【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 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, indicating that market scrutiny is tightening and valuation correction risks are rising.

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 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 the SaaS doom theory valid? 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 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 face risk events, prompting market recall of JPMorgan Chase CEO Jamie Dimon’s warning last year: “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 after the MFS bankruptcy news on 2/27, 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 liquidity crises, 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 means that even if widespread defaults occur among NDFIs later, it is unlikely to spread to the entire financial system causing a 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, suggesting that current defaults 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 cover the massive capital expenditures needed for AI infrastructure, increasing external financing demand. On the other hand, in the AI era, more unlisted unicorns valued over $1 billion are likely to emerge—these private companies, lacking public market financing channels, especially rely on private markets. Both factors further reinforce private credit’s role 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, 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 on questions to get answers from MM AI
                        

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                                            Is the rising risk in private credit likely to trigger a systemic crisis?
                                        
                                        

                                            💡 Although private credit risks have surfaced, since bank exposure to NDFIs remains manageable and default rates are still low, the likelihood of a systemic crisis is relatively low.
                                        

                                    

                                
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                                            What risks does AI’s reliance on private credit for capital expenditure pose?
                                        
                                        

                                            💡 As AI-related capital expenditure reliance on private credit increases, especially among emerging NeoCloud companies, a shift to conservative market sentiment and tighter funding could raise funding disruption risks, affecting expansion and profitability.
                                        

                                    

                                
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                                            Will AI development cause a significant rise in unemployment and lead to a recession?
                                        
                                        

                                            💡 In the short term, AI may cause some unemployment due to substitution effects, but in the long term, AI’s recovery effects are expected to create new jobs and opportunities. US economic growth and productivity gains suggest AI’s impact is not entirely negative, and a sharp rise in unemployment leading to a 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 surpass 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 its ability to boost per capita productivity.
                                        

                                    

                                
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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 still hold advantages in the AI era. These barriers ensure enterprise-level AI integration into data, processes, and systems, reinforcing rather than replacing existing services, and continue to deliver strong revenue and growth prospects.
                                        

                                    

                                
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                                            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 inventory days have increased, with raw materials shifting to work-in-progress and finished goods, indicating stocking needs before large shipments of 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, appropriate diversification is the best strategy. Core allocation should focus on “technology,” with other sectors divided into “offensive” and “defensive” categories, adjusting flexibly based on risk appetite and market sentiment to navigate capital rotation.
                                        

                                    

                                
                                                

                
                
                

                

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