As the role of financial institutions is more and more shifting towards a gatekeeper of the financial system, the regulatory pressure on these institutions to prevent money laundering is increasing. The practical implementation of this regulation can be a challenge though. Each second thousands of transactions take place and resources to check those transactions on possible money laundering are limited.

In order to assist a leading European bank on the detection of money laundering, Heights built a so-called anomaly detection model. This led to the identification of significantly more cases of money laundering, while also having more efficient compliance operations.