THE WHITE HOUSE
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THE GREAT TRANSSHIPMENT SCAM
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RISE, SCOPE, AND COSTS
OFFICE OF TRADE AND MANUFACTURING POLICY
AUGUST 2026
Executive Summary
The United States faces a growing challenge from the illegal transshipment of goods through third countries to evade applicable tariffs and other trade remedies. Exporters in higher-tariff jurisdictions can abuse differences in U.S. tariff treatment across countries to route goods through lower-tariff jurisdictions before entering the American market. Illegal transshipment may involve relabeling, repackaging, re-invoicing, minor processing, false country-of-origin claims, or other actions intended to secure tariff treatment that would not apply if the goods’ true economic origin were declared.
President Trump’s tariff actions have helped to protect U.S. workers and industry, and his Administration has taken stronger actions against countries that pose larger economic challenges. However, the expansion of differentiated tariffs in 2025 has significantly increased the importance of effective transshipment enforcement. Tariff differentials are necessary to address differences in trading practices and levels of reciprocity, but they also create opportunities for arbitrage and evasion. Any higher-tariff country may seek access to the U.S. market through a lower-tariff country, and any lower-tariff jurisdiction may benefit from serving as a production, processing, warehousing, or logistics intermediary for higher-tariff countries.
China provides the most developed historical example of this conduct. Following the imposition of Section 301 tariffs in 2018, the direct U.S. trade deficit with China fell in 2019 and 2020. Even today, imports of a number of Chinese products subject to these original duties, like electric vehicles, are much lower in the U.S. than in places like the European Union. But the overall success of these tariffs co-exists with the abuse, by exporters, of the tariff differentials that they contribute to. After their imposition, Chinese exporters increasingly routed goods through third countries. Products that previously moved directly from China to the United States were shipped through jurisdictions where limited assembly, finishing, repackaging, relabeling, or documentation changes could create the appearance of a different national origin. Over time, these practices contributed to the development of a global network of production hubs, logistics platforms, free-trade zones, bonded warehouses, processing corridors, and re-export centers.
This report identifies more than 40 countries associated with elevated illegal transshipment risk. These jurisdictions vary significantly in economic scale and function. Some are major trading partners with diversified industrial bases and large volumes of overall commerce. Others are closely integrated into China-linked production and supply networks. A third group consists of smaller jurisdictions that offer specific advantages, including low labor costs, permissive free-zone rules, strategic port access, bonded warehousing, limited customs capacity, niche assembly operations, or preferential access to the U.S. market.
The network operates through both production-side and logistics-side channels. Production-side nodes may perform light assembly, finishing, testing, packaging, labeling, inspection, or component integration before export to the United States. Logistics-side nodes may primarily provide routing, consolidation, warehousing, re-invoicing, relabeling, or new export documentation. Effective enforcement therefore requires distinguishing legitimate manufacturing and substantial transformation from pass-through trade and origin shifting.
The available data show a substantial reallocation of U.S. import sourcing following the 2018 tariffs. As China’s direct share of U.S. goods imports declined, the combined share supplied by identified transshipment countries increased. This relationship does not establish that all displaced
Chinese trade was illegally transshipped. Some of the shift reflects legitimate changes in production, investment, and sourcing. However, the timing, magnitude, and direction of the two trends support further investigation of the extent to which tariffed goods were rerouted through third countries.
This report reviews five government and private-sector estimates of potential transshipment or related trade-transfer exposure. The estimates range from approximately $40 billion to $303 billion annually, depending on the methodology and definition used.
Goldman Sachs provides the narrowest estimate by isolating the rerouting channel. The White House Council of Economic Advisers estimates potential illegal transshipment in a range of $34.2 billion to $89.6 billion, and this report uses a rounded midpoint of $60 billion. Exiger develops a central estimate of approximately $75 billion based on product-level and shipment-flow analysis. The Department of Commerce identifies a broader $109 billion trade-transfer benchmark and separately estimates approximately $67 billion in 2025 illegal transshipment through leading hubs. Altana’s $303 billion estimate represents a broad upper-bound exposure measure.
These estimates are not additive and are not directly comparable. They use different datasets, methodologies, product screens, and definitions of illegal transshipment. Nevertheless, they converge on the conclusion that the scale of potential tariff evasion and origin shifting is economically significant.
Applying illustrative tariff differentials of 25, 35, and 45 percent produces annual tariff-revenue-loss estimates ranging from approximately $10 billion under the narrowest case to more than $100 billion under the broadest exposure case. The report’s central estimates indicate annual tariff losses in the tens of billions of dollars. These calculations understate losses in product categories subject to additional antidumping and countervailing duties, where the total avoided duty can substantially exceed ordinary tariff rates.
The report also estimates broader economic effects associated with displaced domestic production. Under a central case of $75 billion in annual illegal transshipment, the report estimates approximately 450,000 jobs displaced; $113 billion to $150 billion in reduced annual gross domestic product; and $19 billion to $26 billion in associated federal revenue losses. These figures are model-based estimates rather than observed job counts. They are intended to illustrate the potential scale of the economic exposure.
The effects are concentrated in specific manufacturing sectors and communities. The report links foreign illegal transshipment-risk corridors to U.S. industrial regions producing similar goods, including electrical equipment, integrated circuits, pumps, compressors, plastics, thermostats, cable assemblies, aluminum products, and motor components. These comparisons illustrate how tariff evasion can translate into lost orders, reduced capacity utilization, and employment pressure in American manufacturing communities.
The Trump Administration has taken steps to strengthen transshipment enforcement. Agreements on Reciprocal Trade include provisions designed to prevent agreement benefits from accruing substantially to third countries. Executive Order 14411 (Customs EO) strengthens customs enforcement by addressing importer accountability, bonding, domestic assets, ownership disclosure, business affiliations, good-standing requirements, penalties, and trade transparency.
The report also outlines an AI-enabled “Detective Border” that would support U.S. Customs and Border Protection (CBP) by integrating shipment data, routing histories, product classifications,
ownership relationships, production-capacity indicators, anomaly detection, computer vision, and other analytical tools. The objective is to improve CBP’s ability to distinguish legitimate nearshoring and foreign investment from illegal pass-through trade, identify high-risk shipments, and convert analytical findings into interdiction, duty collection, penalties, and exclusion.
It is too early to determine the net effect of the Administration’s tariff and anti-transshipment policies. Trade and customs data become available with a lag, and several enforcement provisions remain under implementation. The Administration will need to evaluate future data to determine whether transshipment volumes, tariff losses, and associated economic costs are declining. This report establishes a framework for that continuing assessment and for strengthening the integrity of the U.S. tariff system.
Introduction
Every year, the United States loses tens of billions of dollars to the illegal transshipment of goods from higher-tariff countries through more than 40 lower-tariff jurisdictions before those goods enter the American market. Historically, much of this activity has involved Chinese-origin goods.
Illegal transshipment is driven by exporters taking advantage of differences in U.S. tariff treatment across countries. When a product faces a higher U.S. tariff because it originates in one country, exporters have a greater incentive to route it through another country where a lower tariff applies. But it is important to differentiate tariffs based on each country’s varying circumstances, even if this differentiation creates opportunities that exporters will try to abuse. That is because these tariff differentials are necessary to address differences in trading practices and levels of reciprocity.
In 2025, the Trump Administration raised tariffs on numerous countries, with some countries facing higher rates than others. Those differentials, standing alone, can increase the incentive to illegally transship.
At the same time, the Trump Administration has taken significant steps to prevent and deter transshipment. Some of these measures are embedded in Agreements on Reciprocal Trade, or ARTs. These agreements contain a first-of-its-kind provision allowing a signatory to “establish rules of origin necessary” to prevent the “benefits of this Agreement [from] accruing substantially to third countries,” including through illegal transshipment. In 2026, President Trump also signed Executive Order 14411, which gives U.S. Customs and Border Protection (CBP) additional tools to crack down on transshipment by strengthening customs enforcement and increasing trade transparency.
The second Trump Administration’s efforts to combat illegal transshipment reflect, in part, lessons learned during the first Trump Administration. When the first Administration imposed historic tariffs on China, exporters responded in part by increasing illegal transshipment through third countries. The second Administration has therefore paired its tariff program with historic new measures designed to detect, deter, and prevent such evasion.
The net effect of the second Trump Administration’s trade policies on illegal transshipment remains unresolved. On one hand, tariff differentials can increase the incentive to illegally transship. On the other, the Administration’s anti-transshipment measures are intended to counteract that incentive by increasing the likelihood and cost of detection.
Under the second Trump Administration, U.S. Customs and Border Protection has utilized existing authorities to strengthen trade enforcement operations. According to CBP data comparing the 526-
day periods before and after the inauguration, shipments identified with post-release discrepancies increased 245%—rising from 93,744 to 323,677—while associated revenue assessments increased 169%, growing from $9.6 billion to $25.8 billion.
Which of these effects will prevail cannot yet be determined rigorously. A sound assessment of net effects requires trade and customs data that become available only after a significant lag. In addition, CBP has not yet fully implemented several provisions of the recently signed Executive Order 14411. For these reasons, the overall impact of the second Trump Administration’s tariff and anti-transshipment policies cannot yet be measured with the rigor the question deserves.
While the future may be murky, the past is not. The second Trump Administration inherited a Great Transshipment Scam—a witch’s brew of economic incentives, bad actors, and lax enforcement that had been allowed to simmer and grow more toxic over time.
This report documents the rise, scope, and costs of the Great Transshipment Scam. It offers a taxonomy of the methods through which the scam has operated and imposed economic harm.
Using a novel geographic matching methodology, it then traces potential exposure from selected foreign illegal transshipment-risk hubs across Asia and the Americas to American manufacturing corridors across the country.
Finally, the report looks ahead to the AI-enabled Detective Border being developed to detect and disrupt illegal transshipment, as well as to the eventual evaluation of the second Trump Administration’s anti-transshipment policies.
The Historical Predicate
In plain terms, illegal transshipment is smuggling disguised as trade—fraud cloaked in paperwork—and, in truth, nothing new. For centuries, traders have routed goods through third countries to exploit tariff gaps, dodge imperial duties, skirt embargoes, and take advantage of preferential access offered by certain ports.
What has changed in today’s Great Transshipment Scam is not merely the speed and scale of this modern form of smuggling, but the breadth, depth, and sophistication of the global Shadow Transshipment Network through which China’s tariff evasion now moves.
The genesis of this scam dates to 2018, when President Trump imposed Section 301 tariffs to counter China’s unfair trade practices, forced technology transfer, intellectual property theft, and state-directed mercantilism.
While the 2018 Section 301 duties generated benefits for the United States and costs for China, Beijing and its exporters adapted to them by, among other things, quickly learning to route around tariffs. Goods that once moved directly from Chinese ports to the U.S. increasingly moved through lower-tariff jurisdictions, where minor processing, relabeling, repackaging, re-invoicing, or paperwork changes could create the appearance of a new national origin. What began as smaller-scale tariff evasion became industrial-scale customs fraud and then a global business model.
Other higher-tariff countries are now adopting the China model to evade the Trump tariffs. While Trump trade policy has been highly effective at incentivizing fairer trade deals and imposing costs on offshoring, illegal transshipment schemes are costing America tens of billions of dollars annually and need to be policed.
The countries that comprise China’s Shadow Transshipment Network include many of America’s largest trading partners. China’s biggest enablers range from Mexico and Canada on U.S. land borders to the European Union, India, Japan, and South Korea.
Given their proximity to China, it is hardly surprising that many Southeast Asian countries play an important role in the network, from Cambodia, Indonesia, and Malaysia to Thailand and Vietnam. More surprising is the sheer number of smaller countries scattered across the globe that also enable the Great Transshipment Scam.
These countries—from Costa Rica and the Dominican Republic in Latin America, to Kenya and Morocco in Africa, to Kazakhstan in Central Asia, to Jordan and the United Arab Emirates in the Middle East—do not move the largest dollar volumes. But China-linked exporters gravitate to them because each offers a specialized comparative advantage: cheap labor, permissive free-trade-zone rules, weak customs enforcement, strategic port access, bonded warehousing, niche assembly capacity, and/or preferential access to the U.S. market relative to China.
Every dollar lost to this Great Transshipment Scam is a dollar stolen from American workers, manufacturers, and taxpayers. When power supplies, control panels, aluminum sheet, valves, plastics, or furniture components are rerouted from China through Mexico, Vietnam, Malaysia, Poland, or the UAE, they destroy or reduce jobs in Milwaukee, Cleveland, Toledo, Hickory, Phoenix, Youngstown, and dozens of other American manufacturing communities.
Without stronger monitoring, detection capabilities, laws, and enforcement, the cumulative macroeconomic effects will extend far beyond lost jobs and degraded communities. They will include billions of dollars in lost Gross Domestic Product output and foregone federal tax revenues.
That is why the strategic response to the Great Transshipment Scam must be a new AI-enabled Detective Border. The U.S. needs a system capable of ingesting and analyzing global trade data with lightning speed, identifying anomalous routing patterns, validating production capacity, and directing enforcement toward the highest-probability offenders.
From the Great Reallocation to the Great Transshipment Scam
The People’s Republic of China entered the World Trade Organization (WTO) in 2001 with strong support from President Bill Clinton and gained extraordinary access to American markets. Instead of honoring the spirit of its WTO accession commitments, Beijing entrenched a non-market system marked by forced technology transfer, disregard for intellectual property rights, subsidies and industrial policies that create systemic overcapacity and overproduction, deeply embedded market-access barriers, lack of regulatory transparency, and refusal to provide reciprocal treatment to U.S. exports.
Beijing’s mercantilism and surging imports from China across the presidencies of George W. Bush and Barack Obama triggered plant closures, collapsing supply chains, shrinking tax bases, declining labor-force participation, and deteriorating public health across the Midwest, South, and Rust Belt. The result of this massive “China Shock” was the loss of millions of American manufacturing jobs and the hollowing out of large segments of the nation’s industrial and defense base.
On July 6, 2018, President Trump imposed historic tariffs under Section 301 of the Trade Act of 1974 to defend American jobs and factories against Chinese predation, force Beijing to reform its mercantilist system, and reverse this China Shock. These 301 tariffs covered nearly 70 percent of Chinese exports to the U.S. (roughly $370 billion in goods) and marked the first serious challenge in decades to China’s predatory trade model.
While the Trump tariffs significantly reduced the direct U.S. trade deficit with China, Beijing and its exporters quickly adapted to try to mitigate this. Many Chinese products subject to higher tariffs that once moved directly from Chinese ports to the U.S. began to move through lower-tariff countries in a phenomenon known as the Great Reallocation.
China began using these third countries for minor processing, relabeling, repackaging, re-invoicing, or routing changes that created the appearance of a new national origin while leaving the underlying Chinese content largely intact. By routing around the tariffs, China and its state-supported manufacturers and trading firms could push goods into jurisdictions with cheap labor, weak customs oversight, permissive free zones, or preferential U.S. trade access.
Over time, these lower-tariff countries, which number more than 40 today, became the launchpads and hubs of a new evasion architecture: products made largely in China, lightly touched abroad, and exported to America under new identities.
This Great Reallocation represents the creation of a new profit system. Tariff penalties redirected China-linked goods away from direct shipment and toward third-country channels where the gap between high U.S. tariffs on China and lower U.S. tariffs on third countries could be captured, divided, and reinvested. That spread became the financial engine of what would quickly emerge as a global Shadow Transshipment Network.
The Transshipment Spoils of Tariff Arbitrage
Tariff arbitrage lies at the heart of modern illegal transshipment, the Great Reallocation, and the Shadow Transshipment Network. When a Chinese product facing a high U.S. tariff can be routed through a country with a lower tariff rate, the difference becomes a profit pool. That spread is what turns transshipment from a marginal customs abuse into a global business model.
For example, ship $1 billion of Chinese goods directly to the United States, and the applicable China-specific tariffs can generate hundreds of millions of dollars in duties, depending on the product mix. Route those same goods through a lower-tariff country and falsely claim a new origin, and much of that duty can disappear. Route them through Mexico or Canada and improperly secure United States-Mexico-Canada Agreement (USMCA) treatment, and the China-specific duty can fall to zero.
Such tariff arbitrage creates the financial engine behind the Great Transshipment Scam. The savings are more than sufficient to finance the capital equipment, logistics infrastructure, light-assembly plants, repackaging operations, and “screwdriver factories” needed to support the scam across Southeast Asia, Mexico, India, and Eastern Europe. These facilities are designed less for true manufacturing than for origin-shifting, tariff evasion, and tariff avoidance.
The spoils of illegal transshipment also enrich the transshipping countries themselves. Local firms capture assembly fees, warehousing revenue, logistics margins, port charges, customs brokerage income, land rents, and export-processing-zone investment. Governments benefit from jobs, tax
receipts, foreign investment, and trade growth. China preserves access to the U.S. market while its partners capture a share of the tariff-evasion premium.
The math of the Great Transshipment Scam is the math of arbitrage, evasion, collaboration, and mutual enrichment. Measured in hundreds of millions of dollars per billion dollars of goods, the gains are large enough to finance the infrastructure of the scam, reward the illegal transshipping partners, transform tariff evasion into a highly profitable global partnership, and serve as the taproot of the Shadow Transshipment Network.
The Great Reallocation
Figure 1 provides a vivid statistical signature of the Great Reallocation: the rerouting of Chinese exports that once moved directly to the U.S. through third countries that now form the global Shadow Transshipment Network. The figure shows selected trade counterparts’ shares of U.S. imports over time.
Figure 1. The Great Reallocation Following President Trump’s 2018 Tariffs
Source: White House Office of Trade and Manufacturing Policy calculations using U.S. Census merchandise trade data obtained through USITC DataWeb for jurisdictions identified from analyses by CEA, Commerce, and Exiger; accessed July 2026.
Using annual U.S. goods import data from the U.S. Census Bureau, the red line in Figure 1 charts China’s share of total U.S. goods imports from China’s entry into the WTO in 2001, through the 2018 inflection point coinciding with President Trump’s imposition of his Section 301 tariffs, and into the present period.
Following China’s WTO accession, China’s share of the U.S. import market rose sharply as Beijing gained dramatically expanded access to American consumers. That share crested when President Trump imposed the Section 301 tariffs and then began a steady decline.
Using the same Census import data, the blue line in Figure 1 charts the combined share of U.S. goods imports supplied by more than 40 countries identified as presenting elevated illegal transshipment risk in analyses by the White House Council of Economic Advisers (CEA); the Department of Commerce; and Exiger, a private-sector firm at the cutting edge of AI-enabled illegal transshipment detection.
What is remarkable about the blue line is its replacement pattern. As China’s direct share of U.S. goods imports falls, the share supplied by those countries rises. The open question this report examines is how much of this apparent reallocation of economic activity reflects illegal transshipment rather than legitimate shifts in production and trade. Even so, the timing, magnitude, and direction of the two trends correspond so closely that the relationship is unlikely to be explained by chance alone.
The Shadow Transshipment Network
China’s Shadow Transshipment Network is a distributed system of finishing hubs, logistics platforms, processing corridors, free-zone operators, and re-export centers that allow Chinese goods to enter the U.S. market under new national identities.
The roughly 40 countries identified as participants in the Great Transshipment Scam can be grouped loosely into three tiers, as shown in Table 1 on the following page.
For purposes of this report, “China-linked goods” means goods that are not necessarily declared as Chinese-origin at entry but carry substantial indicia of Chinese economic origin, control, or content. These indicia may include China-origin inputs or components, Chinese ownership or financing, relationships with Chinese suppliers or manufacturers, China-based production steps, China-origin routing histories, or other trade-flow evidence suggesting that the goods may be part of a China-origin illegal transshipment or origin-shifting scheme.
Tier 1 consists of the Diversified Scale Leaders: countries and trading blocs that account for large absolute volumes of China-linked goods while maintaining diversified industrial bases and major U.S.-bound export platforms. In these jurisdictions, illegal transshipment risk is embedded within broad legitimate trade flows. Tier 1 includes Canada, the European Union, India, Israel, Japan, Mexico, South Korea, and Taiwan.
Tier 2 consists of the Scale Leaders with Significant Economic Integration with China. These countries combine significant illegal transshipment volumes with deeper integration into China-linked supply chains, input sourcing, manufacturing platforms, logistics systems, or regional rerouting channels. Tier 2 includes Brazil, Indonesia, Malaysia, Thailand, Turkey, and Vietnam.
These countries possess sufficient industrial scale, port capacity, supplier infrastructure, manufacturing depth, or logistics capacity to move significant volumes of China-linked goods into U.S.-bound trade flows. Vietnam, Thailand, Malaysia, and Indonesia are closely integrated into China-adjacent manufacturing networks and have become major platforms for electronics, machinery, plastics, footwear, apparel, components, and other industrial goods incorporating China-origin inputs. Brazil and Turkey serve as larger regional production and logistics platforms capable of supporting rerouting or transformation claims across selected product categories.
Tier 3 consists of the Small, Opportunistic Chinese Targets. These are smaller economies with lower absolute illegal transshipment volumes but specific weak-link advantages—including low-cost labor, free zones, port or border access, bonded warehousing, niche assembly capacity, preferential U.S. access, or limited customs enforcement capacity—that make them attractive opportunistic targets for China-linked rerouting.
Tier 3 is the largest tier by number of countries. Cambodia offers low-cost labor and export-processing zones. Laos and Myanmar provide China-adjacent border corridors and lower-capacity enforcement environments in which relatively small rerouting flows can be economically significant. Panama and Costa Rica offer maritime access, free-zone logistics, and re-export platforms. Azerbaijan and Georgia provide rail and dry-port transit, consolidation, and overland-to-maritime connections. Jordan offers preferential trade access and niche assembly capacity.
Table 1. Three Tiers of the Shadow Transshipment Network
China-linked exporters may use these jurisdictions for both limited production activity and logistics-side routing. As local export sectors and transportation networks become increasingly dependent on Chinese inputs, logistics, and capital, Beijing may gain additional commercial and geopolitical leverage while preserving indirect access to the U.S. market.
Illegal transshipment can therefore reinforce commercial dependencies created through the Belt and Road Initiative. Ports, rail corridors, free zones, industrial parks, bonded warehouses, and
logistics platforms may serve both legitimate trade and China-linked rerouting. In smaller jurisdictions, such activity can become a significant feature of the export model. Tier 3 is important not because its members individually account for the largest illegal transshipment volumes, but because their weak-link advantages and dependence on China-linked trade can make them particularly useful nodes in the Shadow Transshipment Network.
Table 1 classifies countries according to the scale of China-linked trade, the depth of their economic integration with China, and the weak-link advantages that make them susceptible to rerouting activity. Table 2 applies a separate but complementary framework by classifying countries according to the principal operational functions they perform within the Shadow Transshipment Network. A country may therefore belong to one tier in Table 1 while performing one or more of the functional roles identified in Table 2. Where Table 1 treats the European Union as a single Tier 1 trading bloc, Table 2 on the following page identifies individual EU member states according to the particular functions they perform within the network.
How the Network Operates
China-linked goods do not move through the Shadow Transshipment Network in a single, uniform way. Some countries and corridors function as production-side nodes, where China-origin inputs receive some physical handling before export to the U.S. This may include light assembly, finishing, testing, labeling, packaging, inspection, or component integration that does not amount to substantial transformation for customs purposes. Others function as logistics-side nodes, where the principal activity is not manufacturing but routing, consolidation, warehousing, documentation changes, re-invoicing, relabeling, or re-export under new paperwork.
Being able to distinguish these roles is critical for enforcement. Production-side nodes require scrutiny of factory capacity, input sourcing, local value-added claims, labor utilization, equipment, and whether the alleged transformation is real or merely cosmetic. Logistics-side nodes require scrutiny of ports, bonded warehouses, free zones, related-party invoices, bills of lading, container routing, dwell time, and whether the paperwork changed faster than the product did.
Drawing on analyses by CEA, Commerce’s Office of Trade and Economic Analysis (OTEA), and Exiger, as well as a review by the White House Office of Trade and Manufacturing Policy of country-level trade routing, production capacity, free-zone infrastructure, and logistics characteristics, Table 2 maps the functional architecture of the Shadow Transshipment Network by identifying the principal operating roles that countries perform within the system.
Cambodia illustrates the production-side microhub model, where China-origin inputs can receive stitching, labeling, packaging, or final inspection before export under Cambodian documentation. Poland and the Czech Republic illustrate the European processing-belt model, where Chinese components can enter sophisticated regional supply chains for final assembly, testing, or repackaging before shipment to the U.S. The United Arab Emirates (UAE) illustrates the maritime-gateway supernode model, with Jebel Ali’s port, free zone, bonded facilities, and re-invoicing platforms allowing China-origin goods to move under new export documentation. Some countries, such as Malaysia, function as both microhubs and maritime gateways, including through facilities such as the Port Klang Free Zone.
Although these clusters use different models, they serve the same larger purpose: allowing China-linked goods to move through third countries in ways that obscure origin, reduce tariff exposure, and preserve access to the U.S. market.
Together, the two frameworks provide a unified enforcement map. The functional clusters identify the principal mechanisms—including production-side transformation claims, logistics-side routing channels, processing zones, maritime gateways, overland corridors, bonded warehouses, and re-invoicing systems. The three-tier hierarchy identifies where enforcement attention should be concentrated based on the scale of China-linked trade, the depth of integration with China-linked supply chains, and the presence of weak-link advantages.
Table 2. Functional Architecture of the Shadow Transshipment Network
The Shadow Transshipment Network is global, but it is not amorphous. It has structure and a clear function. It has production-side nodes, logistics-side nodes, and identifiable routing channels. Understanding that architecture is essential to detecting, disrupting, and ultimately stopping the Great Transshipment Scam while protecting America’s manufacturing and defense industrial base from China’s tariff-evasion machine.
The Costs to America of China-Linked Transshipment
Estimating total annual China-linked illegal transshipment is the first step in calculating the likely range of tariff-revenue losses and the broader costs associated with displaced jobs, reduced GDP, and lower federal tax revenues.
Annual Transshipment Flows and Tariff Loss Estimates
To estimate annual illegal transshipment flows, this report relies on five independent analytical sources: two from government and three from the private sector.
The government contributors include the Department of Commerce’s Office of Trade and Economic Analysis (OTEA) and the White House Council of Economic Advisers (CEA). The private-sector contributors include Goldman Sachs and the AI supply-chain firms Altana and Exiger.
Each uses a distinct methodology and dataset, ranging from goods flow analysis to shipment-level tracing, macro-level econometric modeling, and facility-level supply chain mapping. While no single methodology can fully capture a clandestine activity designed to evade detection, the convergence of these five independent analyses as summarized in Table 3 provides a data-grounded picture of the scale of the illegal transshipment problem, and a reliable range, drawing from high-level aggregate estimates at the upper bounds and highly granular, product-specific analysis alike.
Table 3. Estimates of Annual Illegal Transshipment Flows
At the low end is Goldman Sachs, with a narrow rerouting estimate of approximately $40 billion. Goldman uses a top-down econometric model of product-level trade flows to estimate the
rerouting, or entrepôt-trade, channel. Its estimate is the lowest because it isolates that channel and uses 2023 trade data.
Next is CEA. It estimates potential 2025 transshipment in a range of $34.2 billion to $89.6 billion. For Table 3, this report uses $60 billion as a conservative rounded midpoint of that range. CEA uses methodologies based on Freund (2025) to identify potential transshipment of Section 301-covered Chinese goods at the country-product level. The screen looks for products that faced a 2018 Section 301 duty, where China’s share of U.S. imports falls, China’s share of a third country’s imports rises, and that third country’s share of U.S. imports also rises.
CEA then applies two valuation methods. The upper-bound method values potential illegal transshipment as the lesser of China’s exports to the third country or that third country’s exports to the U.S. of the screened product codes. This approach is intentionally broad because it can count all trade in a qualifying product from a third country as potential illegal transshipment, even if some of that trade existed before the Section 301 tariffs. CEA’s more central method adjusts for pre-tariff trade patterns by estimating only the increase in a third country’s U.S. import share after the tariffs took effect. That approach is more conservative because it focuses on new trade activity most consistent with rerouting rather than the entire existing level of trade.
This range is useful because it brackets the plausible CEA exposure estimate. The lower end reflects the more central, post-tariff increase in third-country market share. The upper end reflects the broader Freund-style exposure measure. Both remain tied to same-product flows, identified by Harmonized System six-digit product (HS6) codes.
Exiger offers another mid-range estimate of $75 billion drawn from a granular, product-level analysis. Exiger directly identified $51.1 billion in potentially illegally transshipped U.S. imports from February 2025 to February 2026, using shipment-flow analysis across 27 countries and priority HS6 categories.
Exiger’s AI is capable of isolating and analyzing product composition, manufacturer facility capabilities, and necessary manufacturing processes. Its model takes into consideration HTS codes, shipments, satellite imagery, parts, equipment, and components to specifically test claims of substantial transformation and identify goods originating in one country before moving through a third-country entity and into the United States. Exiger’s methodology uses these proprietary trade analytics to confidently identify imports with matching HS6 codes, close timing, and value parity; it also uses a 90-day dwell-time threshold as a conservative indicator of pass-through trade rather than genuine manufacturing.
Exiger finds that the $51.1 billion figure is limited to priority countries and product codes where global illegal transshipment is likely substantially higher. Its macro framework further indicates that the true annual magnitude of tariff avoidance and evasion likely trends toward an upper bound of $100 billion. The $75 billion figure used here is therefore a conservative midpoint between Exiger’s directly screened estimate and its systemic upper-bound assessment.
Commerce OTEA employs a trade-transfer approach that measures the extent to which imports of products previously sourced from China have been replaced by imports of the same products from other countries. Using HS6-level Census data, OTEA identified 459 product categories in which
U.S. imports from China declined while imports of the same products from the rest of the world increased.
Across those categories, imports from China fell by roughly $109 billion in 2025, while imports from other countries rose by roughly $156 billion. This report uses the $109 billion decline—the more conservative of the two figures—as the OTEA benchmark in Tables 3 and 4. It is a trade-transfer benchmark rather than a direct estimate of illicit transshipment; some of the replacement reflects legitimate, non-transshipment adjustments to the tariffs.
OTEA also produced a narrower, transaction-level estimate that addresses a key shortcoming of country-level measurement: its failure to account for third countries' new production and consumption of the same goods. Adapting and expanding the methodology developed by Iyoha et al. (2025) and using transaction-level Panjiva customs data, OTEA flagged goods as transshipped only when an exact-match HS8 product was imported from China and exported to the United States from the same local region in the same quarter. On that strict standard, OTEA estimates that approximately $67 billion in U.S.-bound goods were transshipped from China through the top hubs—Mexico, India, and Vietnam—in 2025, producing an estimated $28 billion in lost tariff revenue. The narrower estimate provides a powerful cross-check. Even with exact transaction-level matching limited to only three hubs, OTEA finds $67 billion in transshipment—more than 60 percent of the broader $109 billion trade-transfer benchmark. Its estimated $28 billion tariff loss implies a roughly 42 percent effective duty differential, near the upper end of the range used in Table 4 on a subsequent page.
At the high end, Altana estimates $303 billion in annual U.S.-bound potential illegal transshipment exposure, offering an informative upper bound based on aggregate flows. At first glance, this appears to be an outlier relative to the other estimates. The difference, however, reflects Altana’s high-level, goods flow analysis.
Rather than analyzing product-level data, Altana traces facility-level supply chain relationships to identify routes where goods move from an origin facility to an intermediary facility and then to the final destination. Altana’s estimate may be high because it potentially includes the transit of goods that are subject to substantial transformation or legitimate logistics routing. It captures a wider universe of suspected illegal transshipment and tariff-avoidance pathways. Its value lies in reinforcing this report’s central point: narrower methods may capture only the most visible forms of rerouting, while the full scale of tariff evasion and avoidance is likely much larger.
Taken together, the five estimates make the same point from different angles. Goldman captures the narrow illegal rerouting channel. CEA and Exiger capture broader but still bounded Section 301 illegal transshipment exposure. Commerce OTEA and Altana capture the widest network of suspected transshipment and non-transformation. While the range across estimates is wide, the direction is the same: the Great Transshipment Scam is far larger than conservative shipment-level measures alone would suggest.
Estimated Tariff Revenue Losses to Transshipment
To translate the illegal transshipment-flow estimates in Table 3 into lost tariff revenue, an effective tariff differential must be applied. This differential is the China tariff itself minus the lower duty actually paid when the same goods enter the U.S. from an enabling third country.
Average U.S. tariffs on Chinese exports stand near 50 percent as of publication of this report. In round numbers, Chinese-origin goods face an average tariff burden of roughly one-half of declared value before any comparison is made to lower-tariff third-country routes.
The actual tariff differential necessarily varies by the transshipment route. If China-linked goods can be routed through Mexico or Canada and made to appear USMCA-eligible, the tariff may fall to zero or close to zero. Other routes, including EU-type, Japan-type, Vietnam-type, or South Korea-type channels, may still face meaningful duties but remain well below the China rate.
Based on these observations, this report uses three illustrative tariff differentials: 25 percent, 35 percent, and 45 percent.
These tariff differentials are conservative because they do not fully incorporate other additive and stackable China-specific duties. The most important of these are antidumping and countervailing duties (AD/CVD) levied by the Department of Commerce. AD/CVD duties are not ordinary tariffs. They are additional, product-specific duties imposed when imports are dumped or subsidized and injure U.S. industries.
The Department of Commerce maintains hundreds of active AD/CVD orders, including more than 200 covering China-origin products. These duties are additive, product-specific, and often very large. For example, for aluminum wire and cable from China, Commerce has assigned dumping rates of 58.51 percent to 63.47 percent and subsidy rates of 33.44 percent to 165.63 percent—meaning combined AD/CVD exposure can exceed 90 percent and, in some cases, 200 percent before ordinary duties or China-specific tariff penalties are counted.
Similarly, in quartz surface products from China, dumping margins reach as high as 336.69 percent, with subsidy rates ranging from 45.32 percent to 190.99 percent, creating combined exposure that can run into several hundred percent. Large residential washers from China faced antidumping margins ranging from 38.43 percent to 57.37 percent. Solar cells and modules from China have likewise carried AD/CVD exposure well above 30 percent, with later circumvention findings involving Chinese-origin inputs completed in Cambodia, Malaysia, Thailand, and Vietnam.
These examples do not mean every illegally transshipped product carries AD/CVD exposure. They do, however, show that many AD/CVD-covered product categories overlap with the kinds of goods vulnerable to illegal transshipment: aluminum products, solar components, machinery inputs, industrial parts, household appliances, and other manufactured goods. In these product lines, the true avoided-duty differential can rise far above the 25, 35, and 45 percent assumptions used in this report.
These examples also explain why illegal transshipment is a central concern under the Enforce and Protect Act (EAPA). EAPA gives CBP a dedicated mechanism to investigate whether importers are evading AD/CVD orders by routing covered merchandise through third countries, misdeclaring country of origin, or otherwise entering goods as if they were not subject to the applicable antidumping or countervailing duties.
Another duty evasion tactic that has emerged in EAPA cases, which does not necessarily involve transshipment, but also leads to revenue loss, is undervaluation of imported goods; less revenue is collected because the ad valorem AD/CVD rate is applied to a lower base value.
Undervaluation schemes are a problem in other tariff contexts as well, particularly where related-party sales are involved. For example, when an importer uses the first sale (or earlier sale) for exportation to the United States between the foreign manufacturer and its related middleman as the customs value reported to CBP (versus the last sale between the middleman to the unrelated U.S. buyer), the tariff rate is applied to a lower base value, leading to less revenue collected.
Additionally, current standards for determining country of origin are complex and cumbersome, particularly with imports that are made from components manufactured in multiple countries. These rules are based on customs case law, rather than a precise statute, which can lead to inconsistent application and provide an easy mechanism for tariff evasion. While imports may conform to these standards and meet the legal letter of the law, they fail to meet the spirit of the law.
Congressional action to amend and codify these standards, along with the Detective Border, will combat illegal transshipment and strengthen the President’s trade fairness agenda, supporting reciprocal treatments and protecting U.S. jobs and industries from unfair competition.
With that background, Table 4 applies the assumed tariff differentials of 25 percent, 35 percent, and 45 percent to the annual illegal transshipment-flow estimates and trade-transfer benchmarks in Table 3.
Table 4. Annual Tariff Revenue Loss Estimates from Illegal Transshipment
Note: The rows in this table represent alternative estimates and benchmarks, not additive components. Tariff revenue losses are rounded to the nearest billion dollars.
As Table 4 shows, even the lowest illegal transshipment estimate produces substantial tariff revenue losses. At Goldman Sachs’ $40 billion midpoint estimate, annual tariff losses range from roughly $10 billion at a 25-percent differential to $18 billion at a 45-percent differential.
At CEA’s $60 billion transshipment flow estimate, annual tariff loss estimates range from roughly
$15 billion at a 25-percent differential to $27 billion at a 45-percent differential.
At Exiger’s $75 billion estimate, the corresponding range is roughly $19 billion to $34 billion.
Commerce OTEA’s broader $109 billion trade-transfer benchmark produces a still larger implied range: roughly $27 billion to $49 billion.
Altana’s broader exposure estimate produces the largest implied loss. At $303 billion in suspected annual U.S.-bound transshipment exposure, the implied tariff loss ranges from roughly $76 billion to $136 billion. This figure should be treated as a high-exposure case rather than a direct equivalent to the narrower estimates.
Still, the conclusion is clear that under every scenario presented, the Great Transshipment Scam is draining the U.S. Treasury of billions in tariff revenue every year.
Tariff Losses in Context
Table 5 puts the tariff loss estimates in Table 4 into concrete budgetary terms. It compares four illustrative annual revenue-loss levels: a low-end $10 billion loss, a central $25 billion loss, a high-core $40 billion loss, and a broad-exposure loss of $100 billion or more.
Table 5. Putting Annual Tariff Losses in Budget Context
Even the low-end loss is noteworthy in terms of comparable federal budget scale. A $10 billion annual tariff leak is roughly two-and-a-half years of the Federal Aviation Administration’s facilities and equipment modernization at the FY2026 request level of $4 billion per year. It is also nearly half of the U.S. Department of Agriculture’s FY2026 discretionary request of $22.1 billion. At this level, transshipment losses are large enough to fund major port inspection upgrades, border enforcement systems, air traffic control modernization, or industrial base investments.
At the central case of roughly $25 billion per year, illegal transshipment losses become agency-scale. That level of annual leakage exceeds U.S. Customs and Border Protection’s FY2026 budget of $23 billion and the USDA FY2026 discretionary budget request. It is also close to the Space Force’s FY2026 budget request of roughly $26.4 billion. In practical terms, tariff revenue lost to illegal transshipment could otherwise fund a full year of CBP, a full year of USDA discretionary operations, or nearly the entire annual budget of America’s newest military service.
At the high-core level of roughly $40 billion per year, the losses reach the scale of major national infrastructure and defense investments. That amount exceeds the Space Force’s FY2025 enacted budget of roughly $28.7 billion. It is more than half of the Federal Highway Administration’s FY2026 total budgetary resources of $72.6 billion. It is also approaching the scale of the Marine Corps’ FY2026 request of roughly $57.2 billion. At this level, illegal transshipment is a federal
revenue drain large enough to reshape military modernization, highway construction, port security, and industrial renewal priorities.
Under the broad exposure case, annual losses can exceed $100 billion. At that level, the revenue loss is larger than annual Federal Highway Administration resources, roughly two-thirds of the Department of Transportation’s full FY2026 budget of $147.1 billion, about half of the Army’s FY2026 request of $197.4 billion, and nearing the Department of Veterans Affairs’ FY2026 discretionary request of $134.6 billion. That is no longer simply “lost tariff revenue.” It is money on the scale of major departments, military services, national transportation systems, veterans’ programs, and industrial base renewal.
The defense comparisons are especially stark. The Department of the Navy FY2026 request is
$292.2 billion, the Air Force request is roughly $234.4 billion, the Army request is $197.4 billion, the Marine Corps request is about $57.2 billion, and the Space Force request is about $26.4 billion. A $25 billion annual tariff loss is nearly a Space Force budget. A $40 billion loss is most of a Marine Corps budget. A $100 billion loss is service-scale money—large enough to fund a substantial fraction of the Army, Navy, or Air Force.
The conclusion is straightforward. Whether the annual loss is $10 billion, $25 billion, $40 billion, or more than $100 billion, the dollars are large enough to matter. The Great Transshipment Scam is not merely shifting trade flows. It is draining the U.S. Treasury of funds that could otherwise strengthen the border, rebuild roads and ports, modernize air-traffic control, support farmers and veterans, recapitalize military services, and restore America’s manufacturing and defense industrial base.
Broader Economic Losses: Jobs, GDP, and Federal Tax Revenues
Tariff revenue is the most obvious loss from illegal transshipment. However, when China-linked goods enter the U.S. through third countries, they do more than evade duties. They widen the effective trade deficit, displace domestic production, reduce GDP growth, and lower associated federal tax receipts. Table 6 on the following page applies three standard rules of thumb to translate annual illegal transshipment flows into these broader economic losses.
First, this report applies a conservative trade-deficit employment rule of thumb based on Robert
Scott's analyses for the Economic Policy Institute (EPI), which estimate the number of U.S. jobs displaced by increases in the trade deficit. In Scott's study of NAFTA, the increase in the U.S. goods trade deficit with Mexico and Canada between 1993 and 2013 was estimated to have displaced approximately 851,700 U.S. jobs. This implies roughly 5,300 jobs displaced for every
$1 billion increase in the trade deficit.
In a separate EPI study of U.S.-China trade, Scott estimated 3.7 million jobs displaced as the bilateral trade deficit increased by approximately $336.5 billion, implying roughly 11,000 jobs displaced for every $1 billion increase. Rather than use the midpoint of the two implied relationships, this report adopts a deliberately conservative assumption of 6,000 U.S. jobs displaced for every $1 billion increase in the trade deficit associated with illegal transshipment.
Second, for purposes of illustrating a range of potential effects, this report applies an assumed GDP multiplier of 1.5 to 2.0. This scenario assumption is not a direct estimate produced by BEA. In the national income accounts, net exports are a direct component of GDP, meaning a larger
trade deficit reduces measured GDP dollar-for-dollar when imports replace domestic production. The U.S. Bureau of Economic Analysis’s RIMS II input-output framework then provides the standard method for estimating the broader effects of changes in final demand on output, value added, earnings, and employment. Manufacturing-multiplier research likewise finds that manufacturing demand supports substantial upstream and downstream value chains.
On that basis, this report assumes that every $1 billion increase in the trade deficit reduces annual GDP by roughly $1.5 billion to $2.0 billion once direct production losses, supply-chain effects, wage effects, and induced-consumption effects are included. (See U.S. Bureau of Economic Analysis, “RIMS II Multipliers,” explaining that RIMS II estimates the impact of changes in final demand on output, employment, and labor earnings; U.S. Bureau of Economic Analysis’s “BEA Updates Regional Economic Tool,” explaining that RIMS II can estimate impacts on gross output, value added, earnings, and employment; and Manufacturers Alliance’s “How Important Is U.S. Manufacturing Today?,” finding that the domestic manufacturing value-added multiplier is 3.6 and that manufacturing value chains account for roughly one-third of U.S. GDP and employment.)
Third, this report translates lost GDP into lost federal revenue using the historical revenue-to-GDP relationship. The Congressional Budget Office reports that federal revenues average roughly 17.3 percent of GDP over 50 years, while data from the Office of Management and Budget and the Federal Reserve place federal receipts at about 17.0 percent of GDP in 2025. This report therefore uses 17 percent as a rounded rule of thumb: every $100 billion in lost GDP implies roughly $17 billion in foregone federal receipts.
As Table 6 shows, even the narrow case implies substantial damage: roughly 240,000 estimated jobs displaced directly and indirectly; $60 billion to $80 billion in annual GDP loss; and $10 billion to $14 billion in lost federal revenue.
Under the central case, the losses rise to roughly 450,000 jobs displaced, along with $113 billion to $150 billion in GDP loss and $19 billion to $26 billion in federal revenue loss.
Under the broad exposure case, the losses reflect more than 1.8 million jobs displaced, more than
$450 billion in annual GDP loss, and $77 billion to $103 billion in lost federal revenue.
Table 6. Broader Annual Economic Losses from Illegal Transshipment
Together, these estimates show why illegal transshipment is not merely a customs problem. It drains tariff revenues at the border, widens the effective trade deficit, displaces factory and supplier jobs, reduces GDP growth, and erodes the tax base needed to rebuild America’s manufacturing and defense industrial base. These losses accumulate in the industrial geography of the U.S.—in factories, machine shops, logistics networks, and Main Street businesses across America’s manufacturing communities.
Ugly Sister Cities in a Zero-Sum Game
Moving now from the 30,000-foot macroeconomic view of the Great Transshipment Scam to a factory-floor perspective, a set of “ugly sister city” comparisons show how Chinese transshipment equates to a zero-sum transfer of production from American soil to foreign jurisdictions.
The foreign–U.S. city pairings in Table 7 on the following page reveal the micro-geography of trade diversion: as activity rises in foreign staging points handling China-linked goods, the corresponding American manufacturing corridors come under direct pressure.
These are not sister cities in the cultural sense. They are the “ugly sisters” of modern zero-sum global trade, paired not by civic partnership, but by the logic of American jobs lost to unfair trade.
These ugly sisters are illustrative rather than exhaustive. They cover only a small sample of the countries, product lines, and American industrial corridors affected by the Great Transshipment Scam. Yet each pairing displays the same zero-sum arithmetic. When China-linked goods enter the U.S. through a transshipment hub under a new national identity, American producers in the corresponding product line face lost orders, lower utilization, and reduced employment.
The pairings in Table 7 were developed by matching high-volume illegal transshipment-risk HTS product lines to the corresponding U.S. industrial base. The trade side begins with HTS product categories showing significant China-linked rerouting risk in the CEA, Commerce OTEA, Exiger, and Goldman Sachs analyses. Those product lines are then mapped to corresponding NAICS manufacturing industries using USITC DataWeb and Census trade concordance tools, which translate HTS import categories into domestic industry classifications.
The domestic geography is identified from Census County Business Patterns and BLS Quarterly Census of Employment and Wages data, which report establishments, employment, and payroll by NAICS industry at the county, metro, and state levels. The resulting pairings are therefore not cultural “sister city” relationships. They are product-to-industry matches: foreign corridors handling high-risk China-linked goods are paired with American manufacturing corridors where firms and workers produce the same or closely related products.
Using the previously referenced benchmark of 6,000 U.S. jobs displaced, direct and indirect, per
$1 billion in diverted imports, each pairing illustrates a potential channel through which rerouted imports may place corresponding American manufacturing capacity under pressure.
Table 7 illustrates potential illegal transshipment exposure across a range of country-product corridors. Mexico’s Guanajuato–Querétaro corridor provides a potential staging point for electric motors, generators, transformers, and static converters in HS 8501-8504, placing motor and component production in Detroit, Grand Rapids, and Indianapolis under pressure. South Korea’s Gyeonggi semiconductor belt can serve as a conduit for integrated circuits in HS 854239, placing semiconductor production in Phoenix, Austin, Portland, and San Jose under pressure.
In Southeast and South Asia, Vietnam’s Ho Chi Minh City corridor handles electrical switching and circuit-protection apparatus in HS 8536, putting electrical-equipment work in Chicago, Milwaukee, and Rockford under pressure. India’s Pune–Gujarat–Chennai production belt absorbs pumps and compressors in HS 8413-8414, affecting industrial supply chains in Cincinnati, Dayton, and Columbus. Malaysia’s Penang–Kulim cluster moves plastic articles in HS 392690, exposing plastics production in Akron, Canton, and Upstate South Carolina.
Indonesia and Thailand illustrate the same pattern in specialized components. Indonesia’s Bekasi–Batam corridor moves plastic boxes, cases, crates, and packing articles in HS 392310, pressuring plastics and packaging suppliers in Houston, Lake Charles, Beaumont, and Tulsa. Thailand’s Ayutthaya–Samut Prakan corridor handles thermostats in HS 903210, putting pressure on work tied to the Minneapolis–St. Paul controls and instrument base.
Table 7. Representative Foreign–U.S. “Ugly Sister City” Pairs Across Major HS Categories
Source: CEA; Commerce OTEA; Exiger shipment-level data; Goldman Sachs; White House Office of Trade and Manufacturing Policy estimates (2026).
The Caribbean and Central American gateways show how smaller illegal transshipment platforms can still hit specific U.S. production corridors. The Dominican Republic’s Caucedo–Haina corridor moves insulated conductors and cable assemblies with connectors in HS 854442, pressuring the Portland–Seattle–Spokane cable and connector corridor. Costa Rica’s Limón–Moín corridor handles electric motor and generator parts in HS 850300, competing with production and logistics networks in Dallas–Fort Worth and Oklahoma City.
These examples show how illegal transshipment converts foreign staging points into direct pressure on American manufacturing communities. Electric motors, static converters, integrated circuits, circuit-protection equipment, pumps, compressors, plastic articles, thermostats, cable assemblies, and motor parts all map onto specific U.S. industrial corridors.
As illustrated by these pairings, when China-origin goods enter the U.S. market under new identities, American factories, machine shops, metal fabricators, electronics producers, plastics firms, and logistics workers lose orders that should have stayed at home.
The message of these ugly-sister city snapshots is that tariff evasion is a zero-sum game. America loses when these hubs win. And the longer the system operates unchecked, the harder it becomes to restore lost industrial capacity. Unless addressed with meaningful enforcement, the world’s illegal transshipment hubs will continue to siphon off American manufacturing one product line at a time.
The AI Detective Border: A Global Warning
Analog systems of paper manifests, manual inspections, and audits conducted long after shipments enter domestic commerce worked tolerably well when trade volumes were modest and supply chains were largely domestic. However, as trade volumes surged, supply chains became more complicated, and tariffs increased, the incentives to cheat rose exponentially as well.
These legacy systems failed completely in an era of containerized global commerce, complex multinational production, and digital logistics networks capable of relabeling billions of dollars in goods at the stroke of a key.
Recognizing this, CBP worked diligently to expand its enforcement architecture. Following the events of September 11, 2001, CBP’s predecessor, the U.S. Customs Service, established the National Targeting Center: a centralized hub for the screening of cargo and travelers, identification of national security threats, and interdiction of illicit trade before it reaches the U.S. border.
CBP also built systems to better enable enforcement personnel to leverage the enormous amounts of trade and travel data available, incorporating machine learning and large language models into existing targeting and risk analysis platforms to develop new and more advanced tools for the identification and interdiction of illegally transshipped goods. AI is already being leveraged in CBP’s targeting systems, for non-intrusive inspection of cargo containers, for anomaly detection, and as part of advanced analytical models that enable the faster identification of potentially dangerous shipments before they arrive in the United States.
But bad actors have also become more sophisticated. A network-based approach to targeting and enforcement is desperately needed to counter the threat of the Shadow Transshipment Network’s
coordinated tariff evasion schemes. Without the right enforcement tools, tariff circumvention schemes will operate with near impunity, earning profits that dwarf any eventual fines.
Continued investment in and expansion of CBP’s AI/machine learning capabilities is critical for it to remain agile and effectively combat illegal transshipment in a world where criminals can quickly switch tactics, dissolve shell companies, and disappear.
Today, with dramatic advances in artificial intelligence and a clear national mandate to strengthen and seal every aspect of our borders, foreign actors participating in the Shadow Transshipment Network and Great Transshipment Scam are being put on notice. Under Trump leadership, CBP’s emerging AI architecture is fusing anomaly detection, link analysis, capacity validation, and mirrored-flow verification into a single predictive platform—the foundation of what can now be called America’s Detective Border.
At its core, this Detective Border continuously ingests and analyzes global trade data. Algorithms compare declared origins, routing histories, and component content against expected patterns, revealing inconsistencies that no human could catch at scale. The Detective Border amplifies the effectiveness of CBP’s existing risk-based targeting models, directing CBP officers to the highest-probability offenders and multiplying the productivity and precision of every enforcement action.
The Detective Border should help distinguish legitimate foreign direct investment and nearshoring from illicit transshipment. AI-enabled verification should also produce more precise estimates of the value of illicit transshipment.
Artificial intelligence also links the field to the factory. Computer-vision scanners and machine-learning models embedded in port infrastructure now analyze container markings, packaging patterns, and X-ray imaging to detect mismatches between declared and actual cargo. This new, high-tech enforcement layer is designed to ensure that every product’s digital identity matches its physical reality. Goods that once slipped through gaps in paperwork will now face a system designed to identify, track, and intercept them in real time.
The message to the world is simple. The age of untraceable illegal transshipment is over. What once seemed like quiet paperwork maneuvers—relabeling, repackaging, re-invoicing—has become a matter of economic sovereignty and national will.
The United States under President Trump will simply not allow its manufacturing and defense industrial foundation to be hollowed out by trade fraud masquerading as commerce. The same advanced data systems that map global supply chains for industry will now illuminate them for enforcement.
The objective is clear: every bill of lading, shipping manifest, and certificate of origin should pass through an AI-driven net that never sleeps, never tires, and never forgets. Countries that relabel or reroute tariffed goods to evade U.S. law should face immediate interdiction, penalty tariffs, sanctions, and potential loss of market access. Tariff evasion can no longer remain a low-risk, high-profit strategy. It must become a direct path to exclusion.
President Trump’s June 3, 2026 Executive Order on Strengthening Customs Enforcement will bolster this effort by attacking the legal and operational vulnerabilities that transshippers exploit. The order directs the Department of Homeland Security and CBP to tighten importer-of-record requirements, increase bonding and domestic-asset requirements, require additional ownership and business-affiliation disclosures, impose good-standing requirements, strengthen penalties, and improve customs transparency. These reforms go directly to the weak points of the Shadow
Transshipment Network: shell importers, foreign importers beyond easy U.S. enforcement reach, under-bonded entries, opaque ownership structures, repeat violators, and paperwork schemes designed to obscure origin and evade duties.
The Customs EO therefore supplies the institutional backbone for the AI Detective Border. Artificial intelligence can identify anomalous routing patterns, suspicious bills of lading, false-origin claims, value mismatches, and capacity inconsistencies. The Customs EO strengthens CBP’s ability to act on those signals by making importers more accountable, improving the data available to enforcement officers, increasing the cost of noncompliance, and reducing the ability of foreign actors to treat U.S. customs penalties as a manageable cost of doing business. In practical terms, the Detective Border finds the signal; the Customs EO helps give CBP the enforcement leverage to turn that signal into interdiction, penalties, duty collection, and exclusion.
This is America’s message to the Shadow Transshipment Network—our warning to the world: stop evading and avoiding the Trump tariffs through illegal transshipment. Those who continue will be caught. Those who cooperate will be treated as partners in restoring a fair and honest trading system.
CBP’s emerging Detective Border marks the beginning of the end of the Shadow Transshipment Network and the Great Transshipment Scam, and the beginning of a new era of tariff integrity, industrial renewal, and American enforcement that works.
Conclusion
The AI Detective Border is one of several initiatives the second Trump Administration is undertaking to reduce illegal transshipment. Whether these measures will be sufficient to curb the broader budgetary and economic costs imposed by the Great Transshipment Scam remains to be seen.
Answering that question rigorously will require analysis of trade and customs data from the countries and jurisdictions implicated in transshipment. As those data become available, the Trump Administration will evaluate whether, and to what extent, its anti-transshipment measures are working. That continuing assessment reflects the Administration’s commitment to ensuring that the American people receive the full benefits of President Trump’s trade and tariff program.
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