Community-Level Anomaly Detection for Anti-Money Laundering. (arXiv:1910.11313v1 [cs.LG] CROSS LISTED)

Anomaly detection in networks often boils down to identifying an underlying
graph structure on which the abnormal occurrence rests on. Financial fraud
schemes are one such example, where more or less intricate schemes are employed
in order to elude transaction security protocols. We investigate the problem of
learning graph structure representations using adaptations of dictionary
learning aimed at encoding connectivity patterns. In particular, we adapt
dictionary learning strategies to the specificity of network topologies and
propose new methods that impose …

anomaly detection community detection laundering lg money money laundering