pc
nid 94231
Jul 24, 2026
ggallwey@vixio.com
Japan
Financial Services Agency
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2697 charsJapan's Financial Services Agency Publishes FinTech Proof-of-Concept Hub Experiment Results on Cryptocurrency Anti-Money Laundering
On July 24, 2026, Japan's Financial Services Agency (FSA) published the results of a proof-of-concept experiment conducted under its FinTech Proof-of-Concept Hub scheme, which was established in September 2017 to reduce barriers to innovation by fintech companies and financial institutions undertaking unprecedented experimental projects.
The experiment, which ran from March to May 2026, was led by Hitachi Ltd. and involved 13 participating organisations including Aozora Bank, JPYC, GMO Coin, Chainalysis Japan, and others. The experiment verified the effectiveness and legal implications of a new framework enabling private-sector entities to share information collaboratively on anti-money laundering (AML) measures targeting crypto-assets and electronic payment methods.
The framework involved three key components: a monitoring system providing risk assessments of blockchain addresses based on shared suspicious address data, transaction information, risk categories, and risk scores; an AML Joint Center conducting investigations on high-risk transactions; and technology providers supplying analytical tools and sanctions-related information. The monitoring system was tested across three functions: post-transaction monitoring for continuous risk evaluation, online real-time assessment of transfer destination addresses before transaction execution, and token monitoring enabling electronic payment method issuers to track holdings and transfers.
Results confirmed that cross-industry information sharing identified suspicious address patterns difficult for individual entities to detect alone. The combination of list-matching and machine learning processes enhanced detection of both known sanctions and crime-related entities and previously unknown risk indicators. All three monitoring system functions demonstrated operational feasibility. However, alerts alone proved insufficient for determining suspicious transaction reporting, trading restrictions, or token freezing decisions, requiring supplementary investigation of fund flows, public information, and related addresses.
The FSA advised that individual entities retain responsibility for suspicious transaction reporting and trading restrictions, with monitoring system alerts never being the sole basis for decisions. The FSA and the Personal Information Protection Commission provided guidance on data sharing consent requirements, data quality assurance, correction procedures, and privacy impact assessments. Applicants must establish internal rules, contracts, and operational procedures addressing data governance, detection logic improvements, access controls, audit logging, and complaint handling procedures.
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2975 charsJapan's Financial Services Agency Publishes FinTech Proof-of-Concept Hub Experiment Results
On July 24, 2026, the Financial Services Agency of Japan (FSA) published the experimental results of Project No. 13 under its " FinTech Proof-of-Concept Hub " scheme. Originally announced on February 27, 2026 , and conducted between March and May 2026, the demonstration experiment was led by Hitachi, Ltd. alongside participating financial institutions, crypto asset exchange service providers (CAESPs), technology providers, and audit firms, including Aozora Bank, GMO Coin, Bitbank, Rakuten Wallet, NEC Corporation, Chainalysis Japan, and Azusa Audit Corporation.
The experiment examined the technical effectiveness and legal feasibility of an industry-wide joint information-sharing framework to enhance anti-money laundering (AML) and countering the financing of terrorism (CFT) measures targeting crypto assets and electronic payment instruments (e.g., stablecoins).
Key findings and structural details from the demonstration include:
Information Sharing Scope Participants shared data points including suspicious addresses, transaction hashes, risk categories (sanctions, fraud, transaction similarity), risk scores (urgent, high, moderate, low), detection rationale, and timestamps to conduct joint analysis and risk assessments.
Core Functions Verified Practical operational feasibility was confirmed across three functions: Post-event monitoring for continuous customer due diligence (CDD) and transaction monitoring; Online instant evaluation to verify destination address risks prior to executing withdrawals; and Token monitoring to enable electronic payment instrument issuers to track ownership and execute freezes/cancellations of illicit tokens.
Post-event monitoring for continuous customer due diligence (CDD) and transaction monitoring;
Online instant evaluation to verify destination address risks prior to executing withdrawals; and
Token monitoring to enable electronic payment instrument issuers to track ownership and execute freezes/cancellations of illicit tokens.
Operational Results Cross-company sharing enabled the identification of risk indicators that individual entities could not detect in isolation. While combining list-matching with machine learning (AI) improved threat detection, system-generated alerts were found to be insufficient on their own to justify administrative actions (e.g., filing suspicious transaction reports or freezing assets) without additional human-led contextual investigations.
The FSA, in consultation with the Personal Information Protection Commission (PPC) , clarified that business operators must ensure explainability and transparency in AI risk-scoring logic to avoid unfair customer detriment. Furthermore, third-party personal data sharing under Article 27 of the Personal Information Protection Act is permitted based on valid consent (including historical data) or under property protection exemptions where obtaining consent is unfeasible or carries a risk of tipping off criminal suspects.