An unsupervised GNN framework builds period-level graphs from accounting subject associations and uses reconstruction error to rank anomalies in connections and nodes.
bib1"><number>[1]</number>K. H. Guo, X. Yu and C. Wilkin
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Unsupervised Graph Modeling for Anomaly Detection in Accounting Subject Relationships
An unsupervised GNN framework builds period-level graphs from accounting subject associations and uses reconstruction error to rank anomalies in connections and nodes.