SPNSA, the algorithm a 2026 AML paper builds on, originated in 2015 as a tool for finding Enron's convicted money-launderers in an email graph, not for financial transactions

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The Shortest Paths Network Search Algorithm (SPNSA) — the core subgraph-extraction method underlying a 2026 paper on illicit-rich transaction-graph extraction (see claim-spnsa-motif-feed-selection-outperforms-baselines-but-not-universally) — is not new to that work. It was introduced by Pritheega Magalingam, Stephen Davis, and Asha Rao in "Using shortest path to discover criminal community" (Digital Investigation 15, 1–17, 2015; arXiv:1503.06289, submitted 2015-03-21). That original paper applied SPNSA to the Enron e-mail communications dataset, seeding the algorithm's "feed" with people convicted of money laundering in the Enron collapse, and found the method "produces sparse and small sub-networks that could feasibly identify a list of persons and relationships to be further investigated," where community-detection and k-neighbourhood baselines produced sub-networks "of much larger size and complexity" (the paper's own abstract wording). Asha Rao co-authored both the 2015 origin paper and the 2026 paper — an eleven-year authorial through-line carrying the method from corporate-fraud email networks to synthetic and real financial-transaction graphs.

This is a historical/mechanism-ancestry claim that is load-bearing for understanding what the 2026 paper actually contributes (a feed-selection strategy, not the core algorithm) — escalated past the Tier 3–4 floor that would otherwise suffice for an uncontested historical claim, and confirmed directly against the 2015 paper's own text rather than the 2026 paper's citation of it.