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Powering the AI Economy: How Banks Are Managing Their Growing Data Centre Risk Exposure

August 27, 2026

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Powering the AI Economy: How Banks Are Managing Their Growing Data Centre Risk Exposure

Source: Morningstar DBRS

27 August 2026

Overview

The emergence of artificial intelligence (AI) has triggered an unprecedented surge in demand for digital infrastructure, particularly data centres. 

Once viewed as a niche segment within real estate and infrastructure markets, these facilities have rapidly evolved into a distinct asset class. 

As AI models grow in scale and complexity, their computational requirements increase exponentially, making data centres essential to supporting this technological transformation. 

Sustaining AI expansion requires significant investment. In the U.S., AI-related spending was estimated at USD 430 billion in 2025 and could more than double by 2029, reflecting both rapid innovation and the capital-intensive demands of computing, storage and energy infrastructure. To support this growth, technology companies have raised around USD 300 billion from U.S. investors and increasingly relied on bank financing for AI and data-centre development. Banks have become deeply involved in this ecosystem, not only in the U.S. but also in Europe and the UK through large-scale financing, syndicated lending and securitisation. As a result, the banking sector is increasingly embedded in the expansion of AI-driven digital infrastructure. According to Morningstar DBRS, this creates significant business opportunities for banks whilst also increasing sector concentration risks, prompting active exposure management. However, whilst data-centre lending has been one of the fastest-growing areas of bank credit in recent years, exposures generally remain a modest share of overall loan portfolios. Furthermore, banks employ a range of established risk-management tools, including syndication, concentration limits, exposure caps, portfolio monitoring and risk-transfer mechanisms, to manage sector-specific risks and limit excessive concentration.

Key Highlights

  • AI is driving unprecedented investment in data centres, thereby transforming them into a strategic asset class and creating significant financing opportunities for banks through lending, syndication, and capital markets activities.
  • Banks’ exposure to the data-centre sector is growing rapidly across the U.S. and Europe, supported by strong demand from hyperscalers and AI developers, but this expansion increases concentration and credit risks.
  • Banks are actively managing these risks through syndication, securitisation, and risk-transfer structures, shifting part of the exposure to institutional investors whilst raising new questions around transparency and systemic risk.

Strategic Rationale for Banks’ Exposure to Data Centres

Banks’ exposure to data centres takes multiple forms, including syndicated loans to developers, corporate lending to hyperscalers and infrastructure operators, and capital-markets financing through structured finance transactions. Given the scale of modern AI infrastructure projects, financing is typically arranged by large banking syndicates capable of underwriting substantial amounts of capital. Moreover, banks support the sector through a broad range of capital markets solutions, including M&A advisory, debt arranging and equity capital markets transactions.

U.S. banks remain the dominant participants in the market. Institutions such as JPMorgan, Goldman Sachs, Citigroup, Morgan Stanley, and Wells Fargo regularly arrange multibillion-dollar financings for data-centre developers and AI-related infrastructure. For example, JPMorgan led a USD 7.1 billion construction loan for Crusoe’s Stargate AI campus in Texas in 2025, whilst a consortium led by Morgan Stanley and MUFG provided USD 2.6 billion of financing to CoreWeave later that year.

European banks have also increased their participation through infrastructure lending, project financing, and syndicated transactions, both within Europe and internationally. For instance, Deutsche Bank AG, in September 2025, provided EUR 600 million of financing to Sweden-based EcoDataCenter and participated in AirTrunk’s AUD 4.3 billion financing in Australia alongside other lenders. Beyond traditional bank lending, private credit funds, infrastructure investors, and asset managers are becoming increasingly important capital providers. NVIDIA Corporation’s recently announced initiative to help mobilise more than USD 500 billion for AI infrastructure illustrates both the scale of anticipated investment needs and the growing role of nonbank capital providers.

We believe banks’ involvement in data-centre financing is consistent with their traditional role in supporting large-scale infrastructure and technology investments. The sector offers attractive long-term growth prospects, significant financing needs, and access to strategically important technology clients. In addition to lending income, syndication and capital-markets activities generate substantial fee revenues in a normalising interest rate environment, whilst limiting balance sheet usage.

Key Risks Associated With Data-Centre Financing

Despite strong growth prospects, we note that data-centre financing carries several risks for banks. In our view, concentration risk is one of the most significant credit considerations for banks active in the sector. Projects are typically large and often dependent on a limited number of hyperscalers, AI providers, or specialist operators.

Credit risk is also closely linked to expectations regarding future AI adoption. Many investment decisions assume continued growth in demand for computing capacity and the sustained use of new infrastructure. If commercial AI adoption develops more slowly than expected, utilisation rates and cash flows may fall short of projections, weakening borrowers’ ability to service debt.

Data centres are also exposed to technological obsolescence risk, although to a lesser extent. Rapid advances in chip technology, computing architecture, and cooling technologies may reduce existing facilities’ competitiveness, calling for considerable additional investment to remain operationally relevant.

Finally, data centres face asset-specific risks across both the development and operating phases. For facilities under development, permitting delays, construction challenges, power-connection constraints, and cost inflation can adversely affect project performance and increase risks for lenders. For operational assets, revenues often depend on long-term contracts with a relatively small number of tenants, whilst project economics rely on access to reliable and affordable electricity. Energy-price volatility and evolving environmental regulations can adversely affect project performance and increase risks for lenders.

Insurance availability has also become an increasingly important consideration, with higher premiums, tighter coverage terms, and reduced insurer capacity already affecting some large-scale data-centre projects.

Concentration risk at the tenant level remains particularly relevant. Large hyperscalers continue to account for a significant share of industry demand and capacity commitments, creating dependency on a relatively small group of counterparties. Recent market data indicates that hyperscalers represented approximately 59% of North American data-centre tenant demand in 2026, highlighting the importance of monitoring customer concentration and counterparty exposure.

We have also previously highlighted risks related to energy availability and physical security considerations for data centres, which are likely to remain important as the sector continues to expand.

Managing Down Exposures Through Risk Transfer and Securitisation

In response to concentration, capital-allocation, and portfolio-management concerns, banks are increasingly adopting strategies to reduce retained exposures. One primary tool is syndication, which allows institutions to distribute loans across a broader group of lenders and investors, limiting single-name balance sheet exposure. The USD 2.6 billion CoreWeave financing is an example of this approach, with exposure distributed among a large lending syndicate rather than retained by a small number of lead arrangers. Banks are also making greater use of significant risk transfer (SRT) transactions, enabling them to transfer portions of credit risk to external investors whilst preserving client relationships and maintaining lending capacity. In addition, banks increasingly use loan sales and secondary-market transactions to reduce retained exposures, free up capital, and enhance balance sheet flexibility. As a result, institutional investors, including private credit funds, insurance companies, and infrastructure investors, are becoming increasingly important providers of funding for digital infrastructure projects.

Securitisation also plays a growing role. By packaging data-centre loans into ABS and similar structures, banks can convert relatively illiquid exposures into tradable securities and broaden the investor base supporting the sector. For example, Vantage Data Centers completed the first EMEA data-centre ABS transaction in 2024, raising GBP 600 million through securitised notes, whilst Switch issued USD 1.7 billion of data-centre ABS in 2024 and a further USD 3.5 billion of ABS and CMBS financing in 2025. These transactions illustrate how capital markets are increasingly being used to recycle capital and redistribute risk beyond the banking system.

In our view, whilst these mechanisms improve capital efficiency and support the continued expansion of AI infrastructure, they may also create new vulnerabilities. Strong investor demand could weaken underwriting discipline, whilst the migration of exposures from regulated banks to nonbank financial institutions may reduce transparency and complicate the assessment of systemwide risk. Regulators are likely to focus not only on banks’ direct exposures but also on the channels through which AI-related infrastructure risks are redistributed across the broader financial system.

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Notes

All figures are in euros unless otherwise noted.

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