Quick survey of graph-based fraud detection methods. (arXiv:1910.11299v3 [cs.LG] CROSS LISTED)

In general, anomaly detection is the problem of distinguishing between normal
data samples with well defined patterns or signatures and those that do not
conform to the expected profiles. Financial transactions, customer reviews,
social media posts are all characterized by relational information. In these
networks, fraudulent behaviour may appear as a distinctive graph edge, such as
spam message, a node or a larger subgraph structure, such as when a group of
clients engage in money laundering schemes. Most commonly, these …

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