What Is Significant Risk Transfer (SRT)
in Private Credit?

Key Takeaways

• Oxane's Compass 2026 survey found infrastructure finance has the second-highest deployment intensity of any Private Credit+ strategy: 39% of firms are active in it, and 46% of those plan to increase exposure, trailing only securitized products.
• Independent reporting in Private Debt Investor corroborates the shift from the LP side: a Benefit Street Partners survey found 47% of global LPs plan to increase infrastructure debt allocations in 2026, ranking the strategy ahead of direct lending (39%) and asset-based lending (35%) for the first time.
• The demand driver is largely artificial intelligence. Data centre power consumption, grid buildout, and onshoring are converging with geopolitical disruption to energy supply to expand what infrastructure debt actually needs to finance.
• The performance case backs the enthusiasm. Infrastructure debt has posted cumulative five-year default rates of 2.4%, against 9.6% for non-financial corporates, alongside a stronger risk-adjusted return profile than corporate high yield across a full market cycle.

Infrastructure finance has spent most of its history as the quiet, unglamorous corner of Private Credit+, valued for stability rather than growth. That reputation is changing fast, and the reason is the same one reshaping half the market's other conversations this year: artificial intelligence and the physical infrastructure it depends on. The growing role of AI in infrastructure finance is influencing both where capital is being deployed and how portfolios are managed.

Why Infrastructure Finance Is Suddenly the Hottest Sub-Asset Class

Oxane's Compass 2026 survey, fielded across more than 380 senior credit professionals, found that 39% of firms are already active in infrastructure finance. That puts it behind asset-based finance, fund finance, corporate direct lending, and commercial real estate finance in overall adoption. But look at deployment intent rather than current adoption, and the picture flips: 46% of firms already active in infrastructure finance plan to increase their exposure, the second-highest deployment intensity of any strategy in the entire survey, trailing only securitized products.

That finding lines up closely with what LPs themselves are telling independent researchers. A Benefit Street Partners survey covered in Private Debt Investor's July/August 2026 issue found that almost half of global LPs, 47%, are planning to increase their infrastructure debt allocation in 2026, ahead of direct lending at 39% and asset-based lending at 35%. For a strategy that has historically played second fiddle to direct lending in LP portfolios, that ranking is new, and it is showing up in two independent surveys at once.

The driver behind both numbers is largely the same story told from different angles. Don Dimitrievich, global head of Nuveen Energy Infrastructure Credit, described the current environment to PDI as several converging dynamics: the proliferation of AI data centres, the onshoring of supply chains, broader electrification of the economy, and a reindustrialization trend, all expanding the addressable market simultaneously. On top of that structural growth, the conflict in Iran disrupted roughly 20% of the world's liquefied natural gas supply earlier this year, adding urgency and pressure to an already tightening energy market. Pieter Welman, head of global infrastructure debt at Barings, framed it as a genuine confluence of mega-trends, from long-term urbanization patterns to the rapid build-out of digital infrastructure spanning everything from fiber networks to data centres themselves.

The Numbers Behind Infra Debt's Appeal

Infrastructure finance is the smallest of the six asset classes Oxane mapped in its Private Credit+ analysis, sized at roughly $0.6 trillion against ABF's $20.7 trillion or securitized products' $13 trillion. What it lacks in scale, it makes up for in the specific characteristics that make it attractive precisely when uncertainty elsewhere is rising: essential services with inelastic demand, high barriers to entry, and long-term cash flows that can span decades.

The credit performance data backs that positioning up. Infrastructure finance has posted cumulative five-year default rates of just 2.4%, compared with 9.6% for non-financial corporates, according to Moody's default and recovery data, with recovery rates that significantly exceed corporate debt levels as well. Independent analysis from Scientific Infra & Private Assets, a PEI Group affiliate, found infrastructure debt's risk-adjusted return profile beats public credit across a full market cycle from 2014 to 2025: its non-investment-grade infrastructure index posted the highest 10-year return-to-volatility ratio of any index evaluated, achieved with roughly half the volatility of traditional high yield corporate bonds. In stress years like 2015, 2018, and 2022, infrastructure debt held up better than corporate investment grade and real estate credit, drawing down less and recovering faster.

AI Is Reshaping Both Sides of Infrastructure Debt

The AI angle here runs in two directions at once, and it is worth separating them. On the demand side, AI is not just financing the data centres themselves. Vivek Bantwal, co-head of global private credit at Goldman Sachs Alternatives, has described the broader ecosystem that requires financing: data centres need power, that power needs new power plants, and those power plants need transmission line upgrades, cascading into a much larger capital requirement than the data centre buildout alone would suggest. That is precisely the kind of multi-layered, capital-intensive financing need infrastructure debt exists to serve.

This dynamic is creating what many market participants increasingly view as an infrastructure finance AI cycle, where demand for digital infrastructure is driving financing needs while technology simultaneously improves how those investments are evaluated. The rise of AI driven infrastructure finance is therefore affecting both capital formation and operational workflows.

On the operational side, AI is also changing how infrastructure finance itself gets underwritten and monitored, a shift that matters just as much for firms trying to scale into the strategy. Infrastructure portfolios span an unusually wide range of sub-sectors, transportation, energy, renewables, digital infrastructure, and social infrastructure, each with its own servicer, its own reporting cadence, and its own regulatory and ESG requirements to track. Managing that manually is exactly the kind of high-volume, document-heavy workflow that AI-driven data extraction and validation are suited to.

The Operational Complexity Behind Infra Debt Growth

Scaling into infrastructure finance without the right operational backbone tends to expose the same gap Compass 2026 found across the market more broadly: firms are more confident about deploying capital than about the infrastructure needed to manage it once deployed. Oxane's project finance solution was built specifically around this complexity, with ESG compliance tracking, servicer reporting SLA monitoring, multi-level validation of incoming servicer data, and AI-powered servicer data management built to handle exactly the kind of document volume and reporting diversity that a multi-sector infrastructure book generates.

As portfolios scale, infrastructure finance automation is becoming increasingly important for handling reporting, compliance monitoring, data validation, and portfolio oversight across multiple sub-sectors.

Oxane's infrastructure and project finance work spans 20 of the top 30 global investment banks and 10 of the top 15 global private debt firms, giving direct visibility into how both sides of the market are managing this specific operational load as allocations scale.

What This Means for Portfolio Management

Infrastructure finance's jump in deployment intent is not an isolated data point. It sits alongside Compass 2026's broader finding that 78% of firms are increasing technology budgets and that risk management and valuation confidence, not capital availability, are the top operational concerns firms report today. A strategy defined by long-dated, multi-decade cash flows and diverse sub-sector reporting requirements is precisely where that operational gap shows up first if the underlying infrastructure is not already in place.

Oxane Panorama's portfolio management capabilities unify monitoring, reporting, and valuations across infrastructure alongside every other Private Credit+ strategy, complementing broader asset-backed finance technology capabilities across private credit portfolios. Growth in one asset class therefore does not have to mean rebuilding the operating model from scratch.