【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 in 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 regarding AI capital expenditure reliance on private credit?
Q3: Will AI cause a surge in unemployment and lead to a recession?
Q4: Is SaaS facing a doomsday scenario? Will AI dismantle its traditional moat?
Q5: Are there risks in AI hardware as well?

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 failures of regional banks like Zions Bancorp and Western Alliance, as well as 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 reaching their redemption limits.

These opaque, non-deposit financial institutions (NDFIs) continue to face risk events, prompting market memories 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 US KBW Bank Index also dropped as much as -6% intraday on 2/27 following the MFS 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 limited. According to S&P Global Market Intelligence, among the top 20 US banks by NDFI loan holdings 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 failures are mostly isolated incidents, and the overall situation remains stable.

Q: AI capital expenditure reliance on private credit—what should we watch?

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—these private companies, lacking access to public markets, rely heavily on private credit. Both factors further reinforce private credit’s role in the AI supply chain.

Morgan Stanley estimates that by 2028, more than half of the $1.5 trillion in external financing needed for data center construction will come from private credit, making it a major funder in the AI industry chain. Under such a financing structure, if market sentiment turns cautious and private credit funding tightens, the risk of funding disruptions increases, potentially impairing corporate expansion and profitability.

A: Risks in private credit are concentrated in NeoCloud

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Click questions to let MM AI answer for you

Does rising private credit risk trigger systemic crises?
💡 Although private credit risks have surfaced, most bank exposures to NDFIs are controlled, and default rates remain low, indicating failures are mostly isolated incidents. The likelihood of a systemic crisis is therefore low.

What risks does AI’s reliance on private credit pose?
💡 As AI’s capital expenditure reliance on private credit increases—especially for emerging NeoCloud players—if market sentiment turns cautious and funding tightens, the risk of funding disruptions rises, affecting growth and profitability.

Will AI development cause a surge in unemployment and economic recession?
💡 Short-term AI may cause some job displacement, but long-term effects include new tasks and job opportunities. US economic growth and productivity gains suggest AI’s impact isn’t entirely negative; a sharp rise in unemployment and recession remains uncertain.

Can AI’s recovery effects surpass substitution effects to promote employment?
💡 AI’s recovery effects are expected to surpass substitution effects. Although initial layoffs may occur, rapid AI progress and cost reductions will likely create new jobs, and AI has already demonstrated productivity improvements.

Do SaaS companies with three major barriers still hold advantages in the AI era?
💡 SaaS companies with permission, data, and technology barriers still have advantages. These barriers enable enterprise AI to deepen data, processes, and systems, reinforcing rather than replacing existing services, and supporting sustained revenue growth.

Is there a risk of over-ordering in the AI hardware supply chain?
💡 The AI hardware supply chain faces potential over-ordering risks. Nvidia’s rising inventory days, with raw materials shifting to work-in-progress and finished goods, indicate pre-shipment stockpiling. Monitoring inventory changes in the first half of 2026 is necessary to confirm over-ordering.

How to effectively allocate assets amid multiple market concerns?
💡 In the face of multiple market concerns, diversified allocation is 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.

Market Quick Reports:

• Middle East out of control, four key turning points after oil surpasses $100! (2026-03-09)
• US and Israel’s intense strikes, oil and gas surge, full analysis of Middle East war! (2026-03-03)

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