Dutch challenger bank Bunq recently achieved a significant legal victory regarding the integration of artificial intelligence (AI) in anti-money laundering (AML) efforts. The Dutch Central Bank (DNB) had initially barred Bunq from employing AI and machine learning for its AML monitoring, prompting the bank to challenge this decision in court.
The court’s ruling favored Bunq, marking a pivotal moment for the bank and the industry at large. Bunq argued that the DNB’s approach to AML posed a potential “long-term detriment” to both its customers and the overall stability of the banking sector if they had complied with the traditional methods outlined by the central bank.
In their statement, Bunq criticized the DNB’s AML practices as “outdated and ineffective,” emphasizing their commitment to employing advanced technologies like AI for risk mitigation. The bank highlighted that while the DNB relied on a reporting system dependent on the integrity of account holders—placing undue trust in potential fraudsters—Bunq advocated for a more effective solution through machine learning.
Interestingly, Bunq noted that the DNB appeared to be shifting its policies even before the court’s decision, as reflected in a report calling for a more technology-driven approach to AML.
Bunq’s CEO and founder, Ali Niknam, declared, “We made history today. The court has paved the way for progress.”
The traditional manual processes associated with AML and counter-terrorism financing have been a concern for digital challenger banks, as they contribute significantly to compliance costs. This has fueled the growth of the regtech sector, where various vendors utilize AI and machine learning to enhance the efficiency of AML reporting requirements.