Beyond the hyperscaler: Why data center financing is a project, not a proxy
A look at why the tenant may draw attention in data center finance, but the structure defines the risk.

Duration: 5 Mins
Date: Sep 08, 2026
Data centers sit at the center of this buildout, housing the computing infrastructure needed to train, deploy, and scale artificial intelligence (AI) models. Like railways, power grids, and telecommunications networks before them, they form part of the essential infrastructure on which a broader economic transformation depends.
A potential new frontier for private credit
For private credit investors, this is creating a compelling opportunity in specialist asset-based finance. As demand for AI infrastructure grows, financing markets are evolving to support projects that are larger and more complex than traditional digital infrastructure investments.
What is emerging is more than a larger market for lending.
What is emerging is more than a larger market for lending. It is a specialist asset class bringing together elements of corporate credit, infrastructure, real estate, structured credit, and project finance. While hyperscalers remain among the strongest corporate credits globally, the scale of planned investment means funding is increasingly being sourced from a broader range of capital providers.
Tailored structures, higher yields
Joint ventures, project-finance-style vehicles, structured financings, and bespoke asset-based arrangements are becoming more common as borrowers and investors seek tailored solutions suited to individual projects. Data center finance therefore provides a useful lens through which to view the future of private credit: specialist areas where structuring expertise, underwriting skill and tailored capital solutions can create value.
These financings often provide exposure to long-term contractual cash flows supported by high-quality hyperscaler counterparties, but with potentially higher yields than debt issued directly by the same companies.
At first glance, many appear straightforward: tenant or guarantor exposure plus an additional yield spread. Public-market pricing often reflects this view, with spreads closely linked to those of the underlying counterparty. The additional yield is often viewed as compensation for complexity and reduced liquidity, rather than materially different credit risks.
Data center finance is project finance, not hyperscaler credit
However, these are ultimately asset-based project financings, not corporate financings. Many structures are designed to transfer substantial construction, operational, power-supply, contractual, and leasing risks to the hyperscaler, but those risks are never eliminated entirely.
They can be reallocated, mitigated, and managed through contractual arrangements, including triple-net leases with floor rent, residual-value guarantees, construction protections, date-certain rent commencement, debt-service reserves, and debt that fully amortizes within the initial lease term. Even so, the risks remain present to varying degrees.
The fact that these financings typically do not carry the same credit ratings as the underlying hyperscalers illustrates the point. If they were equivalent exposures, they would have identical credit ratings. Instead, their ratings are typically heavily influenced by the hyperscaler’s credit quality but generally sit below it to reflect the specific risks of the project.
Why project structure drives outcomes
In our view, the most important question in data center finance is what risks sit between the tenant and the lender. Answering that requires understanding how each project allocates risk. Construction risk, power availability, operating performance, contractual protections, refinancing structures, insurance arrangements, and long-term asset competitiveness can all influence outcomes.
In some transactions, underwriting may also depend on future refinancing conditions, or on the ability to renew and re-lease capacity once existing contracts expire. No two data center financings are the same. Even two data centers underpinned by the same hyperscaler may transfer and mitigate risks in different ways, resulting in different risk-return profiles.
Dispersion creates opportunities for specialist managers
Markets often treat new asset classes as relatively homogeneous in their early stages. Yet history suggests that, over time, differences in structure, underwriting quality, and risk allocation become more important drivers of performance.
In a market characterized by bespoke structures, dispersion is to be expected. For skilled investors, that dispersion creates the opportunity to outperform.
Data center finance appears unlikely to be an exception. As the sector matures, performance is likely to become more differentiated across projects. In a market characterized by bespoke structures, dispersion is to be expected. For skilled investors, that dispersion creates the opportunity to outperform.
Capturing that opportunity requires robust manager selection and underwriting discipline. Understanding the creditworthiness of the hyperscalers supporting these projects remains essential. Investors need a view on the competitive position, financial strength, and long-term prospects of the companies driving AI infrastructure demand.
But that alone is insufficient. Underwriting these transactions requires expertise across corporate credit, project finance, infrastructure, real estate, and structured credit. Depending on the transaction, sustainability factors may also be material to long-term asset resilience and downside risk.
We believe the strongest managers are likely to look beyond tenant or guarantor quality to assess whether the compensation offered is sufficient for the risks embedded in each project. The challenge is understanding which risks are being transferred, which risks are being retained and whether investors are being compensated appropriately.
Investment discipline matters
The AI infrastructure buildout is likely to create opportunities for many years to come. The challenge for investors is identifying which opportunities offer the most attractive risk-adjusted returns. Successful managers will need to ensure they are compensated for complexity, illiquidity, and the project-specific risks that distinguish these investments from direct exposure to debt issued by the underlying hyperscalers.
In our view, success in specialist asset-based private credit, including data center financing, depends on maintaining a disciplined and selective approach, underpinned by transparency and strong governance in how each transaction is assessed and structured.
The ability to say no can be just as important as the ability to say yes.
The ability to say no can be just as important as the ability to say yes. Some opportunities may appear compelling at first glance but still fall short on closer inspection. The project structure may not be sufficiently robust, or the additional spread may not adequately compensate for incremental risks beyond those associated with the underlying hyperscaler.
At Aberdeen, we believe the most successful investors will not be those who finance the most projects, but those with the discipline to walk away from the wrong ones and the patience to wait for the most compelling opportunities.
Final thoughts
In our view, data center financing may ultimately be remembered as more than a response to the growth of AI infrastructure. It may also serve as a case study in how private credit continues to evolve toward increasingly specialized forms of lending that cannot be understood through simple comparisons to traditional corporate debt. As capital flows into complex, capital-intensive sectors, we believe investors are likely to encounter more opportunities where the underlying asset, contractual framework, and financing structure matter as much as the strength of the names involved. Viewed through that lens, data center finance offers an important reminder: familiarity is not the same as exposure. A hyperscaler may help anchor demand and attract attention, but it does not define the investment. Ultimately, these transactions stand or fall on the quality of the project itself, the resilience of its structure, and its ability to perform as intended over time.
