Consensus Highlights: Bitrace Shares AI-Driven RegTech Trends
From February 19-20, 2025, Bitrace CEO and Co-Founder Isabel Shi was invited to speak at the Consensus conference. During the event, Isabel delivered a keynote speech and participated in a live interview with CoinDesk, where she shared her insights on blockchain compliance, risk monitoring, and Web3 developments.
AI in On-Chain Risk Monitoring
Drawing from Bitrace’s expertise, Isabel explored how AI is transforming RegTech to enhance the accuracy of crypto asset risk identification and monitoring.
AI Tagging Systems & Models
AI-powered tagging models help identify various risk characteristics, including structural traits, behavioral patterns, and illicit fund inflows:
- Structural Traits: Recognizing publicly available data and standardized structures to detect potentially suspicious addresses.
- Behavioral Patterns: Identifying common risk behaviors even with limited data sources.
- Illicit Fund Inflows: Analyzing fund movement patterns to uncover potential illicit activities.
AI-Driven Fund Flow Tracking
- Unlike traditional transaction tracing methods, AI can differentiate and tag transactions based on specific crime types. For example, AI can identify transactions related to illicit markets, drug trade, phishing scams, online gambling, and money laundering, each of which follows distinct transaction flow patterns.
- AI-powered monitoring systems scan the blockchain network in real-time, promptly detecting and alerting potential risks to provide more precise risk warnings.
Bitrace leverages AI technology to deliver comprehensive on-chain monitoring and risk assessments, including Anti-Money Laundering (AML) engines, risk detection, and alerting capabilities. This enables businesses to remain compliant while proactively identifying potential risks and preventing illicit activities on the blockchain.
Regulatory Challenges for APAC Enterprises
During the live interview with CoinDesk, Isabel highlighted key regulatory challenges faced by APAC enterprises:
- Regulatory Arbitrage: The competitive nature, economic development stages, and structural differences among APAC countries lead to regulatory inconsistencies. For example, Singapore and the U.S. generally regulate crypto exchanges through money transfer licensing frameworks, whereas Hong Kong enforces stricter asset protection rules for customers. Given the cross-border operations of Web3 firms, establishing a unified compliance framework remains a significant challenge.
- Rapid Technological Advancement vs. Lagging Regulation: Unlike traditional finance, which relies on standardized, closed regulatory frameworks, Web3 operates on decentralized, anonymous, and permissionless transactions. This makes it difficult for traditional regulations to keep pace with industry developments.
- Insufficient RegTech Adoption in APAC: Isabel emphasized that while Web3 heavily relies on RegTech, APAC lags behind in its support for RegTech solutions. In contrast, governments and investors in the U.S. and Europe actively support RegTech firms, fostering stronger compliance solutions and regulatory confidence. She urged APAC regulators to prioritize RegTech adoption to enhance market supervision and compliance capabilities.
Conclusion
Isabel underscored the transformative potential of AI in enhancing the accuracy of on-chain risk monitoring and called for greater support for RegTech in APAC. Her insights provided valuable guidance on leveraging AI technology to strengthen blockchain compliance and security.
About Bitrace
As a leading RegTech company in Hong Kong, Bitrace specializes in providing crypto transaction risk identification and prevention solutions for enterprises and regulators. By combining advanced machine learning technology with deep expertise in crypto crime analysis, Bitrace is committed to enhancing security in the crypto industry and helping stakeholders navigate the growing complexities of crypto asset risks.
Contact us:
Website: www.bitrace.io
Email: bd@bitrace.io
Twitter: @Bitrace_team
LinkedIn：@bitrace tech
