Temporal Graph Networks for Graph Anomaly Detection in Financial Networks

arXiv:2404.00060v1 Announce Type: cross
Abstract: This paper explores the utilization of Temporal Graph Networks (TGN) for financial anomaly detection, a pressing need in the era of fintech and digitized financial transactions. We present a comprehensive framework that leverages TGN, capable of capturing dynamic changes in edges within financial networks, for fraud detection. Our study compares TGN's performance against static Graph Neural Network (GNN) baselines, as well as cutting-edge hypergraph neural network baselines using DGraph dataset for a realistic financial context. …

abstract anomaly anomaly detection arxiv cs.ai cs.lg detection dynamic financial fintech framework graph networks paper q-fin.st temporal transactions type