This paper examines how contemporary FinTech architectures shape anti–money laundering (AML) outcomes. We focus on three practice shifts: (i) the growing use of stablecoins on low-fee rails during layering, (ii) cross-chain composability that shortens interdiction windows and exposes Travel Rule gaps, and (iii) uneven financial-crime controls at high-growth FinTechs relative to incumbents. We analyze public evidence from 2020 to 2025—enforcement orders, supervisory reviews, and industry analytics—using a structured coding template and cross-validating against primary sources. We then translate the patterns into operational metrics that can be monitored by issuers, virtual-asset service providers, and supervisors, including time-to-freeze, unfreeze error rate, Travel Rule match rate across counterparties, and case conversion rates from off-chain alerts to on-chain actions, with targets ranging from 12 to 24 months. Limitations: the design is descriptive and relies on public sources; it does not estimate the global prevalence of illicit flows nor identify causal effects. As a calibration point, the 2023 U. S. enforcement against Binance culminated in a 4. 3 billion resolution and multi-year compliance monitorship, establishing concrete baselines for expected controls (Justice, 2023). Overall, the paper offers a portable KPI framework that moves the AML debate from labels to measurable performance, and outlines a minimal reporting template and SupTech dashboard to track progress over time.
Anas Al Qudah (Thu,) studied this question.
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