Tag Archives: fraud detection

Networks, Relationships & Financial Crime Graphs on the Bronze Layer

Financial crime rarely appears in isolated records; it emerges through networks of entities, relationships, and behaviours over time. This article explains why financial crime graphs must be treated as foundational, temporal structures anchored near the Bronze layer of a regulated data platform. It explores how relationships are inferred, versioned, and governed, why “known then” versus “known now” matters, and how poorly designed graphs undermine regulatory defensibility. Done correctly, crime graphs provide explainable, rebuildable network intelligence that stands up to scrutiny years later.

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Probabilistic & Graph-Based Identity in Regulated Financial Services

This article argues that probabilistic and graph-based identity techniques are unavoidable in regulated Financial Services, but only defensible when tightly governed. Deterministic entity resolution remains the foundation, providing anchors, constraints, and auditability. Probabilistic scores and identity graphs introduce likelihood and network reasoning, not truth, and must be time-bound, versioned, and replayable. When anchored to immutable history, SCD2 discipline, and clear guardrails, these techniques enhance fraud and AML insight; without discipline, they create significant regulatory risk.

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