The compliance industry agonizes over the consequences of following up on what turn out to be time-consuming false positives, resulting in significant and unnecessary costs, but the real problem is the false negatives that you miss due to the inability of your rules-based software to identify potential problems early on, so that you, as gatekeeper, can bar them from entry in the beginning, before they have an opportunity to push the proceeds of crime through your bank with impunity.
While false positives command the attention of compliance officers, as they must each be checked and ruled out, false negatives do not result in entries or results, and are generally overlooked, as they slip through the flaws in your system, which cannot and does not adapt to the evolving strategies and tactics of money launderers and financial criminals. I know, from a decade of personal experience as a laundryman, that the dynamic nature of that dark "profession," where one is constantly moving into new typologies totally unknown to traditional AML platforms, that success in the placement of illicit profits is the result, in beating legacy systems that cannot adapt in real-time. They are, by their very rules-based nature, obsolete for stopping money laundering.
Remember this, because I was once a participant: money launderers stay up night and weekends, to brainstorm their way into new methods, which traditional systems, stuck in what is now money laundering history, do not respond to, because their limited nature prevents them from understanding new, and to them, opaque data. That is how they consistently beat you, day after day.
It gets worse; Any increased focus by your traditional rules-based program, in an effort to keep up with innovative and responsive money launderers, often results in still more false positives, a vicious cycle of more time wasted, and you still have not identified and interdicted the money launderers, just wasted more precious compliance research time. The laundrymen know exactly what the limitations of your software are, and artfully evade detection, because your programs cannot connect the dots in a new ballgame that's changing regularly. The name of the game is being unpredictable and opaque.
Given the increased demands of regulatory agencies, which now require effective AML compliance, the threat of civil penalties, negative press, and even potential criminal charges or deferred prosecution agreements, causes management to fear compliance failure; the buck stops with you.
The solution is to employ machine learning, operating in a platform powered by Artificial Intelligence, which will make sense of seemingly disconnected connections and relationships, and more importantly, will adapt and learn, cobbling together disconnected and confusing data, and drawing conclusions useful to the user. Unless the system you are using can analyze disjointed data, and draw usable conclusions, you will never be able to identify the crafty money launderers who have been successfully targeting your bank.
The laundrymen will continue to fool your systems, until and unless you move forward into AI and machine learning platforms in 2023.