Designing a law–data–SupTech framework for crypto-asset supervision: a frontier-market blueprint from Vietnam

Purpose This paper aims to examine how Vietnamese regulators can narrow the supervisory gap in crypto-asset markets by pairing recent legal reforms with a low-cost law–data–SupTech strategy. Vietnam is treated as a crypto-intensive frontier market where household adoption is high while supervisory capacity and data infrastructures remain thin. Design/methodology/approach This paper adopts a design-oriented regulatory methodology. It combines doctrinal analysis of Vietnam’s post-2022 anti-money laundering (AML), digital technology and fintech-sandbox instruments with focused comparison of Financial Action Task Force, Financial Stability Board and International Organization of Securities Commissions standards and practice in the EU and Singapore. Rather than empirically testing an existing SupTech system, it specifies the legal, data and institutional conditions for artificial intelligence (AI)-enabled supervision in a crypto-intensive frontier market. Findings The analysis identifies persistent gaps in the identification of crypto-asset service providers, including virtual asset service providers for anti-money laundering and counter-terrorist financing purposes, the standardisation of reporting duties and the systematic use of on-chain analytics in day-to-day supervision. It proposes a sequenced strategy in which Decree 94/2025’s sandbox operates as a SupTech sandbox that generates clean, labelled data sets for supervisory AI before any wider rollout to the broader market. Practical implications The framework offers a staged but realistic way for frontier-market supervisors to align licencing, reporting and analytics under tight fiscal and human-resource constraints, and to experiment with SupTech tools without large upfront investments in data platforms. Originality/value This paper delivers one of the first concrete law–data–SupTech blueprints tailored to Vietnam’s 2025 reforms and shows how sandbox-generated data can support AI-enabled supervision in other crypto-intensive emerging markets.