来源：环球市场播报 资产支持融资（ABF）将引领增长。随着合作模式和资产发起（origination）活动加速，ABF将成为增 长核心。另类资产管理公司正寻求为更加多样化的新资产池提供资金——尤其是消费贷款和数据基础设 施信贷。新的合作关系正在催生资产发起机会，而在部分贷款领域银行仍受监管约束的情况下，另类资 产管理机构将继续扩大参与度。 更广泛的资产类别将支持证券化增长。私募信贷在证券化产品领域的影响力不断扩大，尤其集中在高收 益能够补偿资产风险的板块——特别是在不同资产类别利差收窄的背景下。 创新将支持不断增长的流动性需求。私募信贷比以往更加依赖金融创新工具，例如结构化信贷、评级基 金结构、净资产值（NAV）贷款以及实物支付利息贷款（PIK贷款），以满足另类流动性融资需求。常 青基金的采用率上升也正在重塑管理人的分销渠道。 监管护栏仍将有限，但对透明度的关注将增加。在全球范围内，监管机构总体上继续支持私募信贷在满 足资本需求方面发挥更大作用。但同时也保持谨慎。例如，英格兰银行最近启动了一项针对私募市场的 系统性探索性情景分析。 随着互联性增强，风险将上升。私募信贷基金与传统金融机构之间的联系正在加深，这在 ...

Core Insights - The article highlights the massive capital expenditure by major tech companies on AI infrastructure, exceeding $250 billion in 2024, with a projected total investment of $2.9 trillion over the next four years [1][2] - There exists a significant funding gap of approximately $1.5 trillion in AI-related investments, indicating that major companies can only cover about half of their needs, necessitating external financing [2][3] - Private credit is emerging as a key source of funding to fill this gap, as traditional banks are increasingly reluctant to lend for long-term, asset-heavy AI projects [4] Investment Landscape - The private credit market has seen rapid growth, expanding from $1 trillion in 2020 to an estimated $1.5 trillion in 2024, with projections to exceed $2.6 trillion by 2029 [3][5] - Investors are attracted to private credit due to its higher yields, often exceeding 10%, compared to traditional bank deposits [5] - Asset-backed financing (ABF) is particularly appealing for AI data center projects, allowing for flexible financing options even during early project stages [5] Corporate Financing Strategies - Major tech companies like Google and Amazon have the capacity to issue up to $600 billion in debt without affecting their credit ratings, but they prefer to limit debt issuance to avoid shareholder concerns about excessive spending [6] - Companies are strategically using their cash reserves and limited debt to fund initial investments in AI infrastructure, planning to seek additional financing once these investments yield returns [6] Energy Consumption Concerns - The energy consumption of global data centers is projected to reach 415 terawatt-hours (TWh) in 2024, accounting for 1.5% of global electricity use, with expectations to double by 2030 [7][4] - Major tech firms are exploring renewable energy solutions to mitigate the high energy demands of AI operations, including significant contracts for renewable energy and acquisitions of energy facilities [7][6] Long-term Investment Trends - Institutional investors, such as pension funds and sovereign wealth funds, are increasingly investing in AI infrastructure due to its potential for stable cash flows and inflation protection, with expected annual returns of 7-9% over the long term [8] - These investors prioritize projects that demonstrate certainty in growth, policy support, and environmental sustainability, particularly those with ESG credentials [9] Risks and Challenges - Investors face risks related to economic slowdowns, which could lead to reduced risk appetite and a preference for more liquid assets, potentially impacting private credit markets [10] - The uncertainty surrounding AI commercialization could disrupt financing expectations, especially if tech companies cut capital expenditures [10] - Practical challenges, such as securing land permits and connecting to power grids, can hinder project progress and investor confidence [10] Conclusion - The article emphasizes the explosive growth in capital investment for AI infrastructure, the significant funding gap, and the role of private credit in addressing this gap [12] - It also highlights the importance of understanding the underlying dynamics of this investment landscape, including energy consumption and the need for strategic risk management [12]