Structural entropy minimization combining graph representation for money laundering identification
Shaojiang Wang,
Pengcheng Wang,
Bin Wu
et al.
Abstract:Money laundering identification (MLI) is a challenging task for financial AI research and application due to its massive transaction volume, label sparseness, and label bias. Most of the existing MLI methods focus on individual-level abnormal behavior while neglecting the community factor that money laundering is a collaborative group crime. Furthermore, the massive volume of transactions and the issue of label shifting also impede the application of supervised or semi-supervised models. To this end, this pape… Show more
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