Stellar has long positioned itself as a blockchain for real-world money movement. But what does that actually look like onchain?

In this second installment of our Stablecoin Onchain Series - a data-driven research series looking at stablecoin usage across web3 - we explore USDC usage patterns on Stellar, from high-frequency intrachain payments to cross-chain settlements via Decaf and Allbridge. With a dataset spanning over 90 million transactions and $17B in volume, this analysis breaks down who is using Stellar for stablecoin transfers, when those transfers happen, and how value enters and exits the network.

Our findings highlight the unique role Stellar plays in global stablecoin adoption - supporting microtransaction use cases, institutional flows, and secure cross-chain bridges alike.

Stellar: A network for daily transfers

Focusing on USDC activity, between September 2024 and September 2025, we observed:

• 91.3 million USDC transactions

• $17.9 billion total volume

• Average of 252,216 transactions per day

• Average transaction size: $196.71

These numbers reveal that USDC is actively used as a day-to-day payment rail on Stellar, with relatively small transfers dominating the majority of onchain activity. Notably, the median transaction size is only 1.57 USDC, confirming that the network supports high-volume microtransactions alongside larger institutional flows.

Time-of-Day Patterns

Usage patterns by time of day highlight distinct behaviors across user types and geographies. Transaction activity peaks around 14:00–15:00 UTC, a time consistent with the business hours of European and Middle Eastern regions. The lowest transaction volume is seen between 4:00 and 10:00 UTC, aligning with overnight hours across most EMEA regions.

While the number of transactions aligned with EMEA mid-day and evening (12-9 pm), volume tells a different story. 

The largest USDC movements by value consistently occur around 7:00 UTC, during relatively quiet periods of transactions. This implies that wallets responsible for high-value transfers are not the same as those driving high-frequency transaction counts, and may operate on a different schedule (most likely East Asia) - likely corresponding to institutional or automated activity based in other regions.

As with our earlier analysis of overall USDC flows via CCTP, whale wallets account for the majority of activity on Stellar. Just 0.1% of transactions on Stellar were responsible for 64.5% of total USDC volume - closely mirroring the 70.8% share held by the top 0.1% of CCTP transfers. In both cases, a small subset of whale transactions dominates the flow of funds.

Unlike the overall CCTP transaction analysis, we did not detect a 3-minute pattern in rhythmic spikes in transactions; however, there is a significant spike in transactions at minute 32 of every hour. It is unclear what might be driving this.

Weekday vs Weekend

While the number of transactions remains relatively steady across weekdays and weekends (a slight dip on weekends), the total volume transacted decreases significantly on weekends. 

The data shows that volume from Monday through Friday is 4.6 times higher than weekend volume. This further supports the view that the most significant USDC flows on Stellar are institutionally driven, as they tend to follow traditional business hours and settlement cycles.

Cross-Chain transfers: How USDC flows to and from Stellar

Stellar's role as a standalone ecosystem is increasingly visible in USDC activity. From July 2025 onward, we tracked transfers of USDC into and out of Stellar, analyzing bridge usage, destination chains, and transaction patterns. This analysis confirms that much of Stellar's activity occurs within its network, with users transacting between Stellar apps or utilizing it for cross-border payments and dollarized remittance apps.

The use case of real-world payments becomes clearer when examining the decimal precision of USDC transactions, with only 5% of transactions being whole numbers, indicating that users are likely settling in USDC after converting amounts from a fiat currency.

Of the 91.3 million USDC transactions and $17.9 billion volume we monitored between Sep 2024-2025, just a few thousand transactions were cross-chain. However, with increasing support from cross-chain bridges in the past few months (NEAR Intents, Axelar and others), we expect cross-chain activity on Stellar to increase in the coming period.

Cross-chain transfers from Stellar primarily flow to Solana, while Solana and Base drive inflows. USDC remains the dominant stablecoin, and Decaf is the most frequently used bridge, followed by Allbridge.

• Top outflow route: Stellar ⟶ Solana

• Top inflow routes: Solana and Base ⟶ Stellar

• Dominant asset: USDC

• Dominant bridge: Decaf (52.7% of transactions), followed by Allbridge (40.9% of transactions)

You can monitor the cross-chain flows of Stellar in real-time on our Stellar Explorer.

Solana vs Base as inflow networks

We also compared the profiles of inbound transactions from Solana and Base. Despite similar transaction counts, the size and volume of transfers from Solana are significantly higher.

This divergence suggests that Solana is preferred for large-value transfers, while Base supports a greater volume of small-value activity. 

The distinction may reflect different user demographics, such as treasury movements from Solana versus user-level remittances from Base.

Onchain risk: Malicious address behavior on Stellar

In parallel with usage trends, we examined how malicious actors interact with USDC on Stellar. We analyzed 12,971 addresses tagged as malicious on the network, focusing on their counterparties and behavioral patterns.

From this dataset, 282 malicious addresses were identified as active in stablecoin transactions, involving a total of 1,524 counterparties. The vast majority of these counterparties (99.2%) were not tagged as malicious, highlighting a common tactic: using clean addresses to obfuscate flows and limit traceability.

• Malicious-to-malicious connections: 0.8%

• Malicious-to-non-malicious connections: 99.2%

• Average counterparties per malicious address: 16.41

• Maximum counterparties observed: 357

This structure supports a common laundering pattern in which actors use multiple clean addresses to fragment and re-route funds. These address clusters can be fingerprinted using Range Trail, enabling real-time investigations, red flag monitoring, and anomaly detection.

Additionally, our Risk API and Faraday products can prevent malicious actors from interacting with your app in real-time. Get in touch for a demo, or read how Varnish Trade uses Range to ensure bad actors do not use its private trading and shielded swaps app.

Scam tokens and lookalike asset abuse

Token impersonation remains a significant issue on Stellar due to its open issuance model. By issuing assets with familiar tickers (e.g., BTC, ETH), scammers can exploit user trust and visual shortcuts, especially among less experienced users.

We reviewed verified tokens on Stellar.Expert and compared them against other assets using the same ticker but issued by unverified or malicious accounts. The results were striking:

• DOGE: 99.06% of transfers involved unverified issuers

• BTC: 92.43%

• ETH: 81.68%

• USDC: 9.67%

However, it's important to contextualize these figures. Much of the activity with these unverified tokens appears to be spam or wash trading by scammers attempting to simulate legitimacy, often routing spoofed assets between their own wallets. These transfers are better understood as network misuse rather than successful fraud, and don't necessarily indicate that counterparties were victims or that the transfers had economic impact.

Still, the presence of large volumes of spoofed activity creates friction and risk - especially for wallets, apps, or users that rely solely on asset tickers. Even in the case of USDC - despite rigorous verification - nearly 1 in 10 transfers involve non-verified assets. This highlights the ongoing need for wallet-level intelligence and token verification layers, particularly in wallets, DEXs, and payment apps that operate on Stellar.

Range's risk tooling can automatically surface counterfeit tokens, detect clusters of scam issuers, and trace victims based on interaction history. Get in touch to learn how we help teams monitor and act on scam activity before value is lost.

Stablecoins at the edge of real-world money movement

The Stellar network presents a unique convergence of retail-grade microtransactions and institutional settlement flows - with both operating on the same rails. Our analysis reveals a consistent narrative: a small number of large-value transactions account for the majority of volume, while the network sustains a high baseline of small, frequent transactions across time zones and days of the week.

This duality makes Stellar an attractive network for real-world financial applications. On one side, it supports cross-border payments, mobile-first wallets, and dollarized remittance apps. On the other, it handles institutional settlements, treasury movements, and cross-chain USDC transfers with the predictability and transparency expected by financial teams.

These traits are increasingly visible onchain:

• USDC remains the dominant stablecoin across both intrachain and interchain flows

• Stellar serves as a bridge between ecosystems, including Base and Solana

• Institutional flows follow weekday cycles, while high-frequency agents transact around the clock

• Scam token activity remains high, but traceable and monitorable with the right tooling

In short, Stellar is not just being used - it is being operationalized. Its core infrastructure, predictable costs, and verification layers make it one of the most effective blockchain environments for stablecoin-based money movement today.

Explore Stellar stablecoin flows with Range

Range provides real-time intelligence across 100+ chains, helping you monitor stablecoin flows, flag high-risk actors, and investigate counterparties across networks.

• Visit the Range Stablecoin Explorer

• View real-time cross-chain transactions and analysis on our Stellar Explorer

• Investigate wallet behavior with Range Trail

If you're a Stellar protocol, wallet, or compliance team, get in touch to integrate real-time security and monitoring into your product.

This article was written by Syed Choudhury, based on data and analysis conducted by Daniel Fiuza Dosil - Lead Data Scientist at Range.

Also read our previous report: USDC via CCTP: How institutions and retail users move money cross-chain.