$7 Trillion Bypassing the Dollar: How China Built an Alternative to SWIFT

cryptonews.ruPublished on 2026-08-08Last updated on 2026-08-08

Abstract

The article discusses China's development of the Cross-border Interbank Payment System (CIPS) as a yuan-based alternative to SWIFT, driven by global de-dollarization efforts following the use of the US dollar as a political tool. Launched in 2015, CIPS now processes cross-border payments equivalent to roughly $7 trillion monthly. Its growth accelerated after key geopolitical events, most notably the 2022 freezing of Russian reserves, prompting countries to diversify away from dollar-dependent systems. While CIPS has expanded to over 1,800 participant institutions, the yuan's share in global payments remains modest at 3.1%, far behind the dollar. The article notes CIPS still relies on SWIFT for about 80% of its message routing, positioning it more as a supplement than a full replacement. A key unresolved challenge is whether CIPS can overcome the fundamental barrier posed by China's capital controls and the yuan's limited convertibility.

Dedollarization is no longer a theoretical topic for economists—it has become a national security issue for a number of countries. The turning point was the repeated use of the dollar as a tool of pressure: disconnecting Iran from SWIFT, sanctions against Russia, and then the freezing of Russian currency reserves. Each such step pushed countries to find ways to conduct settlements bypassing the American financial infrastructure—and China was ready to offer an alternative.

We are talking about the Cross-border Interbank Payment System (CIPS)—a cross-border interbank payment system that China is developing as an analogue to SWIFT for settlements in yuan. Launched in 2015 with nearly zero volume, the system now processes cross-border payments equivalent to approximately $7 trillion per month.

How the Freezing of Russia's Reserves Changed the Yuan's Trajectory

The growth dynamics of CIPS have not been uniform. On the graph of cross-border transaction volumes, acceleration points are clearly visible, and each coincides with another case of the "militarized" use of the dollar:

  • 2012 — Iran's disconnection from SWIFT

  • 2014 — Sanctions against Russia

  • 2017–2018 — Launch of the yuan-denominated oil contract and the first Trump-China trade war

  • 2022 — Freezing of Russia's currency reserves

  • 2023 — Biden administration restrictions on exporting advanced chips to China

  • 2025 — A new round of the Trump-China trade war and the US strike on Iran

The most dramatic spike occurred in 2022: after Western countries blocked Russia's access to its reserves, the volume of yuan settlements grew multiple times. The logic is simple—if a currency can be frozen by a political decision, countries have an incentive to diversify reserves and switch trade to other currencies.

From Zero to $7 Trillion Per Month in a Decade

Official statistics from the People's Bank of China (PBOC) confirm the scale of growth. In 2025, CIPS processed 8.4419 million transactions with a total value equivalent to $25.55 trillion for the year. Preliminary data for the first half of 2026 indicate the annual pace could be even higher—suggested by estimates based on monthly PBOC and CIPS operator statistics. The average daily transaction value grew from about $96 billion in 2025 to around $118 billion by June 2026.

The network itself is expanding: the system is currently used by 210 direct and 1,619 indirect participants—banks and financial organizations worldwide that in 2015 simply did not have the ability to conduct settlements in yuan directly, bypassing the dollar.

The Yuan is Still Far from Reserve Currency Status

The growth of CIPS should not be confused with displacing the dollar from the global financial system. According to SWIFT tracker data, the yuan's share in global payments in June 2026 was only 3.10%—fifth place among currencies, far behind the dollar. In trade finance, the figure is slightly higher at 8.00%.

The total volume of cross-border yuan settlements within China at the end of 2025 reached approximately $9.9 trillion equivalent, which is 10.2% more year-on-year. In other words, the yuan is becoming a significant tool for settlements between specific trade partners and for bypassing sanctions risks, but does not yet aspire to the role of a universal reserve currency.

Nevertheless, the trajectory itself is indicative: each new use of the dollar as a tool of pressure—be it disconnection from SWIFT, freezing of reserves, or trade restrictions—has historically coincided with a new wave of growth for CIPS.

AI Opinion

From the perspective of machine data analysis, the growth of CIPS looks less clear-cut when adding a technical detail not covered in the article: the platform still largely depends on SWIFT at the level of interbank message exchange. According to estimates from industry sources, about 80% of CIPS transactions pass through SWIFT channels for message routing, making the Chinese system more of a complement to the global infrastructure than a full-fledged alternative to it.

Historical context adds another layer: China's reluctance to fully liberalize the yuan exchange rate and remove capital movement restrictions long constrained the currency's internationalization more than the lack of an alternative payment system. The question is whether the CIPS infrastructure can accelerate this process by itself, or whether the yuan's convertibility remains a more fundamental barrier than any technical limitations.

Related Questions

QWhat is CIPS and what is its primary purpose according to the article?

ACIPS, or the Cross-border Interbank Payment System, is a Chinese-developed international payment system for clearing and settling cross-border yuan (renminbi) payments. Its primary purpose is to serve as an alternative to SWIFT, allowing countries and financial institutions to conduct trade and financial transactions in yuan, bypassing the US dollar and the traditional US-led financial infrastructure.

QWhat event in 2022 is cited as causing the sharpest acceleration in CIPS transaction volumes?

AThe sharpest acceleration in CIPS transaction volumes occurred in 2022, following the Western freeze of Russia's foreign currency reserves. This event drove a multiple-fold increase in yuan-denominated settlements as countries sought to diversify reserves and move trade away from currencies that could be politically weaponized.

QWhat was the approximate total value of transactions processed by CIPS in 2025, and what was the year-on-year growth in China's cross-border yuan settlements for that year?

AIn 2025, CIPS processed transactions with a total value equivalent to $25.55 trillion. Additionally, the overall volume of cross-border yuan settlements within China reached approximately $9.9 trillion for the year, representing a year-on-year growth of 10.2%.

QAccording to the 'AI Opinion' section, what key technical dependency limits CIPS from being a full-fledged alternative to SWIFT?

AThe 'AI Opinion' section notes that CIPS still largely depends on SWIFT for message routing between banks. Approximately 80% of CIPS transactions reportedly pass through SWIFT channels for messaging, making the Chinese system more of a complement to the global infrastructure rather than a complete standalone alternative.

QDespite the rapid growth of CIPS, what is the yuan's current share in global payments according to SWIFT tracker data from June 2026, and what does this indicate about its global role?

AAccording to SWIFT tracker data from June 2026, the yuan's share in global payments was only 3.10%, placing it fifth among global currencies and far behind the US dollar. This indicates that while the yuan is becoming a significant tool for specific trade partners and sanction avoidance, it is not yet close to challenging the dollar's status as a universal reserve currency.

Related Reads

US Nonfarm Payrolls Unexpectedly Strong, Probability of September Rate Hike Rises to About 60%, Market Eyes Next Week's CPI

U.S. August non-farm payrolls came in significantly stronger than expected, adding 162k jobs—nearly triple economists' forecasts. This robust employment data signals ongoing economic resilience and has sharply increased market expectations for a Federal Reserve rate hike at the September meeting, with fed funds futures now pricing in roughly a 60% probability of an increase. The data prompted immediate market adjustments: U.S. equities closed lower on Friday, and Treasury yields climbed, with the policy-sensitive 2-year yield rising to its highest level since January 2025. However, broader market impact remained contained for now, as major stock indexes still posted weekly gains and credit spreads stayed relatively low. Analysts note that despite higher rates, financial conditions remain accommodative, corporate earnings are strong, and the AI investment boom—evident in job gains in sectors like construction and manufacturing—is providing economic support. While the non-farm payrolls report tilts the policy debate toward a more hawkish stance, it does not conclusively determine the Fed's next move. Market focus is now firmly shifting to the upcoming Consumer Price Index (CPI) report. Analysts warn that if inflation data remains elevated and further pushes up rate expectations, it could force investors to more aggressively reduce risk exposure, potentially increasing market volatility. The CPI release, alongside political considerations around the midterm elections, is seen as the next critical variable for the Fed's decision.

marsbit19m ago

US Nonfarm Payrolls Unexpectedly Strong, Probability of September Rate Hike Rises to About 60%, Market Eyes Next Week's CPI

marsbit19m ago

The Era of Large Model Distillation is Over: Fable 5.1 Rewrites API, Cutting Off the Path of Distillation for Good

The era of large model distillation is ending. On September 2nd, Anthropic delivered a decisive blow by updating its API rules with Claude Fable 5.1, effectively cutting off the path for shell models and distillers. Previously, companies bypassed immense compute costs and lengthy training times by using API calls to extract the reasoning process of top-tier models like Claude, then using this data to train their own smaller "distilled" models. A key vulnerability was the "thinking blocks"—the model's internal Chain-of-Thought reasoning steps returned via API. Distillers exploited this by modifying the surrounding context (like system prompts or earlier messages) in multi-turn conversations, tricking Claude into revealing its hidden underlying logic. Fable 5.1 introduces a stringent "context consistency verification" mechanism. The API now strictly validates that the "thinking blocks" sent back by the client match the original system prompts, tools, and message history that produced them. Any modification causes the API to return an error. A "non-strict mode" is offered for legitimate developers who need to modify context (e.g., for compression), but it silently deletes all thinking blocks, forcing the model to answer without its prior reasoning. This crackdown was deemed necessary due to industrial-scale abuse. "Distillation hackers" used thousands of fake accounts and automated scripts to exploit the API, extracting high-intelligence reasoning capabilities while completely bypassing the costly safety and alignment training (like RLHF) built into models like Claude. This created a critical risk: "capability-safety decoupling," where distilled models gain advanced abilities but lack the ethical guardrails, potentially making them dangerous. The new rules are being rolled out in phases, initially targeting new API accounts created after August 31, 2026, UTC. Existing API accounts and consumer users (e.g., Claude.ai) are unaffected for now, giving legitimate developers time to adapt. Anthropic states the "thinking retention" mechanism will eventually apply to all accounts. An unexpected benefit for compliant developers is potential cost reduction and speed improvements. Enforcing context consistency allows for highly efficient prompt caching on API servers, slashing latency and compute overhead. This move marks a watershed for the AI industry, challenging the narrative of small models outperforming large ones through distillation and forcing a reckoning on innovation versus imitation.

marsbit46m ago

The Era of Large Model Distillation is Over: Fable 5.1 Rewrites API, Cutting Off the Path of Distillation for Good

marsbit46m ago

South Korea Announces Securities Tokenization Timeline: First Batch of Tokenized Assets to Include Bonds, Funds, and Unlisted Stocks

South Korea's Financial Services Commission (FSC) has unveiled a three-phase roadmap for tokenizing securities, positioning itself as a potential first-mover with dedicated legislation. Following the formal enactment of amended laws in February 2027, Phase 1 will begin with tokenized private market assets, including bonds, institutional money market funds, and unlisted stocks (via trust beneficiary certificates). Existing licensed securities firms can operate without new permits, with specific rules for non-financial platform operators and investor limits. Phase 2 will expand to publicly issued securities, contingent on the stability of initial systems and market readiness. The final Phase 3 aims to enable on-chain settlement using stablecoins, pending separate stablecoin legislation. The announcement contrasts sharply with rapid, decentralized approaches like Robinhood's recent tokenization of stocks, which sparked controversy. South Korea's path prioritizes legal clarity and infrastructure, starting with controlled, institutional markets before broadening access. While this methodical approach may sacrifice speed, it seeks to establish a clear regulatory foundation. The global race for tokenization is highlighting divergent strategies between regulated, incremental models and faster, more open but less certain alternatives.

marsbit50m ago

South Korea Announces Securities Tokenization Timeline: First Batch of Tokenized Assets to Include Bonds, Funds, and Unlisted Stocks

marsbit50m ago

Just Now, Claude Proves Fermat's Last Theorem for the First Time, Led by Tsinghua Yao Class Prodigy

In a groundbreaking development, Claude has autonomously generated the first machine-verified proof of Fermat's Last Theorem in just 11 days. The project was led by Tianyi Peng, a researcher from Anthropic with a background from Tsinghua University's prestigious Yao Class. This achievement required Claude to write 13 million lines of Lean code, proving over 29,500 intermediate theorems and consuming 60 billion tokens—a volume exceeding the largest existing mathematical theorem library by fivefold. The process involved formalizing the 350-year-old theorem, which states that no three positive integers a, b, c satisfy a^n + b^n = c^n for any integer n > 2. While Andrew Wiles provided a human proof in 1995, its complexity made verification a years-long task for experts. Claude's formal proof builds from foundational axioms, autonomously constructing the entire logical chain and verifying it through the Lean compiler. Key to the success was the development of the "Prove2Me" platform, which managed dozens of Claude agents by organizing tasks into a theorem DAG (directed acyclic graph), separating statements from proofs, and maintaining natural language indexes. This addressed early collaboration inefficiencies and "hallucination" issues. The result is the largest Lean proof ever created. The accomplishment has stirred significant discussion in the mathematical community, highlighting AI's potential to automate the formalization and verification of complex proofs. While not replacing mathematicians, such technology could fundamentally change mathematical practice by providing absolute verification, checking human-generated mathematics, and enabling broader access to formal verification tools.

marsbit50m ago

Just Now, Claude Proves Fermat's Last Theorem for the First Time, Led by Tsinghua Yao Class Prodigy

marsbit50m ago

Raoul Pal: Why Has the Traditional Investment Portfolio Become Obsolete?

Raoul Pal argues that traditional investment portfolios (bonds, gold, real estate, index funds) are no longer effective for building real wealth. He posits that due to persistent currency devaluation from money printing (global liquidity expanding ~8% annually plus regular inflation), an investor needs an 11% annual return just to preserve purchasing power. He evaluates traditional assets: bonds fail as interest doesn't cover currency devaluation; real estate's historic wealth-creation window from falling rates is over; gold preserves purchasing power but doesn't create new wealth; and the S&P 500 barely meets the 11% threshold, relying on a historic bull market. The only assets consistently exceeding this benchmark, based on decade-long data, are technology stocks (NASDAQ 100: ~20% annualized) and crypto assets (Bitcoin: 58-70% annualized). Their outperformance stems from user adoption S-curves (Metcalfe's Law), not speculation. Pal explains that post-2008, traditional diversification lost its protective power because bonds, gold, real estate, and stocks are all now primarily driven by the same macro factor: liquidity. Thus, a diversified portfolio of underperforming assets offers false security. For crypto, he favors underlying protocols/L1 blockchains over applications, as they capture value from the entire ecosystem. A key, underappreciated future driver is AI agents, which will require programmable money and 24/7 settlement, a natural fit for blockchain. Key investment principles include: avoid leverage (it removes the ability to weather severe drawdowns), allocate a meaningful portion (not all) of capital to high-growth assets, and practice patience—"doing nothing" is a valid long-term strategy. The core opportunity cost is freedom. Returns below 11% annually mean your labor buys less freedom over time. The goal is to use this framework to audit your holdings, moving capital from assets that erode purchasing power to those with genuine compounding potential.

marsbit2h ago

Raoul Pal: Why Has the Traditional Investment Portfolio Become Obsolete?

marsbit2h ago

Trading

Spot
活动图片