Private Credit's $124B Software Bet Has a Hidden Risk Map

What's New

A recent analysis from PRISM reveals that the private credit market holds $124.2 billion in software exposure across 131 funds and 1,305 companies, yet prices structurally different risk profiles as if they were identical assets. The report introduces the Velcro Score, a three axis taxonomy that classifies software borrowers by how difficult they are for customers to replace in a downturn, exposing an inverted risk premium where the riskiest software credits actually price tighter than the safest.

Why It Matters

The entire private credit industry classifies software using GICS, a system built for equity investors that lumps a core banking platform and a website builder into the same sector bucket. With $467 billion in software principal maturing between 2027 and 2032, lenders without a framework to distinguish between sticky infrastructure software and substitutable discretionary tools face asymmetric downside when the cycle turns.

Big Picture Drivers

• Classification failure: GICS assigns every recurring revenue software company to one bucket, making it impossible for credit analysts to differentiate between a multiyear ERP replacement and a monthly subscription tool a marketing director can swap in a weekend.

• Stickiness over growth: The Velcro Score reframes software credit analysis around three axes (stack depth, end industry budget stickiness, end user function criticality) rather than equity style metrics like revenue growth and net retention that describe expansion, not resilience.

• Fund composition divergence: Velcro Credit Quality Scores range from 82 (Goldman Sachs PC, 46% Utility Software) to 62 (Blackstone Secured Lending, 10.5% Discretionary Tools), a 20 point gap invisible in standard reporting.

• AI substitution risk: Utility Software carries natural moats against AI displacement through regulatory cycles, data migration complexity, and compliance certification, while Discretionary Tools face direct competition from AI powered alternatives at lower price points.

• Maturity wall concentration: Software positions cluster heavily in 2028 through 2031, with $105 billion maturing in 2031 alone, creating refinancing pressure that will force archetype level visibility into the market.

By The Numbers

• $124.2B total software fair market value in private credit as of Q4 2025, up 27% year over year and 8x since Q4 2019.

• Negative 2 bps spread inversion where Discretionary Tools price tighter than Utility Software, meaning the market charges less for the riskiest credits than for the safest.

• 160 bps interquartile rate range across all software positions (8.22% to 9.82%), remarkably narrow for a sector spanning core banking to website builders.

• 9,230 total software positions held across 131 funds, representing the largest single sector concentration in private credit.

• 95.5% FMV to cost ratio during COVID Q1 2020, the stress test that showed infrastructure software held value while discretionary tools deteriorated.

Key Trends to Watch

• Repricing risk: Archetype aware pricing will emerge as the maturity wall forces refinancing conversations that expose the gap between Utility Software and Discretionary Tool risk profiles.

• Lagging indicators: The 6 to 12 month lag between economic deterioration and ARR deterioration for Discretionary Tools means trailing NRR will mask problems until borrowers have already burned through liquidity cushions.

• LP due diligence: Fund level Velcro scores will become a differentiator as institutional allocators seek to understand whether a fund's software book is anchored in infrastructure or loaded with substitutable tools.

• AI acceleration: AI disruption will widen the bifurcation between high Velcro and low Velcro software, compressing valuations on Discretionary Tools while reinforcing the moats around regulatory driven infrastructure platforms.

The Wrap

Private credit built a $124 billion software position without the taxonomy to tell good software from bad. The Velcro Score fills that gap with a framework that is empirically grounded, practically applicable, and already exposing mispricing the market has not corrected. The question for lenders is whether they develop archetype level visibility before the cycle provides the lesson or after.