Predicting Money Laundering Sanctions Using Machine Learning Algorithms

This article predicts the likelihood of a country being sanctioned by Basel for not adhering to anti-money laundering (AML) standards. Multiple machine learning algorithms were used to identify the strongest risk predictors, resulting in Basel sanctions against a country. In terms of sanction prediction, the random forest classifiers outperformed the stand-alone classifiers. AML classification algorithms can aid in the prediction of AML risks. The top three predictors of sanctions are money laundering and terrorist financing, political and legal risks, and public transparency and accountability