The number of unique wallets sending peer-to-peer stablecoin transfers in China increased 43-fold between the first quarter of 2024 and the second quarter of 2026, according to a new regional analysis from Chainalysis.
The blockchain analytics company estimates that China-linked self-custodied stablecoin holdings generated $104.1 billion across 18.1 million transfers in the 12 months ended June 30, 2026. Chainalysis measured average holdings of $3.1 billion and calculated annual turnover of 33.2 times, more than three times its estimated global average of 9.3.
The figures indicate rapid movement through wallets that Chainalysis associates with China, but they are not a direct count of people, merchant purchases or completed remittances. A person or organization can control several wallets, and ledger data alone cannot establish the commercial purpose of every transfer.
P2P activity dominates the China estimate
Chainalysis estimates China’s total crypto economy at no less than $176 billion for its 2026 reporting period, which covers July 1, 2025 through June 30, 2026. It says domestic P2P activity represented 59.1% of that total, with the share rising to 3.5 times its level in the previous reporting period.
That composition differs from markets where centralized exchanges provide a larger share of observable activity. Crypto exchange services remain restricted in mainland China, so Chainalysis says it derives its China estimate primarily from transfers between personal wallets.
Chainalysis interprets the high turnover as consistent with stablecoins being used as working capital rather than simply held as a store of value. That is a plausible reading of the pattern, not proof that each transfer settled a purchase. Cointelegraph independently reported the same headline measurements from the Chainalysis release.
What the data mean for payment providers
For payment companies, the important signal is the combination of growth and channel. Activity moving directly between self-custodied wallets can sit outside the customer interfaces of a conventional exchange, reducing the usefulness of exchange account data as a complete view of a transaction chain.
Providers serving counterparties, corridors or off-ramps connected to China may therefore need controls that examine wallet exposure as well as customer identity and account behavior. Relevant questions include whether a transfer touches a sanctioned or illicit address, where stablecoins are converted to bank money, and which intermediary can screen, freeze or reject activity at each stage.
The settlement sequence also matters. An on-chain transfer can complete around the clock, but that does not show that a stablecoin was redeemed, that reserves were liquidated or that fiat funds reached a beneficiary’s bank account. Token transfer, issuer redemption and bank settlement are separate operational events with different compliance and liquidity constraints.
The estimates have important limits
The regional figures form part of Chainalysis’s 2026 Geography of Crypto research and use the company’s proprietary attribution model. Its broader methodology assigns activity to countries using service and wallet data, including GDP-adjusted web traffic for some service flows. Chainalysis acknowledges that filtering virtual private network and bot traffic is imperfect.
The company also describes its estimates as a lower bound because it excludes transfers that it cannot confidently attribute to a country and omits some unclustered personal-wallet activity. Those choices improve precision but leave uncertainty around the true market size.
Chainalysis separately proposes a possible relationship between the acceleration in wallet activity and changes to China’s social-credit system. It explicitly labels that explanation a working hypothesis. The timing does not establish causation, so payment providers should not treat it as a verified driver of the measured growth.
The practical conclusion is narrower: Chainalysis has detected a substantial increase in China-linked P2P stablecoin wallet activity, with unusually high turnover in its dataset. The measurements support closer attention to self-custody, off-ramp and transaction-monitoring exposure, but not a claim that all of the value represents ordinary domestic payments.