for managing liquidity risk and maintaining investor trust in a market that continues to evolve amid technological change.
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