Expert: Nigerian Banks Need AI-native AML, Not Automated AML

Dr. Osagie Kingsley Omoruyi, Director of Innovation & Technology at Datalink Consulting Limited, has emphasized the need for Nigerian banks to adopt AI-native Anti-Money Laundering (AML) systems instead of merely relying on automated AML controls. In a statement, Omoruyi explained the implications of the Central Bank of Nigeria's (CBN) new deadlines, which mandate banks to transition from manual, batch-based AML processes to fully automated, real-time systems.

He highlighted that the CBN's move signifies an end to an era and is a critical step towards addressing money laundering effectively.

Omoruyi pointed out that Nigerian banks have historically treated AML as a reactive measure, often implemented as a nightly batch job that does not continuously monitor transactions. He emphasized that this approach is no longer sufficient in today's rapidly evolving financial landscape. To illustrate the urgency, he referenced a recent court order in Lagos, which required 71 banks and fintechs to freeze accounts suspected of holding a portion of the N1.34 billion allegedly transferred from customer accounts through the SME app of Access Bank without authorization.

Although the case remains pending and the figures are unverified, Omoruyi argued that the situation underscores the importance of prompt action in detecting and mitigating financial crimes.

According to Omoruyi, the CBN's mandate outlines three essential pillars that banks must integrate into their operations: real-time monitoring, identity integration, and leveraging biometric verification (BVN and NIN) for risk assessment. He stressed that real-time monitoring is now the foundational requirement, with screening processes integrated directly into the transaction flow rather than being executed as an overnight batch operation.

Furthermore, he stressed that identity verification should be an integral aspect of transaction decisions, utilizing BVN and NIN data to dynamically inform risk scores and enhance decision-making.

In summary, Omoruyi's insights underscore the urgent need for Nigerian banks to embrace AI-native AML systems that provide continuous, real-time monitoring, incorporate identities within the transaction process, and utilize biometric data to bolster risk assessments. This shift is crucial for effective fraud detection and prevention, especially in light of recent legal precedents highlighting the vulnerabilities of traditional AML approaches.