【Market Quick Report】 Market fluctuations are intense; here are the five key points to focus on when deploying AI!

What we want you to know:

At the outbreak of the US-Iran conflict, the market was highly focused on soaring oil prices and rising inflation, which we also discussed in several articles. In this article, we revisit concerns raised by other markets, including recent private credit risk events over the past month, and the increasing potential for AI capabilities to disrupt software stocks; meanwhile, in the hardware sector, Nvidia’s optimistic earnings report was followed by a stock price decline, reflecting the market’s tightening scrutiny and rising valuation correction risks.

Amid these concerns, the worsening conflict in the Middle East has further dragged down overall stock market performance. As of the close on 3/10, the S&P 500’s YTD growth was nearly zero. Therefore, following our previous quick analyses of the Middle East situation, this report will further examine the five major concerns in the recent market, including private credit, SaaS software’s potential demise, and renewed worries about AI monetization.

Key points of this article:
Q1: Is there a hidden crisis in private credit, with systemic risk increasing?
Q2: What should we watch for regarding AI capital expenditures relying on private credit?
Q3: Will AI cause a surge in unemployment and lead to an economic recession?
Q4: Is SaaS facing a doomsday scenario? Will AI dismantle its traditional moat?
Q5: Are there risks in AI hardware supply chains?

Q: Is there a hidden crisis in private credit, with systemic risk increasing?

Beyond the US-Iran conflict, recent liquidity risks in private credit have resurfaced in discussions. Following last year’s defaults by regional banks like Zions Bancorp and Western Alliance, and auto loan provider Tricolor, the storm reignited in February this year. First, asset management firm Blue Owl Capital restricted redemptions from its retail debt funds. On 2/27 (Friday), UK mortgage lender Market Financial Solutions (MFS), which had secured financing from multiple Wall Street institutions, also declared bankruptcy. Large asset managers like Blackstone and others have reported record redemption waves from private credit funds, with some funds hitting redemption limits.

These opaque, non-deposit financial institutions (NDFIs) continue to pose risks, prompting market recall of last year’s warning from JPMorgan CEO Jamie Dimon: “When you see a cockroach, there may be more.” Concerns about larger systemic risks lurking in the private credit market are rising again. The KBW Bank Index in the US also dropped as much as -6% intraday on 2/27 following MFS’s bankruptcy news, marking the largest single-day decline since the tariff panic in April last year.

A: Bank exposure to non-bank financial loans remains manageable, with low liquidity risk

Regarding the likelihood of a liquidity crisis, we remain relatively optimistic because most banks’ exposure to NDFIs remains within limited ranges. According to S&P Global Market Intelligence, among the top 20 US banks by NDFI loan exposure in Q4 2025 (accounting for about 85% of the total NDFI loan market), most have relatively limited exposure, with related loans generally constituting less than 20% of total assets. Only 8 banks have exposure exceeding 10%, indicating overall risk concentration remains manageable.

This suggests that even if widespread NDFI defaults occur later, they are unlikely to trigger a systemic liquidity crisis. More importantly, S&P Global Market Intelligence reports that the default rate on bank loans to NDFIs remains stable at around 0.14% in Q4 2025, indicating that current defaults are mostly isolated incidents, and the overall situation remains stable.

Q: What should we watch for regarding AI capital expenditures relying on private credit?

In contrast, we believe a key concern is the growing importance of private credit in AI financing. On one hand, even tech giants with strong cash flows find it difficult to fully fund the massive capital expenditures needed for AI infrastructure, increasing external financing demand. On the other hand, in the AI era, many unlisted unicorns with valuations exceeding $1 billion are emerging, especially those lacking access to public markets, which rely heavily on private markets. Both factors further reinforce the central role of private credit in the AI supply chain.

According to Morgan Stanley estimates, by 2028, private credit will provide over half of the $1.5 trillion in external financing needed for data center construction, becoming a main funding source in the AI industry chain. Under such a financing structure, if market sentiment turns conservative and private credit funding tightens, it could increase the risk of funding disruptions, adversely affecting corporate expansion and profitability.

A: Risks of private credit are concentrated in NeoCloud

[Content truncated for brevity; see original for full details.]

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Click questions to let MM AI answer for you
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Does rising private credit risk threaten a systemic crisis?
💡 Although private credit risks have surfaced, most bank exposures to NDFIs are controlled, and default rates remain low, indicating defaults are mostly isolated incidents. The likelihood of a systemic crisis is therefore low.
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What risks arise from AI capital expenditure dependence on private credit?
💡 As AI-related capital spending increasingly relies on private credit, especially for NeoCloud firms, a shift to conservative market sentiment and credit tightening could raise funding disruption risks, impacting growth and profitability.
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Will AI development cause a surge in unemployment and lead to recession?
💡 Short-term AI may cause some job displacement, but long-term effects include new job creation and productivity gains. US economic growth and per capita productivity improvements suggest AI’s impact isn’t entirely negative; a sharp rise in unemployment and recession remains uncertain.
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Can AI’s recovery effects surpass substitution effects to promote employment?
💡 AI’s recovery effects are expected to outweigh substitution effects. Although initial layoffs may occur, as AI technology matures and costs decrease, more new jobs are likely to be created, and AI has already demonstrated productivity enhancements.
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Do SaaS companies with three major barriers still hold advantages in the AI era?
💡 SaaS companies with permission, data, and technology barriers will still have advantages. These barriers enable enterprise AI to deepen data, processes, and systems, integrating with existing workflows to strengthen rather than replace current services, ensuring continued revenue and growth prospects.
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Is there a risk of over-ordering in the AI hardware supply chain?
💡 AI hardware supply chains face potential over-ordering risks. Nvidia’s rising inventory days, with raw materials shifting to work-in-progress and finished goods, indicate pre-shipment stockpiling before large-scale shipments in GB300. Monitoring inventory changes in the first half of 2026 is necessary to confirm over-ordering risks.
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How to effectively allocate assets amid multiple market concerns?
💡 In the face of multiple market concerns, diversified allocation remains the best strategy. Focus on “technology” as the core, and categorize other sectors into “offensive” and “defensive” based on risk appetite and market sentiment, adjusting flexibly to capital flows.