Zero-Knowledge Proofs for AML Compliance in High-Value Payment Transactions

Abstract

High-value payment transactions (HVTs) face heightened exposure to money laundering risks due to their large monetary volumes, cross-jurisdictional nature, and the increasing complexity of financial networks. Traditional Anti-Money Laundering (AML) procedures rely heavily on sharing customer identities, transactional attributes, and risk-model outputs across institutions and regulators—creating substantial privacy, security, and data-handling risks. Zero-Knowledge Proofs (ZKPs) offer a transformative alternative by enabling financial institutions to prove compliance with AML requirements without revealing the underlying sensitive information. This paper examines the design and application of ZKP-based compliance frameworks for HVT ecosystems, detailing how AML checks—including KYC verification, sanctions screening, transaction-amount threshold validation, behavioral-risk scoring, and source-of-funds assessment—can be cryptographically attested through privacy-preserving proofs.
We propose a hybrid architecture that combines off-chain AML computation with an on-chain ZKP verification and audit layer supported by secure regulatory nodes. Through structured workflows and proof types such as range proofs, list membership proofs, and rule-compliance circuits, the model ensures regulatory oversight while maintaining strict confidentiality. The study also evaluates the performance implications of ZKP systems in high-volume transaction environments and addresses security, interoperability, and oracle-reliability concerns. Ultimately, ZKP-enabled AML frameworks demonstrate significant potential to enhance compliance efficiency, reduce data-exposure risk, and strengthen trust across global payment networks. The paper concludes by outlining future research opportunities, including AI-driven AML circuits, cross-border ZKP interoperability standards, and integration with decentralized identity solutions.