Graph Analytics

Graph analytics models entities and their relationships as nodes and edges to surface patterns traditional tables miss. In AML and fraud, it reveals money mule networks, collusive merchants, and shared infrastructure such as devices, IPs, or beneficiaries. Techniques include community detection, centrality, path analysis, and subgraph matching against typologies. Integrated with entity resolution and funds-flow data, graphs power alert grouping, prioritize high-impact clusters, and support decisive actions like coordinated closures.Governance must track data lineage, limit sensitive attributes, and document thresholds to avoid over-linking. Effective deployments pair dashboards for analysts with model feedback loops, ensuring insights translate into tuned scenarios and reduced false positives. Graphs also strengthen SAR narratives by providing clear visual timelines and connections.