The Canadian dollar climbed to a two-week high against the U.S. dollar on Monday as stronger-than-expected inflation pushed Canadian bond yields higher, while investors weighed the impact of a looming U.S. tariff deadline on the country’s economic recovery.

The loonie was up 0.2% at C$1.3850 per U.S. dollar, or 72.20 U.S. cents, after touching C$1.3845, its strongest intraday level since June 1.

Canada’s annual inflation rate accelerated to 3% in July from a year earlier, exceeding economists’ expectations for a 2.9% reading. The increase was driven in part by higher gasoline prices as renewed tensions between the United States and Iran pushed energy markets higher.

Underlying inflation, however, remained considerably more subdued. The CPI-trim measure was 1.9%, while CPI-median stood at 2%, suggesting that the headline acceleration has not yet translated into broad-based price pressure.

“Overall, the July report remains consistent with a relatively favourable combination of firming economic growth and underlying inflation close to target,” Royal Bank of Canada economists Nathan Janzen and Abbey Xu said in a note.

That combination could complicate the Bank of Canada’s monetary policy calculations. Stronger economic activity and inflation close to the central bank’s target reduce the urgency for further monetary easing, while the underlying inflation figures provide policymakers with room to remain cautious.

The Canadian dollar’s gains also came as investors assessed the potential consequences of a new round of U.S. tariffs. Washington has said that starting August 19, it will impose 50% tariffs covering nearly $20 billion of Canadian goods, equivalent to about 5.2% of Canada’s exports to the United States.

The measures have added another layer of uncertainty for Canada’s economy, particularly for industries and regions heavily dependent on cross-border trade.

“The approaching U.S. tariff deadline adds uncertainty, and the proposed measures would have significant consequences for some affected industries and regions,” the RBC economists said. “But their narrow coverage means they are unlikely to derail the broader economic recovery.”

Canada’s trade negotiations with the United States remain unresolved.

Dominic LeBlanc, the Canadian minister responsible for trade with the U.S., told an advisory committee on Friday that the two countries remained far from reaching a draft agreement despite regular meetings.

The tariff threat is of major concern for Canada because the United States is its dominant export market. Any disruption to cross-border trade could weigh on manufacturing, investment and employment even if the overall value of goods subject to the proposed tariffs remains relatively limited.

Canadian financial markets have nevertheless priced in a stronger domestic economy.

The country’s 10-year government bond yield has risen about 17 basis points over the past month, the largest increase among G7 sovereign bonds apart from Japan. Recent employment, trade and gross domestic product data have pointed to a recovery after a weak start to the year.

Bond yields rose across the Canadian curve on Monday.

The 30-year government bond yield increased 2.6 basis points to 4.117%, after reaching 4.145% earlier in the session, its highest level since March 2010. The increase in long-term yields suggests investors are demanding greater returns to hold Canadian government debt as the economic outlook improves and inflation remains a consideration.

Foreign investors are also continuing to provide significant demand for Canadian securities. Separate data showed that overseas investors bought a net C$40.83 billion ($29.46 billion) of Canadian securities in June, with federal government bonds accounting for much of the purchases.

The combination of stronger domestic data, elevated inflation and robust foreign demand is creating a more complicated environment for Canadian assets.

For the currency, analysts expect the near-term direction to depend on the balance between domestic economic resilience and the potential damage from U.S. trade measures. A stronger Canadian economy and firm inflation can support the loonie by reducing expectations for aggressive monetary easing, while tariffs could weaken growth and undermine the currency.

For the Bank of Canada, the latest inflation data provide little reason to respond aggressively to the headline increase because its preferred underlying measures remain close to the 2% target.

The greater uncertainty comes from the external environment. Higher energy prices have helped push headline inflation upward, while the impending U.S. tariffs threaten to create a separate drag on Canadian growth.

The result is a delicate policy environment in which the central bank must distinguish between temporary price pressures and a sustained acceleration in domestic inflation.

However, the Canadian dollar’s move to a two-week high shows that markets are currently placing greater weight on the improving domestic economy and relatively contained core inflation than on the immediate threat from U.S. trade policy. But that balance could change quickly as the August 19 tariff deadline approaches and negotiations between Ottawa and Washington continue.

The financing of the artificial intelligence boom is moving into a new phase, with Wall Street increasingly treating data centers and the computing capacity inside them as infrastructure that can be financed with long-term debt rather than assets that technology companies must fund largely from their own balance sheets.

A recent Securities and Exchange Commission staff position could make that transition easier by giving investors greater flexibility in structuring certain data center financings without triggering the risk-retention requirements that apply to some asset-backed securities.

The move follows a major deal in the AI industry. Nvidia last week announced partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to establish financing platforms capable of mobilizing more than $500 billion in third-party capital for AI computing infrastructure. Nvidia said it could provide backstops of up to $125 billion, or roughly a quarter of the potential financing.

The initiative is seen as another indication that the financing of AI infrastructure is becoming almost as important as the technology itself. AI developers and cloud providers need enormous amounts of capital to build data centers, secure electricity and purchase GPUs, but not every customer can finance that expansion directly from its balance sheet.

That is creating an opening for private equity, private credit and structured-finance investors.

“Folks contemplating this transaction will be quite happy about the response from the SEC,” Orion Mountainspring, a securitization attorney at Orrick, told CNBC.

The SEC’s position followed a request from law firm Latham Watkins concerning whether certain data center debt should be treated as an asset-backed security under the Exchange Act. The agency agreed with the firm’s interpretation that the structures under discussion would not fall within that definition and therefore would not be subject to the associated risk-retention requirements.

That matters because Dodd-Frank rules introduced after the 2008 financial crisis generally require sponsors of covered securitizations to retain part of the credit risk attached to the assets they package and sell. Removing that requirement for qualifying data center structures can reduce the amount of equity sponsors need to commit.

Mountainspring said the decision could allow sponsors to “push down the required equity in the deal,” making the structures more attractive to capital providers.

B.K. Lee, an asset-backed securities attorney at Alston & Bird, said the guidance could make data center financing more “flexible and capital-efficient” by reducing the constraints associated with conventional risk-retention structures.

The development also points to a broader change in how AI infrastructure is being financed. Data centers were once largely viewed as specialized real estate and technology assets. Increasingly, investors are evaluating them as long-duration infrastructure capable of producing recurring cash flows from customers that need computing capacity for years.

That shift is already visible in the emergence of dedicated investment vehicles. KKR, for example, launched Helix Digital Infrastructure in June with more than $10 billion of committed long-duration capital to finance data centers, power and connectivity for AI workloads. Nvidia is a founding investor and strategic partner.

The SEC position could add another financing tool to that expanding capital stack.

Why The Financing Shift Matters

The economics of AI infrastructure require enormous upfront spending. A data center developer must often commit capital years before the facility reaches full utilization, while AI hardware also has a comparatively rapid technological replacement cycle.

Structured financing can move some of that burden away from the companies building and operating the facilities. Instead of relying entirely on corporate borrowing or equity, developers can potentially raise money against expected future revenues generated by computing capacity. That could allow more projects to be built simultaneously and give AI companies access to infrastructure without carrying the entire cost on their own balance sheets.

The scale of the capital requirement helps explain why Nvidia is increasingly involved in financing as well as supplying the chips used in AI systems. The company has described computing capacity as an emerging asset class and is working with major financial institutions to make long-term capital available to its customers.

But the model also introduces a new layer of financial risk.

The fundamental question for lenders is whether the future cash flows from AI data centers will be large and durable enough to support the debt being raised today. That depends on continued demand for AI services, high utilization of computing equipment, electricity costs, and the pace at which new generations of chips make older infrastructure less competitive.

There is also a potential circular-financing concern. Nvidia has a direct commercial interest in the expansion of AI infrastructure because more data centers generally mean more demand for its chips. If Nvidia helps support financing for infrastructure that subsequently purchases Nvidia equipment, the company could benefit both as a technology supplier and as a facilitator of the capital used to buy that technology.

That does not by itself make the financing unsound, but it makes the quality of underlying demand particularly important.

Recent developments show why investors are paying attention. Nvidia is providing substantial financial support for an OpenAI data center project in Ohio, including a guarantee of up to $105 billion for the first phase and a $1.5 billion investment in SB Energy. The facility is expected eventually to reach 8 gigawatts of capacity, with the initial phase relying exclusively on Nvidia chips.

The size of these commitments illustrates the financing challenge facing the AI industry. Companies are making infrastructure commitments measured in tens or hundreds of billions of dollars, while investors are being asked to assess demand for computing capacity years into the future.

SEC Guidance Is Not A New Rule

The regulatory change should not be overstated. The SEC position is a staff opinion rather than a formal rulemaking or congressional legislation. It does not create a blanket exemption for every data center financing transaction.

Instead, it gives market participants a clearer indication of how the agency views a particular legal structure.

That clarity can still have a significant commercial effect. Financial institutions and their advisers can now design transactions with greater confidence that structures following the framework outlined in the SEC’s exchange with Latham will not automatically be subjected to the risk-retention regime applicable to Exchange Act asset-backed securities.

Attorneys at Katten Muchin Rosenman said the distinction rests partly on the nature of data center assets and their revenues. Unlike mortgages, which are designed to repay through the gradual liquidation of an underlying asset, data centers can generate continuing operating revenues over their useful lives.

That difference could give financiers greater room to structure debt around long-term computing contracts and other predictable revenue streams. The likely result is a wider range of financing options for the AI infrastructure industry, from conventional project finance and private credit to asset-backed structures and dedicated infrastructure funds.