As demand for artificial intelligence (AI) and cloud computing services accelerates, data centers will be the engine of the smart technology revolution. Global tech giants, or hyperscalers, are rapidly expanding into new markets, pre-leasing capacity and spurring developers to raise substantial amounts of capital through equity, loans, and bonds.
As private equity drives major investments and M&A booms, the industry faces growing regulatory scrutiny and public concerns over energy and water consumption. Explore how these trends are shaping opportunities and credit risk in this rapidly evolving sector.
As demand for data center capacity to support artificial intelligence (AI), cloud computing and data storage services grows, data center developers and landlords will need to raise substantial development capital in the form of equity, bank loans, corporate and securitized bonds, or project finance vehicles. Leverage levels will likely increase for developers focused on hyperscale buildouts to be completed in 2026-28.
This methodology applies globally to data center asset-backed securitizations, where repayment is primarily sourced from tenant lease payments tied to data center operations, often structured through master trusts allowing for the addition of new collateral over time.
This methodology applies to commercial mortgage-backed securities (CMBS) backed by large loan and single asset/single borrower transactions across the US, Canada, Asia-Pacific, and Latin America, outlining the credit risk assessment approach and region-specific applications.
In this methodology, we explain our approach to assessing credit risks for conduit and fusion commercial mortgage-backed securities (CMBS) in the US and Canada, including quantitative and qualitative factors that are likely to affect rating outcomes in this sector.
This methodology applies to EMEA CMBS backed by mortgages on income-producing commercial real estate, covering single-loan and multi-loan transactions. Unlike US CMBS approaches, it uses a bottom-up DP/LGD method due to limited historical data availability and less granular loan pools in EMEA.
This methodology applies to collateralized loan obligations (CLOs) backed by project finance and infrastructure assets, including PPP/PFI projects, regulated utilities, renewable energy, and large infrastructure and power-related sectors.
This methodology applies to special or single purpose entities (SPEs) globally that are financed on a nonrecourse, project finance basis and whose primary business purpose is limited, typically to one activity (a project financing).
How we apply our generic project finance methodology to data center financings
This methodology globally applies to commercial real estate firms, including REITs, focused on long-term ownership and operation of income-producing properties, addressing their secured or unsecured corporate-level debt but excluding non-recourse mortgage debt.
This methodology applies globally to companies that provide communications infrastructure, including physical or network services like data transport and processing, to telecom carriers, pay-TV providers, corporations, governments, and other organizations.
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Wednesday, March 18
Digital Frontiers 2026
Digital finance is accelerating a fundamental shift in how technology, capital and data converge – reshaping how risk is understood, measured and managed. Moody’s brings clarity to this shift, uniting trusted credit expertise with advanced AI and data-driven innovation.
