Banks, being the pillars of every international financial system, have the duty to detect suspicious money movements related to criminal activities such as fraud, terrorism financing or money laundering, in order to protect their clients and countries from significant losses. The techniques used in the past, based on rule-based definitions, are no longer effective: the increase in digitization has not only made it easier for criminals to evade these systems but has also significantly increased the speed and the volume of transactions to be analyzed, rendering them obsolete. More reliable outlier detection systems must be built, necessarily based on the usage of big data and artificial intelligence techniques, to label suspicious transactions and provide useful insights to the final human operator, who will be responsible for conducting the necessary investigations to determine the real nature of the marked money exchange.