Paper 2025/465

zkAML: Zero-knowledge Anti Money Laundering in Smart Contracts with whitelist approach

Abstract

In the interconnected global financial system, anti-money laundering (AML) and combating the financing of terrorism (CFT) regulations are indispensable for safeguarding financial integrity. However, while illicit transactions constitute only a small fraction of overall financial activities, traditional AML/CFT frameworks impose uniform compliance burdens on all users, resulting in inefficiencies, transaction delays, and privacy concerns. These issues stem from the institution-centric model, where financial entities independently conduct compliance checks, resulting in repeated exposure of personally identifiable information (PII) and operational bottlenecks. To address these challenges, we introduce \textsf{zkAML}, a cryptographic framework that offers a novel approach to AML/CFT compliance. By leveraging zero-knowledge Succinct Non-Interactive Argument of Knowledge (zk-SNARK) proofs, \textsf{zkAML}~enables users to cryptographically demonstrate their regulatory compliance without revealing sensitive personal information. This approach eliminates redundant identity checks, streamlines compliance procedures, and enhances transaction efficiency while preserving user privacy. We implement and evaluate \textsf{zkAML}~on a blockchain network to demonstrate its practicality. Our experimental results show that \textsf{zkAML}~achieves 55 transactions per second (TPS) on a public network and 324 TPS on a private network. The zk-SNARK proof generation times are $$ms for senders and $$ms for receivers, with a constant verification time of $$ms per transaction. These findings highlight \textsf{zkAML}'s potential as a privacy-preserving and regulation-compliant solution for modern financial systems.