Motif-based feed selection (S4) raises illicit concentration far above baselines on most AML datasets tested, but loses to a simpler degree-imbalance heuristic on the lowest-illicit-density one

amlanti-money-launderingtransaction-networksgraph-algorithmsspnsaarxiv

A 2026 preprint proposes "motif-based coherent feed selection" (labeled S4) as a strategy for choosing which small set of entities to seed SPNSA (Shortest Paths Network Search Algorithm) with, when extracting a compact, illicit-rich subgraph from a transaction network. Tested against uniform-random (S1) and two degree-based heuristics (S2, S3) on the Elliptic Bitcoin graph and the IBM-AML synthetic benchmark family, S4 produced the highest illicit-node ratio of any strategy tested on most dataset variants, while keeping the extracted subgraph small. On Elliptic, at feed size k=200 and SPNSA radius r=1, S4+SPNSA produced a 213-node subgraph with a 33.8% illicit ratio — against a dataset-wide base rate of 2.23% and a random-feed baseline near 2–3%, a gain the authors describe as roughly 14×.

The advantage is not universal. On IBM-AML LI-Small — the variant with the lowest dataset-wide illicit rate of the four tested (1.04%) — S4 was outperformed by the much simpler S2 heuristic (ranking nodes by |out-degree − in-degree|): at the same (k, r) = (200, 1) settings, S2 reached 11.4% against S4's 5.5%. The authors read this as evidence that the best graph-only feed-selection signal is dataset-regime-dependent rather than universal, not as a refutation of S4's value elsewhere.

Both figures are the paper's own self-reported experimental results, read directly from the primary preprint (Tier 1), clearing the Tier 1–2 sourcing floor required for quantitative claims.