Event-Driven AI for Real-Time Sanctions Screening
Keywords:
Sanctions compliance, regulatory technologies, event-driven architecture, AI architecture design, machine learning governance, cloud-native platforms, cloud-native compliance solutions, data inspection, privacy, and sensitivity management, observability and monitoring, streaming data processing, model production, operation, and supervision, rule management, risk-based thresholds, and human oversight.Abstract
A crucial task in financial crime compliance is sanctions screening, which involves determining whether organizations or individuals should be restricted from engaging in business relationships with a financial institution or the institution’s customers. The evolving geopolitical landscape has led to increasingly extensive and dynamic sanctions lists. Regulatory scrutiny on the adequacy of screening controls has heightened, with realtime detection of potential matches emerging as the next frontier for more forward-thinking institutions. A monitoring-based industry guidance paper jointly published by the Basel Committee and Financial Action Task Force calls for greater use of artificial intelligence in sanctions compliance.
Despite this opportunity, a current shortcoming is that matching against sanctions lists continues to be predominantly based on batch processing, involving either screening transactions against sanctions list prior to pass through the bank, or screening customers’ information against sanctions list prior to onboarding or at defined refresh frequency. Suitable event-driven architectural patterns and cloud-native platforms can help financial institutions close this gap.
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