The global banking environment, still navigating the aftershocks of US-China trade tensions, elevated interest rates, and a battered commercial real estate sector, United Overseas Bank’s Q4 2025 earnings briefing offered something increasingly rare: measured reassurance. The Singapore lender’s leadership told analysts and investors on Monday that provisions set aside for its most closely watched exposures—Greater China and US commercial real estate—remain more than sufficient, even as the broader sector braces for a prolonged period of uncertainty.

For investors who have spent the better part of two years watching regional bank balance sheets with a mix of hope and dread, that message carries real weight.

Slowing Bad-Debt Formation: A Quiet but Meaningful Shift

Perhaps the most encouraging signal from UOB’s Q4 briefing was the deceleration in new non-performing asset (NPA) formation. The bank recorded S$599 million in new NPA formation in Q4 2025, a meaningful improvement from the S$838 million logged in Q3. That’s a quarter-on-quarter decline of roughly 29%—not a dramatic reversal, but in the language of credit risk, a deceleration of that magnitude deserves attention.

To put it plainly: bad debts are still forming, but they’re forming more slowly. In credit cycle terms, this is often the first sign that the worst may be passing.

Group CFO Leong Yung Chee, speaking at the briefing alongside Deputy Chairman and CEO Wee Ee Cheong, characterised pre-emptive provisions for commercial real estate “hot spots” in Greater China and the United States as adequate buffers against potential future bad debts. That language—pre-emptive—is telling. UOB did not wait for losses to crystallise before building reserves. It anticipated stress and prepared for it. As Bloomberg has reported, Singapore banks have faced persistent scrutiny over their Hong Kong and China property loan exposures, making this kind of forward provisioning strategically critical.

Adequate Buffers for High-Risk Exposures

The headlines around UOB’s Greater China and US portfolios have not always been comfortable reading. But the numbers presented Monday suggest the bank has managed these concentrations with discipline.

On US commercial real estate, the CFO confirmed that problematic loans account for approximately 1% of UOB’s local US portfolio—a figure that, in the context of what has unfolded in American office and retail property markets since 2022, is remarkably contained. For context, several mid-tier US regional banks have seen CRE stress levels multiples higher, contributing to a string of failures and near-misses that Reuters has documented extensively.

For Greater China, the bank’s pre-emptive provisioning strategy has been running since the early tremors in China’s property sector became impossible to ignore. With Chinese developer defaults and Hong Kong office vacancies still elevated, UOB’s conservative stance now looks prescient rather than overcautious.

Key Metrics at a Glance:

The halving of allowances for credit and other losses—from S$227 million a year earlier to S$113 million in Q4 2025—reflects lower specific allowances, a signal that the bank is not being forced into emergency provisioning on newly distressed assets. That’s a meaningful distinction.

Stable NPL Ratio and an Unchanged Credit Outlook

UOB’s non-performing loan (NPL) ratio held steady at 1.5% in Q4, unchanged from the prior quarter. Stability here is underrated. In an environment where several global banks have seen NPL ratios creep upward under the combined weight of higher-for-longer interest rates and slowing trade volumes, a flat 1.5% is a credible result.

The bank also maintained its credit cost guidance at 25 to 30 basis points for the period ahead—a range that signals neither complacency nor alarm. It reflects an institution that has stress-tested its books honestly and arrived at a considered, defensible estimate of forward losses.

How UOB Compares to Its Singapore Peers

UOB does not operate in a vacuum. Singapore’s banking sector—anchored by the “Big Three” of DBS, OCBC, and UOB—is among the most closely watched in Asia, and cross-peer comparison matters to both investors and regulators.

DBS Group, Singapore’s largest bank, reported a 10% drop in Q4 net profit, weighed down by rising allowances and fee income headwinds. That result rattled some investors, though DBS management attributed a portion of the provision build to proactive risk management rather than asset deterioration. OCBC, meanwhile, has been expected to report relatively stable net interest margins (NIMs) as its asset-liability mix has benefited from the elevated rate environment—though NIM compression risk remains live as global central banks edge toward easing cycles.

Against this backdrop, UOB’s Q4 print reads as the more cautiously optimistic of the three. It has neither DBS’s sharp profit dip nor the NIM sensitivity questions surrounding OCBC. What it does have is a provisioning track record that appears, at least for now, to have gotten ahead of the curve.

Broader Economic Implications for ASEAN Banking

The UOB briefing is not just a story about one bank. It is a data point in a much larger narrative about how ASEAN’s financial institutions are navigating a world reshaped by US-China strategic competition, deglobalization pressures, and the slow unwinding of the post-pandemic rate cycle.

The Financial Times and The Economist have both noted that Southeast Asian banks occupy a peculiar geopolitical sweet spot—exposed to both the Chinese economic sphere and the dollar-denominated global financial system, and therefore vulnerable to friction in both directions. UOB, with its pan-ASEAN franchise spanning Thailand, Malaysia, Indonesia, and Vietnam, is particularly exposed to trade flow disruptions. If US tariffs on Chinese goods accelerate supply chain reshuffling into Southeast Asia, UOB could benefit from the financing boom that tends to accompany such relocations. If, however, the tariff regime suppresses regional growth broadly, credit quality across its ASEAN book faces pressure.

The credit cost guidance range of 25 to 30 basis points implicitly acknowledges this dual-sided risk. It is conservative enough to absorb a modest deterioration in the macro environment, but not so elevated as to suggest the bank sees a crisis on the horizon.

Conclusion: Resilience Maintained, Vigilance Required

UOB’s Q4 2025 earnings briefing delivered what its leadership likely hoped for: a credible narrative of stability without complacency. The slowdown in NPA formation, the adequacy of Greater China and US CRE buffers, the unchanged NPL ratio, and the maintained credit cost guidance all tell a story of an institution that managed its risks carefully through a turbulent year.

But the story is not finished. US commercial real estate faces structural challenges that are unlikely to be resolved within a single business cycle. Greater China’s property sector remains in a drawn-out adjustment. And the geopolitical environment—US-China trade friction, rate uncertainty, ASEAN growth volatility—continues to generate tail risks that no provision buffer can fully insulate against.

What Monday’s briefing demonstrated is that UOB entered 2026 with its balance sheet integrity intact and its risk management credibility undamaged. For the Singapore banking sector resilience in Q4 2025, that may be the most important headline of all.

The atmosphere at the India AI Impact Summit in New Delhi this February 2026 made one reality unavoidably clear: the US China AI race is no longer a straightforward sprint to a singular finish line. Instead, we are witnessing the entrenchment of an asymmetric bipolarity. For global economists, corporate strategists, and policymakers, the AI competition US China has evolved from a theoretical technology battle into a grinding, multipolar war over supply chains, energy grids, and the economic allegiance of the Global South.

To understand the true stakes of US vs China AI supremacy, we must discard the simplistic, moralizing narratives of Cold War 2.0. As an analyst watching the tectonic plates of the global economy shift, the reality is far more nuanced. The question of AI leadership US China is not merely about who builds the smartest chatbot; it is about who controls the underlying thermodynamics of the future economy.

In this comprehensive analysis, we will demystify the geopolitics of AI race dynamics, cutting through the hype to examine the real-time tradeoffs, capital constraints, and data-driven realities defining 2026.

The Illusion of a Single Finish Line in the US China AI Race

Western media often frames the US China AI race as a zero-sum game of frontier models. However, Time’s recent February 2026 analysis correctly notes that there are, in fact, multiple overlapping races. While the United States continues to dominate closed-source, highly capitalized frontier models, China has pivoted toward a radically different theory of value: rapid, low-cost diffusion.

The AI competition US China shifted permanently with the “DeepSeek shock” and the subsequent surge of open-source models. When Alibaba released Qwen 2.5-Max—surpassing 1 billion downloads globally—it proved that Chinese developers could achieve near-parity with US models at a fraction of the computational cost. As CNN reported in February 2026, China’s AI industry is utilizing algorithmic efficiency to circumvent hardware limitations.

This dynamic explains the pragmatic, if politically fraught, decision in January 2026 to loosen US export controls on Nvidia H200 chips. The move was a stark acknowledgment of global interconnectedness: starving China of chips entirely risks accelerating their indigenous semiconductor ecosystem while severely denting the bottom lines of American tech champions. In the battle for US vs China AI supremacy, capital requires market access just as much as it requires compute.

Key Divergences in the AI Competition US China

• US Strategy (Innovation & Capital): High-end chips, hyperscale data centers, closed-source models (OpenAI, Anthropic), and massive capital concentration.
• Chinese Strategy (Diffusion & Application): Open-source models (DeepSeek, Qwen), industrial deployment, legacy chip scale, and aggressive pricing to capture emerging markets.

The Core Battlegrounds: Compute, Chips, and Energy Bottlenecks

You cannot discuss the geopolitics of AI race dynamics without discussing thermodynamics. Artificial intelligence is, fundamentally, electricity transformed into computation. Here, the US vs China AI supremacy narrative takes a politically incorrect but entirely substantiated turn.

The US undeniably leads in compute. According to the Federal Reserve’s late-2025 data, the US commands a staggering 74% global share of advanced compute capacity. Furthermore, as Reuters reported, US AI investments are projected to hit $700 billion in 2026. However, American capital advantages face a severe domestic bottleneck: regulatory holdups and grid limitations. Building a hyperscale data center in the US requires navigating localized zoning, environmental reviews, and grid interconnection queues that can take years.

Conversely, China’s state-controlled model enables faster scaling of physical infrastructure. While the Brookings Institution’s January 2026 report highlights the contrasting energy strategies, the raw numbers are sobering. By 2030, China is projected to have 400 GW of spare energy capacity, heavily subsidized by state directives (Bloomberg, Nov 2025).

The Asymmetric Matrix: US vs China Advantages

The Geopolitics of AI Race: Courting the Global South

The geopolitics of AI race extends far beyond Silicon Valley and Shenzhen. As highlighted at the New Delhi summit, the Global South is actively refusing to be relegated to mere consumers in the US China AI race.

For middle powers and developing economies, the AI leadership US China paradigm offers a stark choice. US closed-source models are highly capable but computationally expensive and heavily paywalled. In contrast, China is weaponizing open-source AI as a form of geopolitical diplomacy. By flooding the Global South with highly capable, free, or hyper-cheap models like Qwen and DeepSeek, Beijing is embedding its digital architecture into the foundational infrastructure of developing nations.

As Foreign Affairs noted in its February 2026 “The AI Divide” issue, this dynamic creates a new non-aligned movement. Countries like India, Saudi Arabia, and the UAE are hedging their bets. They purchase US hardware where possible but eagerly adopt Chinese open-source models to build “sovereign AI” capabilities. To win the geopolitics of AI race, the US cannot simply sanction its way to the top; it must offer a compelling, cost-effective alternative to Chinese digital infrastructure.

Capital Flow vs. Regulatory Bottlenecks: A Politically Incorrect Reality

To truly understand US vs China AI supremacy, we must look at how each system translates capital into productive capacity. A recent CSIS geoeconomics report provides a sobering multiperspective analysis: the US is optimized for a pathway dependent on high-end chips and continuous model scaling, heavily indexed to stock market expectations.

In the AI competition US China, America’s greatest strength—its free-market capital—is concurrently its Achilles’ heel. Trillions of dollars in market capitalization rely on the promise of Artificial General Intelligence (AGI) and sustained productivity gains. If regulatory holdups prevent the physical building of power plants to support this compute, the capital bubble risks deflating.

Meanwhile, China’s industrial policy suppresses firm-level valuations (to the detriment of its stock market) but excels at embedding AI into its leading industrial sectors, such as robotics and electric vehicles. As the Council on Foreign Relations (CFR) emphasized late last year, China’s approach guarantees that even if its frontier models lag by a few months, its factories will not. The US China AI race is therefore a test of whether America’s financialized innovation can outpace China’s state-directed diffusion.

The Path Forward: Redefining AI Leadership US China

The AI leadership US China debate is ultimately about resilience. The global supply chain is too interconnected to fully de-risk. America relies on TSMC in Taiwan, which relies on ASML in the Netherlands, to produce the chips that fuel the US China AI race.

For the United States to secure long-term AI leadership US China, it must transcend a purely defensive posture of export controls and tariffs. True US vs China AI supremacy will belong to the power that not only innovates at the frontier but scales those innovations globally. As Forbes analysts have routinely pointed out, democratic techno-alliances must move beyond rhetorical agreements and start co-investing in physical compute infrastructure, energy grids, and open-source ecosystems tailored for the Global South.

The AI competition US China will define the economic hierarchy of the 21st century. But victory will not be declared in a single moment of algorithmic breakthrough. It will be won in the trenches of grid interconnections, the boardrooms of middle powers, and the quiet diffusion of productivity across the global economy.

Next Steps for Democratic Alliances: To maintain relevance and leadership, Western coalitions must prioritize “compute diplomacy”—subsidizing energy-efficient AI infrastructure and accessible models for emerging markets, rather than ceding the open-source landscape entirely to Beijing. Would you like me to dive deeper into the specific policy frameworks the US could use to counter China’s open-source diplomacy in the Global South?

China’s state-backed industrial machine is running at full throttle — but the International Monetary Fund says the fuel costs are crippling the very economy it’s meant to supercharge.

In a sweeping set of policy recommendations that span from Beijing’s factory floors to global supply chains, the International Monetary Fund has delivered its clearest call yet for China industrial policy reform: slash state subsidies to industry from roughly 4 percent of GDP to around 2 percent, redirect those savings toward social welfare spending, and pivot the world’s second-largest economy away from export-led manufacturing toward domestic consumption. The message is urgent, data-backed, and geopolitically loaded.

This is not a bureaucratic nudge. It is a diagnosis of a fundamental imbalance — one with consequences that ripple from the steel mills of Wuhan to the factory floors of Michigan, the automotive plants of Stuttgart, and the solar panel markets of Mumbai.

The 4 Percent Problem: What IMF China Subsidies Research Actually Found

The numbers at the heart of this debate come from IMF Working Paper No. 2025/155, a landmark study published in August 2025 that, for the first time, comprehensively quantified the full fiscal cost of China’s industrial policy apparatus. The findings were striking:

• Cash subsidies account for approximately 2.0 percent of GDP annually
• Tax benefits add another 1.5 percent of GDP
• Subsidized land contributes 0.5 percent of GDP
• Subsidized credit adds a further 0.4 percent of GDP
• Combined total: roughly 4 percent of GDP per year — equivalent to well over $700 billion at current exchange rates

To put that in perspective: China’s annual industrial policy expenditure rivals the entire GDP of Switzerland. The beneficiaries are concentrated heavily in sectors flagged under Beijing’s “Made in China 2025” strategic plan — chemicals, machinery, electric vehicles, metals, and semiconductors. By 2022, the number of subsidies flowing into these strategic sectors had nearly quadrupled compared to 2015.

Yet here is the paradox that IMF China subsidies reduction advocates keep returning to: all this spending is quietly undermining the very productivity it claims to boost.

The Hidden Drag: 1.2 Percent Productivity Loss

The IMF’s structural modeling reveals a striking inefficiency at the core of Beijing’s industrial strategy. By distorting how capital and labor are allocated across the economy — a phenomenon economists call “factor misallocation” — China’s industrial policies are estimated to reduce aggregate total factor productivity (TFP) by approximately 1.2 percent. That is not a rounding error. For an economy of China’s scale, a 1.2 percent productivity drag represents hundreds of billions of dollars in foregone output every year.

The mechanics differ by policy instrument. Cash subsidies and subsidized credit tend to encourage excess production — factories churn out more than the market can absorb, leading to the gluts in steel, aluminum, and electric vehicles that have triggered trade disputes from Brussels to Washington. Trade and regulatory barriers, by contrast, suppress production in sectors that might otherwise thrive, distorting resource allocation in the opposite direction.

The net result, as discussed in CEPR’s analysis of China’s industrial policy costs, is an economy that is simultaneously over-producing in some industries and under-investing in others — a structural imbalance that feeds directly into deflation, weak domestic demand, and swelling trade surpluses.

IMF Recommendations for China’s Economy: The Reform Blueprint

The Fund’s 2025 Article IV Consultation with China, concluded in December 2025 and formally endorsed by the IMF Executive Board in February 2026, frames IMF recommendations for China’s economy around three interlocking priorities.

1. Scale back industrial subsidies — urgently. The IMF’s call to roughly halve support from 4 percent to around 2 percent of GDP is not merely about fiscal savings. It is about forcing market discipline back into an economy where state preferences have increasingly crowded out private-sector dynamism. Freed-up fiscal resources should be redirected toward social protection: healthcare, pensions, childcare, and expanded coverage for China’s 300 million-plus migrant workers under Hukou reform.

2. Rebalance toward consumption-led growth. IMF Managing Director Kristalina Georgieva, speaking at the 2025 Article IV press conference, was direct: China has the opportunity to reach “a new stage in its economic development, in which its growth engine switches from investment and exports to domestic consumption.” The Fund estimates that boosting social spending — particularly in rural areas — combined with Hukou reform could lift consumption by up to 3 percentage points of GDP in the medium term.

3. Structural reforms to lift long-term growth. These include reducing regulatory burdens, lowering barriers to internal trade (especially in services), leveling the competitive playing field between state-owned and private enterprises, and addressing persistent youth unemployment.

The payoff, the IMF calculates, is substantial: material progress on all three fronts could lift China’s GDP by about 2.5 percent by 2030, generate approximately 18 million new jobs, and meaningfully reduce both deflationary pressures and the current account surplus — currently running at an estimated 3.3 percent of GDP in 2025, up sharply from 2.3 percent the year before.

Global Trade Impact of China Subsidies: A World on Edge

The global trade impact of China subsidies has become one of the defining fault lines of 21st-century economic diplomacy. Beijing’s subsidized exports have suppressed prices in sectors from solar panels and electric vehicles to steel and furniture across dozens of markets. The IMF’s own 2024 working paper on trade implications found that Chinese subsidies not only boosted the country’s own exports and depressed imports, but amplified these effects through supply-chain linkages — subsidies given to upstream industries expand the export competitiveness of downstream sectors in ways that compound and cascade globally.

The resulting overcapacity has fed a wave of trade countermeasures. The European Union has imposed tariffs on Chinese electric vehicles. The United States has layered tariffs on a broad range of Chinese manufactured goods. India, Brazil, and other emerging markets are increasingly deploying anti-dumping investigations. The IMF’s call for IMF China subsidies reduction is, in this context, as much a diplomatic signal as an economic one — a multilateral institution urging Beijing to defuse tensions by reforming the policies at their source.

For global businesses and policymakers tracking the global trade impact of China subsidies, the IMF’s framework offers a rare piece of analytical clarity in what has otherwise been a fog of political rhetoric.

China’s Balancing Act: Resilience Meets Structural Fragility

None of this is to suggest China’s economy is in crisis. Far from it. The IMF projects GDP growth of 5 percent in 2025 — meeting the government’s target — and 4.5 percent in 2026. China accounts for roughly 30 percent of global growth. Its export machine, fueled in part by the very subsidies the IMF wants curtailed, has been a pillar of resilience.

But the structural tensions are real and deepening. Headline inflation averaged 0 percent in 2025. The GDP deflator continued to decline. Consumer confidence remains fragile. The property sector, once a locomotive of growth, has shifted into a slow-motion adjustment that is compressing local government finances and dragging on household wealth. The yuan, weakened in real terms relative to trading partners, has kept exports competitive but contributed to external imbalances the rest of the world finds increasingly difficult to absorb.

The China economic shift toward consumption that the IMF envisions would address all of these dynamics — but it requires the government to consciously redirect resources from the industrial sector it has long prioritized toward households it has long expected to save.

Modeling the Reform Scenarios: What Halving Subsidies Could Mean

Consider two scenarios, based on IMF modeling assumptions:

Scenario A — Partial Reform (subsidies cut to 3 percent of GDP): Factor misallocation eases modestly. TFP improves by approximately 0.4–0.6 percent. Fiscal savings of roughly 1 percent of GDP are partially redirected to social spending, nudging household consumption upward. Trade tensions moderate but do not resolve. Net GDP benefit by 2030: modest.

Scenario B — Full Reform (subsidies cut to 2 percent of GDP, per IMF target): Factor misallocation falls sharply. TFP gains approach the full 1.2 percent identified in the working paper. Fiscal savings fund meaningful social protection expansion, boosting consumption by up to 3 percentage points of GDP over the medium term. Current account surplus narrows. Trade tensions ease. GDP gains of 2.5 percent by 2030 materialize. Eighteen million new jobs created.

The second scenario is economically compelling. It is also politically difficult. China’s industrial policy apparatus is not just an economic tool — it is a statement of geopolitical ambition, a mechanism for technological self-sufficiency, and a source of local government revenue and employment. The IMF knows this. Its language is careful, constructive, and notably free of ultimatums.

Conclusion: A Reform Window That Won’t Stay Open Forever

The IMF’s call for China to halve its industrial subsidies is the most precisely calibrated version yet of an argument the global economic community has been making for years: that China’s current growth model, for all its undeniable successes, is generating costs — domestic and global — that are becoming increasingly hard to ignore.

The data on IMF China subsidies reduction is unambiguous. A 4-percent-of-GDP industrial policy bill that drags productivity by 1.2 percent, inflates trade surpluses, fuels global overcapacity, and suppresses household consumption is not a foundation for durable prosperity. It is a structural vulnerability dressed up as industrial strength.

China’s leaders have signaled their awareness of the challenge. The 15th Five-Year Plan explicitly names the transition to consumption-led growth as a strategic objective. But as the IMF’s Georgieva noted pointedly in December 2025, the economy is like a large ship — changing course takes time. The question is whether the wheel is being turned with sufficient force and speed.

For businesses navigating global supply chains, investors pricing geopolitical risk, and policymakers from Washington to Brussels, the answer to that question will define much of the decade ahead. As discussed in broader analyses of global trade impacts, the trajectory of China economic policy reform is not a regional story — it is the central economic narrative of our time.