As blockchain adoption accelerates, regulators and financial institutions face growing pressure to enforce effective anti-money laundering (AML), know your customer (KYC), know your transaction (KYT), and transaction monitoring across decentralized and multi-chain environments. Building on prior research, this project proposes an AI- and blockchain-based RegTech platform that unifies heterogeneous data sources, such as smart contracts, distributed ledger technology (DLT) security audits, and external corporate registries, into a single compliance ecosystem. By developing a comprehensive threat model and a scalable aggregator for smart contract audits and AML/KYT services, the platform aims to deliver adaptive, near–real-time risk identification and suspicious activity detection across multiple blockchain networks.

The project addresses the need for automated threat modeling in dynamic virtual asset markets by integrating machine learning, graph analytics, and knowledge bases to map attack vectors and perform multi-layer risk scoring across addresses, tokens, and cross-chain interactions. Techniques such as clustering, graph-based anomaly detection, deep learning, and sandboxed smart contract analysis will be used to detect exploits, mixing, wash trading, and other illicit behaviors, while continuously learning from on-chain and off-chain intelligence. The platform is designed to align with Hong Kong and global regulatory frameworks by incorporating customizable risk-scoring models, human-in-the-loop supervision, and transparent methodologies that support compliance with evolving standards such as those overseen by the Hong Kong Monetary Authority (HKMA), Securities and Futures Commission (SFC), and Markets in Crypto-Assets Regulation (MiCA).

The roadmap begins with building an intelligent RegTech foundation that combines regulation-oriented knowledge bases, automated threat detection, and smart contract auditing under expert supervision. It then progresses toward agentic, AI-assisted compliance capabilities, including governance-aware analytics for decentralized autonomous organizations (DAOs), tokenized asset oversight, and automated on-chain interventions. Participation in the sandbox and related initiatives will allow the system to be stress-tested under realistic regulatory scenarios, refine human-in-the-loop controls, and contribute to industry best practices. Looking ahead, the project will explore cross-border regulatory sandboxes, adaptive governance mechanisms, and post-quantum security to future-proof blockchain compliance for next-generation digital asset markets.