A groundbreaking collaboration among five prominent Dutch banks—ABN AMRO, ING, Rabobank, Triodos Bank, and de Volksbank—has emerged as a response to the staggering influx of illicit funds, estimated at approximately 16 billion euros ($17.4 billion) annually, coursing through the Netherlands’ banking system. Launched in July 2020, this innovative initiative seeks to shed light on patterns of potential money laundering activities within the business banking accounts of these five institutions, which collectively command around 77 percent of the Netherlands’ banking market.
The impetus behind this pioneering effort stemmed from a fundamental question: could a unified approach offer more effective means of monitoring transactions across all these banking platforms? Out of this query, the collaborative venture "Transactie Monitoring Nederland" (TMNL) was born. Over the ensuing three years, TMNL has refined its anti-money laundering (AML) tools, harnessing the power of cutting-edge technologies.
TMNL's modus operandi involves acquiring encrypted and pseudonymized transaction data from the participating banks. The organization then employs artificial intelligence and machine learning tools to meticulously scrutinize the data for aberrant patterns that may signal money laundering activities. These models are devised in consultation with the AML teams of the five banks, and they align with the Netherlands’ national AML priorities.
Once these models are developed, TMNL initiates testing. Upon receiving approval from the organization’s model board and user council, the models are employed for joint monitoring, leading to the generation of AML alerts. These alerts are subsequently transmitted to the banks for a comprehensive review process.
In this collaborative endeavor, the AML experts from each bank undertake the responsibility of assessing the alerts and offering insights into the efficacy of the models and the alerts they generate. Beyond this, the banks can leverage the information derived from TMNL’s alerts, in conjunction with their own transaction data, to prepare and file reports highlighting suspicious activity with the Financial Intelligence Unit Netherlands.
Norbert Siegers, the CEO of TMNL and a former IT lead for commercial banking at ABN AMRO, underscores the overarching objective: to produce signals of money laundering activity that individual banks might have overlooked. He elaborates that the aspiration is for these signals to be "30-50 percent useful to the banks."
Nonetheless, it’s important to note that there are certain constraints related to the data analyzed by TMNL. Presently, the data doesn't encompass individual banking transactions; instead, it is limited to transactions involving business entities. However, Siegers notes that evolving legislation within the Netherlands and the broader European Union aims to encompass individual banking transactions within TMNL’s models. Yet, this expansion remains subject to ongoing political discussions, as privacy concerns take center stage.
Looking toward the future, TMNL envisions the incorporation of individual banking transactions into its models and aims to extend its transaction monitoring activities on behalf of the participating banks. With over 100 banks in the Netherlands, many of them relatively small, Siegers envisions expanding the collaboration to include a wider array of Dutch banks. Furthermore, he proposes the potential replication of TMNL's model by banks in other nations, with countries like Austria, Italy, and Denmark already expressing interest in understanding its operational framework.
The initiative has garnered support from the Nederlandse Vereniging van Banken (Dutch Banking Association), which views TMNL's progress positively. The association sees the potential for such collaborative efforts to have a transformative impact on the fight against money laundering.
While TMNL's alerts have not directly contributed to specific law enforcement investigations into money laundering, the initiative underscores the power of collective action in combating financial crime. The collaborative model it employs offers a potential blueprint for global initiatives of a similar nature, potentially reshaping the landscape of anti-money laundering efforts well beyond the Netherlands.
By fLEXI tEAM