Virtual Asset Service Providers (VASPs) have become a high-value target for organised criminal networks, largely because they enable fast, cross-border movement of value across exchanges, wallets and tokenised products.
According to Arctic Intelligence, the combination of speed, technical complexity and pseudonymous transactions can create opportunities to place, layer and integrate illicit proceeds through on-chain activity, peer-to-peer trades, mixers and opaque intermediary services.
As regulators sharpen expectations around crypto supervision, VASPs are increasingly being judged on whether they can evidence a structured, enterprise-wide approach to managing money laundering, terrorism financing and proliferation financing (ML/TF/PF) risks. For many firms, that means moving beyond policy statements and static checklists towards a risk assessment framework that identifies crypto-specific threats, assesses exposure across products and channels, and tests whether controls work in practice.
A proportionate approach matters, because VASPs vary significantly in size, operating model and technical sophistication. But the direction of travel is consistent: firms need defensible risk assessments that support governance, protect customers and help sustain trust as the digital asset ecosystem matures. In practical terms, that also means being able to explain risk decisions to senior stakeholders and demonstrate outcomes that stand up to regulatory review.
For money laundering reporting officers (MLROs) and senior compliance leaders, the objective is not simply meeting minimum requirements. The bigger challenge is demonstrating a deep and evidence-backed understanding of how ML/TF/PF risks manifest across customer types, wallet behaviours, transaction patterns, jurisdictions and delivery channels—and how mitigation is designed, implemented and monitored over time.
Arctic Intelligence is positioning its ML/TF/PF Risk and Control Assessment Solution as a sector-specific option for VASPs, aiming to provide a structured and regulator-ready method for identifying, assessing and governing financial crime risk across lines of business. The proposition is built around standardisation and evidence: an assessment process designed to be repeatable, reviewable and auditable.
The firm argues that VASPs’ inherent exposure is driven by their gateway role between fiat and digital assets, the velocity and opacity of blockchain transfers, and the borderless nature of crypto services that can intersect with high-risk jurisdictions, sanctions regimes and proliferation financing corridors. Additional risk can emerge where platforms integrate with mixing services, privacy-enhancing assets and DeFi protocols, or where third-party wallets, payment integrations and cross-chain bridges introduce fragmented control environments.
The module is designed to help providers identify and prioritise ML/TF/PF risks using VASP-specific taxonomies aligned to FATF and supervisory expectations, then map controls to the underlying risk drivers. It also emphasises testing design and operational effectiveness, with the intention of enabling firms to show evidence that controls are operating as intended—rather than relying on a compliance tick-box approach.
A further focus is residual risk. By aggregating inherent risk indicators with control performance data, Arctic Intelligence says the module can generate residual risk ratings aligned to risk appetite, escalation thresholds and governance frameworks—aiming to make risk outcomes easier to defend internally and externally.
The solution also highlights audit-readiness through features such as version history, review workflows and reporting intended for regulators, internal audit and governance forums. Arctic Intelligence positions the audit trail and board-ready reporting as a way to make complex, technical risk conclusions digestible for executives, while preserving the underlying evidence base.
In terms of scope, the content library is framed as applicable to a wide range of VASP models—from digital asset exchanges and brokers to custodians, OTC desks, NFT marketplaces, DeFi platforms and wallet providers. The module content can be deployed out-of-the-box or tailored, with options to import a firm’s own indicators and controls, helping teams avoid starting from scratch while maintaining ownership of their methodology.
Finally, the underlying framework is structured around enterprise-wide ML/TF/PF risk groups—such as environmental, customer, product and services, channel, transaction and country risk—alongside control libraries and control tests. It also includes deeper modules focused on product and service risks (for areas like exchange, custody, issuance/fundraising, transfers and wallets) and channel risks spanning face-to-face and non-face-to-face onboarding and transaction routes, including partner and intermediary channels.
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