SANTO DOMINGO.- Doing without specialized technological systems for the prevention of money laundering and terrorist financing (ML/TF) in financial intermediation entities is practically impossible, not only because of the regulatory mandates for the formal system, but also because of the speed imposed by the operations of the sector in the current environment.
This is the view of Ramón Guzmán, vice president of the Committee for the Prevention of Money Laundering (COPLA) of the Association of Multiple Banks of the Dominican Republic (ABA), when explaining the innovations that the banking sector is implementing, including artificial intelligence, to effectively meet these challenges.
It emphasizes that the effective fight against money laundering and terrorist financing (ML/TF) begins with the ability of financial intermediaries to identify suspicious transactions. It explains that once these transactions are identified and potentially verified, risk mitigation measures prescribed by law and sector regulations can be implemented, and new typologies within these modalities can be identified.
In an article published on the ABA Blog, Guzmán asserts that technology becomes a vital ally in achieving effective prevention of money laundering and terrorist financing.
Ramón Guzmán. (EXTERNAL SOURCE).
“Especially in the times we live in, where the digitization of banking processes and the high level of interconnection allow customer funds to be available in any jurisdiction in seconds and for use in physical form (cash) or through electronic means,” he noted.
The anti-money laundering specialist explains that technology offers "invaluable" help in onboarding new clients and identifying unusual transactions or transaction patterns in terms of amounts, jurisdictions, products used, counterparties involved, among other variables that exceed human capacity to analyze them manually and in a timely manner.
Use of AI and other innovations in AML/CFT
COPLA Vice President Ramón Guzmán points out that the use of technology facilitates the analysis of alerts, through supervised machine learning algorithms, where artificial intelligence (trained by humans) tells compliance teams which alerts to focus on for more effective risk management.
It clarifies that, once reviewed, these alerts allow confirmation of whether the transactions are suspicious or, conversely, qualify them as unusual transactions for the user's profile that are duly justified.
Similarly, it states that technology allows for the design and monitoring of AML/CFT risk indicators, so that decision-makers can strategically assess risk exposure and propose appropriate control and mitigation measures.
Guzmán, who is also Vice President of Compliance at Banco Santa Cruz, points out that, for these reasons and in a proactive manner, the Dominican Republic's banking sector dedicates considerable financial and human resources each year to the acquisition, updating, and operation of its platforms that support the prevention of money laundering and the financing of terrorism.
