Population-Calibrated Graph Screening at 835-Million-Address Scale, with Label-Free Transfer to New Chains
Deployed graph-screening system scores 835 million blockchain addresses and transfers risk labels across chains without training data — potentially reshaping crypto-AML compliance beyond static sanctions-list lookups.
Summary written by editorial AI · Source link below
arXiv:2609.03036v1 Announce Type: new Abstract: Compliance screening of blockchain addresses is, in practice, a lookup against sanctions registries plus clustering heuristics; it fails on unlabelled addresses and on chains with no label coverage at all. We describe a deployed system that scores an address by its position in a multi-chain transaction graph rather than by its presence in a list. The substrate is a single graph of 835,330,427 addresses and 15,826,261,934 edges across five EVM chai
Editorial Analysis
Framed for the Compliance & GRC desk
A deployed system scoring 835 million blockchain addresses with label-free cross-chain transfer could reshape sanctions-screening obligations, especially as EU AML frameworks expand to crypto assets.
Evaluate whether graph-based population-calibrated scoring tools can supplement your current sanctions-registry lookups for crypto-asset compliance.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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