Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs. (arXiv:2112.07508v3 [cs.LG] UPDATED)

Web: http://arxiv.org/abs/2112.07508

Money laundering is a global problem that concerns legitimizing proceeds from
serious felonies (1.7-4 trillion euros annually) such as drug dealing, human
trafficking, or corruption. The anti-money laundering systems deployed by
financial institutions typically comprise rules aligned with regulatory
frameworks. Human investigators review the alerts and report suspicious cases.
Such systems suffer from high false-positive rates, undermining their
effectiveness and resulting in high operational costs. We propose a machine
learning triage model, which complements the rule-based system and learns to …

arxiv graphs learning lg machine machine learning money optimization