The Hidden Centralization Landscape of Stablecoin Payments: 85% of Transaction Volume Controlled by the Top 1000 Wallets

Original Title: Stablecoin Payments from the Ground Up

Original Source: Artemis

Original Compilation: Deep Tide Techflow

This report empirically analyzes the use of stablecoin payments, covering transactions between individuals (P2P), businesses (B2B), and between individuals and businesses (P2B/B2P).

This report conducts an empirical analysis of stablecoin payment usage, examining transaction patterns between individuals (P2P), businesses (B2B), and between individuals and businesses (P2B/B2P). We utilize the Artemis dataset, which provides metadata on wallet addresses, including geographic location estimates, institutional ownership labels, and smart contract identifiers. By analyzing the characteristics of sender and receiver wallets, we classify transactions. The focus of the analysis is on the Ethereum network, which hosts approximately 52% of the global stablecoin supply.

We primarily study two mainstream stablecoins: USDT and USDC, which together account for 88% of the market share. Despite a significant increase in the adoption of stablecoins and regulatory scrutiny over the past year, a key question remains unanswered: how does the actual use of stablecoins in payments compare to other activities? This report aims to reveal the main drivers of stablecoin payment adoption and provide insights for predicting future trends.

1. Background

In recent years, the adoption of stablecoins has grown significantly, with a supply reaching $200 billion and a monthly original transfer volume exceeding $4 trillion. Although blockchain networks provide fully transparent transaction records that can be analyzed, the anonymity of these networks and the lack of information regarding the purpose of transactions (e.g., domestic payments, cross-border payments, trading, etc.) make transaction and user analysis challenging.

Furthermore, the use of smart contracts and automated trading on networks like Ethereum further complicates the analysis, as a single transaction may involve interactions with multiple smart contracts and tokens. Therefore, a key unresolved question is how to assess the current use of stablecoins in the payment space relative to other activities (such as trading). While many researchers are working to address this complex issue, this report aims to provide additional methods for evaluating the use of stablecoins, particularly for payment purposes.

Overall, there are two main approaches to assessing stablecoin usage (especially for payment purposes).

The first approach is the filtering approach, which uses raw blockchain transaction data and employs filtering techniques to remove noise, thereby providing a more accurate estimate of stablecoin payment usage.

The second approach involves surveying major stablecoin payment providers and estimating stablecoin activity based on their disclosed payment data.

The Visa Onchain Analytics Dashboard, developed in collaboration with Allium Labs, employs the first approach. They reduce noise in the raw data through filtering techniques, providing clearer information on stablecoin activity. The research indicates that after filtering the raw data, the overall monthly stablecoin transaction volume decreased from approximately $5 trillion (total transaction volume) to $1 trillion (adjusted transaction volume). When considering only retail transaction volume (transactions with amounts below $250), the volume is only $6 billion. We adopted a filtering method similar to that of the Visa Onchain Analytics Dashboard, but our approach focuses more on explicitly labeling transactions as payment purposes.

The second method, based on corporate survey data, has been applied in the "Fireblocks 2025 Stablecoin Status Report" and the "Stablecoin Payments from the Ground Up" report. These two reports utilize disclosure information from major companies in the blockchain payment market to estimate the direct use of stablecoins in payments. In particular, the "Stablecoin Payments from the Ground Up" report provides an overall estimate of stablecoin payment transaction volume, categorizing these payments into B2B (business-to-business), B2C (business-to-consumer), P2P (peer-to-peer), and other categories. The report shows that as of February 2025, the annual settlement total is approximately $72.3 billion, with most being B2B transactions.

The main contribution of this study lies in applying data filtering methods to estimate the use of stablecoins in on-chain payments. The findings reveal the usage of stablecoins and provide more accurate estimates. Additionally, we offer guidance for researchers on using data filtering methods to process raw blockchain data, reduce noise, and improve estimates.

2. Data

Our dataset covers all stablecoin transactions on the Ethereum blockchain from August 2024 to August 2025. The analysis focuses on transactions involving the two main stablecoins, USDC and USDT. These two stablecoins were chosen due to their high market share and strong price stability, which reduces noise in the analysis process. We only focus on transfer transactions, excluding minting, burning, or bridging transactions. Table 1 summarizes the overall situation of the dataset used in our analysis.

Table 1: Summary of Transaction Types

3. Methods and Results

In this section, we detail the methods used to analyze stablecoin usage, focusing on payment transactions. First, we filter the data by distinguishing transactions that involve interactions with smart contracts from those that represent transfers between EOAs (Externally Owned Accounts), classifying the latter as payment transactions. This process is detailed in Section 3.1. Subsequently, Section 3.2 explains how to further classify payment transactions into P2P, B2B, B2P, P2B, and internal B-type transactions using EOA account label data provided by Artemis. Finally, Section 3.3 analyzes the concentration of stablecoin transactions.

3.1 Stablecoin Payments (EOA) vs. Smart Contract Transactions

In the decentralized finance (DeFi) space, many transactions involve interactions with smart contracts and combine multiple financial operations within a single transaction, such as swapping one token for another through multiple liquidity pools. This complexity makes it more challenging to analyze the use of stablecoins solely for payment purposes.

To simplify the analysis and enhance the ability to mark stablecoin blockchain transactions as payments, we define stablecoin payments as any ERC-20 stablecoin transfer from one EOA address to another EOA address (excluding minting and burning transactions). Any transaction not marked as a payment will be classified as a smart contract transaction, including all transactions involving interactions with smart contracts (primarily DeFi transactions).

Figure 1 shows that most payments between users (EOA-EOA) are completed directly, with each transaction hash corresponding to a single transfer. Some multi EOA-EOA transfers within the same transaction hash are primarily completed through aggregators, indicating that the use of aggregators in simple transfers is still relatively low. In contrast, the distribution of smart contract transactions is different, containing more multiple transfer transactions. This indicates that in DeFi operations, stablecoins typically flow between different applications and routers, ultimately returning to EOA accounts.

Figure 1:

The analysis sample data covers transactions from July 4, 2025, to July 31, 2025.

Table 2 and Figure 2 show that, in terms of transaction count, the ratio of payments (EOA-EOA) to smart contract transactions (DeFi) is approximately 50:50, while smart contract transactions account for 53.2% of the transaction volume. However, Figure 2 indicates that the volatility of transaction volume (total transfer amount) is greater than that of transaction count, suggesting that large EOA-EOA transfers primarily driven by institutions lead to these fluctuations.

Table 2: Summary of Transaction Types

Figure 2:

Figure 3 explores the distribution of transaction amounts for payments (EOA-EOA) versus smart contract transactions. The amount distribution for both payment transactions and smart contract transactions resembles a heavy-tailed normal distribution, with an average of approximately $100 to $1,000.

However, there is a significant peak for transactions below $0.1, which may indicate the presence of bot activity or manipulation related to fake trading activities and wash trading, consistent with descriptions by Halaburda et al. (2025) and Cong et al. (2023).

Since Ethereum's gas fees typically exceed $0.1, transactions below this threshold require further scrutiny and may need to be excluded from the analysis.

Figure 3:

The data sample used in this analysis covers transaction records from July 4, 2025, to July 31, 2025.

3.2 Payment Types

By utilizing the label information provided by Artemis, we can further analyze payments between two EOAs (Externally Owned Accounts). Artemis provides label information for many Ethereum wallet addresses, allowing us to identify wallets owned by institutions (e.g., Coinbase). We categorize payment transactions into five types: P2P, B2B, B2P, P2B, and internal B-type. Below is a detailed description of each category.

P2P Payments:

P2P (peer-to-peer) blockchain payments refer to transactions that transfer funds directly from one user to another via the blockchain network. In account-based blockchains (like Ethereum), such P2P transactions are defined as the process of transferring digital assets from one user's wallet (EOA account) to another user's EOA wallet. All transactions are recorded and verified on the blockchain without the need for intermediary institutions.

Main Challenges:

A major challenge is identifying whether a transaction between two wallets in the account system indeed occurs between two independent entities (i.e., individuals rather than companies) and correctly classifying it as a P2P transaction. For example, transfers between a user's own accounts (i.e., Sybil accounts) should not be counted as P2P transactions. However, if we simply define all transactions between EOAs as P2P transactions, we may incorrectly classify such transfers as P2P.

Another issue arises when an EOA account is owned by a company, such as a centralized exchange (CEX, like Coinbase); in this case, the EOA wallet is not actually owned by a real individual. In our dataset, we are able to label many institutional and corporate EOA wallets; however, due to incomplete label information, some EOAs owned by companies but not recorded in our dataset may be incorrectly labeled as personal wallets.

Finally, this method cannot capture blockchain P2P payments conducted through intermediary institutions—also known as the "stablecoin sandwich" model. In this model, funds are transferred between users through intermediaries that utilize blockchain for settlement. Specifically, fiat currency is first sent to the intermediary, which converts it into cryptocurrency, then the funds are transferred via the blockchain network, and finally, the receiving intermediary (which can be the same or a different intermediary) converts it back to fiat currency. The blockchain transfer serves as the "middle layer" of the "sandwich," while the conversion of fiat currency constitutes the "outer layer." The main challenge in identifying these transactions is that they are executed by intermediaries, which may bundle multiple transactions together to reduce gas fees. Therefore, some key data (such as exact transaction amounts and the number of users involved) is only available on the intermediary's platform.

B2B Payments:

Business-to-business (B2B) transactions refer to electronic transfers from one business to another via the blockchain network. In our dataset, stablecoin payments refer to transfers between two known institutional EOA wallets, such as from Coinbase to Binance.

Internal B Payments:

Transactions between two EOA wallets of the same institution are labeled as internal B-type transactions.

P2B (or B2P) Payments:

Personal-to-business (P2B) or business-to-person (B2P) transactions refer to electronic transfers between individuals and businesses, which can be bidirectional.

Using this labeling method, we analyzed the payment data (limited to EOA-EOA transfers), with the main results summarized in Table 3. The data shows that 67% of EOA-EOA transactions belong to the P2P type, but they only account for 24% of the total payment volume. This result further indicates that P2P users have lower transfer amounts compared to institutions. Additionally, one of the categories with the highest payment transaction volume is internal B-type, meaning that transfers within the same organization constitute a significant proportion. Exploring the specific implications of internal B-type transactions and how to account for them in payment activity analysis remains an interesting question for further research.

Table 3: Distribution of Transactions by Payment Category

Finally, Figure 4 shows the cumulative distribution function (CDF) of transaction amounts categorized by payment type. The CDF clearly indicates significant differences in the distribution of transaction amounts across different categories. Most transactions with amounts below $0.1 among EOA-EOA accounts are of the P2P type, further supporting the notion that these transactions may be driven more by bots and manipulated wallets rather than initiated by institutions labeled in our dataset. Additionally, the CDF for P2P transactions further supports the view that most transactions have smaller amounts, while those labeled as B2B and internal B-type show significantly higher transaction amounts. Lastly, the CDF for P2B and B2P transactions falls between P2P and B2B.

Figure 4:

The data sample used in this analysis covers transaction records from July 4, 2025, to July 31, 2025.

Figures 5 and 6 illustrate the trends over time for each payment category.

Figure 5 focuses on weekly changes, showing a consistent adoption trend and growth in weekly transaction volume across all categories. Table 4 further summarizes the overall changes from August 2024 to August 2025.

Additionally, Figure 6 shows the differences in payments between weekdays and weekends, clearly indicating a decrease in payment transaction volume over the weekend. Overall, the usage of payment transactions across all categories shows a growing trend over time on both weekdays and weekends.

Figure 5:

Figure 6:

Table 4: Changes in Payment Transaction Volume, Count, and Amount Over Time

3.3 Concentration of Stablecoin Transactions

In Figure 9, we calculate the concentration of major sending wallets for stablecoins sent through the Ethereum blockchain. Clearly, the majority of stablecoin transfer volume is concentrated in a small number of wallets. During our sample period, the top 1,000 wallets contributed approximately 84% of the transaction volume.

This indicates that, despite DeFi and blockchain aiming to support and promote decentralization, there are still highly concentrated characteristics in certain aspects.

Figure 9:

The data sample used in this analysis covers transaction records from July 4, 2025, to July 31, 2025.

4. Discussion

It is evident that the adoption rate of stablecoins is continuously increasing over time, with transaction volume and transaction count more than doubling from August 2024 to August 2025. Estimating the use of stablecoins in payments is a challenging task, and an increasing number of tools are being developed to help improve this estimation. This study utilizes label data provided by Artemis to explore and estimate the use of stablecoin payments recorded on the blockchain (Ethereum).

Our estimation results indicate that stablecoin payments account for 47% of the total transaction volume (35% if internal B-type transactions are excluded). Given our limited restrictions on payment classification (primarily based on EOA-EOA transfers), this estimate can be viewed as an upper limit. However, researchers can further apply filtering methods such as upper and lower limits on transaction amounts based on their research objectives. For instance, increasing the minimum amount limit to $0.1 can exclude the low-value transaction manipulations mentioned in Section 3.1.

In Section 3.2, by further categorizing payment transactions into P2P, B2B, P2B, B2P, and internal B-type transactions using Artemis label data, we found that P2P payments account for only 23.7% of total payment transaction volume (from all raw data) or 11.3% (excluding internal B-type transactions). Previous research indicated that P2P payments account for about 25% of stablecoin payments, and our results are consistent with this.

Finally, in Section 3.3, we observed that, in terms of transaction volume, most stablecoin transactions are concentrated in the top 1,000 wallets. This raises an interesting question: is the use of stablecoins developing as a payment tool driven by intermediaries and large companies, or as a settlement tool for P2P transactions? Time will reveal the answer.

References \<1> Yaish, A., Chemaya, N., Cong, L. W., & Malkhi, D. (2025). Inequality in the Age of Pseudonymity. arXiv preprint arXiv:2508.04668. \<2> Awrey, D., Jackson, H. E., & Massad, T. G. (2025). Stable Foundations: Towards a Robust and Bipartisan Approach to Stablecoin Legislation. Available at SSRN 5197044. \<3> Halaburda, H., Livshits, B., & Yaish, A. (2025). Platform building with fake consumers: On double dippers and airdrop farmers. NYU Stern School of Business Research Paper Forthcoming. \<4> Cong, L. W., Li, X., Tang, K., & Yang, Y. (2023). Crypto wash trading. Management Science, 69(11), 6427-6454.

Original Link