Fighting Money-Laundering with Statistics and Machine Learning: An Introduction and Review. (arXiv:2201.04207v1 [stat.ML])

Money laundering is a profound, global problem. Nonetheless, there is little
statistical and machine learning research on the topic. In this paper, we focus
on anti-money laundering in banks. To help organize existing research in the
field, we propose a unifying terminology and provide a review of the
literature. This is structured around two central tasks: (i) client risk
profiling and (ii) suspicious behavior flagging. We find that client risk
profiling is characterized by diagnostics, i.e., efforts to find and …

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