III. Expectations and Limitations of Blockchain Analysis
1. What Is Blockchain Analysis?
In this section, we look at blockchain analysis as an investigative method that has proven useful in addressing tax enforcement challenges arising from the anonymity and decentralization of cryptocurrencies. By examining transaction data on the blockchain, it is possible to detect patterns, relationships, and activities among entities—such as identifiable individuals or organizations—involved in crypto transactions.
Transactions involving cryptocurrencies are recorded on the blockchain, and on public blockchains in particular, anyone can view and verify this information without special permission. This means that if a wallet address is known, it becomes possible to trace its transaction history and balances, as well as to infer which CEX accounts or wallets may be controlled by the same person. Blockchain analysis takes advantage not only of the traceability and transparency of cryptocurrencies, but also of their pseudonymous nature.
That said, blockchains themselves do not contain personally identifiable information. However, the process of converting fiat currency into cryptocurrency (known as an “on-ramp”) and converting it back into fiat (an “off-ramp”) is typically handled by centralized institutions that are subject to Know Your Customer (KYC) and anti-money laundering/counter-terrorist financing (AML/CTF) regulations.
As a result, these on- and off-ramps serve as key points of connection between on-chain activity and real-world identities. It should be noted, however, that decentralized exchanges (DEXs) generally do not offer services that directly convert cryptocurrencies into fiat currency.
Because centralized institutions still play a major role in providing crypto-related services, opportunities to receive payments in crypto remain limited compared to fiat currency, and real-world use cases for crypto as a means of payment are still relatively narrow. This situation persists in part because most cryptocurrencies are primarily used for purposes other than everyday payments.
For example, suppose that (1) an unverified CEX account or wallet address—one that has not completed identity verification—has conducted transactions on the blockchain with (2) a domestic CEX or another exchange that does require identity verification.
If it can be determined that both (1) and (2) are controlled by the same individual, then the identity of the person behind (1) can also be established. From there, other CEX accounts or wallets likely managed by the same person can be identified as well.
The National Tax Agency can identify (ⅰ) domestic CEX accounts by requesting information on Japanese taxpayers who meet specified criteria from domestic centralized exchanges (CEXs) during the investigation selection phase, as well as by requesting information on investigation targets from domestic CEXs during individual audits. Once it is established that a specific account is transacting with (ⅱ) “overseas CEXs or private wallets,” blockchain analysis can identify indicators that (ⅰ) and (ⅱ) are managed by the same individual. Through this process, it becomes possible to identify the individual controlling (ⅱ) and to uncover additional overseas CEX accounts or wallets that are likely under that individual’s control. Accordingly, blockchain analysis is a highly effective investigative tool in both the case selection stage and the individual audit stage.
Blockchain analysis can remain effective even where technologies designed to enhance anonymity are deliberately employed. For example, blockchain data may still allow investigators to trace transactions and fund flows or to identify the controllers of CEX accounts and private wallets in situations such as the following1:
・Transfers of crypto assets from Wallet A to Wallet B using multiple intermediary private wallets to complicate tracing
・Use of mixing or tumbling services that pool crypto assets from multiple users to obscure the origin and ownership of funds
・Use of services or protocols that enable transfers between different blockchain networks, resulting in complex and layered transaction paths
・Use of privacy-focused cryptocurrencies, such as Monero or Zcash, which employ advanced cryptographic techniques to conceal transaction details
At present, tax authorities are likely to depend primarily on blockchain analysis tools provided by private-sector firms. Although basic analysis can be conducted using publicly available (free) tools and websites, more precise and reliable analysis is achievable through professional platforms such as Reactor, a transaction-tracking tool offered by Chainalysis, a leading blockchain analytics company. By inputting a specific wallet address into Reactor, analysts can identify address groups associated with that address through clustering techniques—groupings of multiple wallet addresses inferred to be controlled by the same entity. This allows investigators to determine which entities (such as individuals, organizations, CEXs, or other groups) are connected to those addresses, or to visualize transaction flows graphically to identify the routes and ultimate destinations of funds.
Specifically, Reactor enables the following analytical functions2:
・Wallet address association (clustering)
・Analysis of cluster attributes, including addresses contained within the cluster, aggregate balances, internal and external transaction flows, and the cluster’s classification (e.g., CEXs, organizations involved in fraud or money laundering)
・Linkage between clusters and identified entities, such as determining that a particular wallet address belongs to an overseas exchange; the use of Chainalysis’s proprietary entity attribution data enhances both the accuracy and efficiency of this process
In addition, Reactor provides intuitive visualizations of transaction flows and inter-cluster relationships, allowing analysts to understand how funds move across the blockchain ecosystem. This visualization capability is particularly effective in identifying the ultimate destination or storage location of crypto assets.
- https://www.chainalysis.com/blog/crypto-money-laundering-japan-japanese/ ↩︎
- https://anchor-u.com/product/chainalysis/.United States v. Sterlingov, 719 F. Supp. 3d 65, 71-77 (D.D.C. 2024). ↩︎
