
Performs periodic reviews by monitoring investor transactions and risk scores (high, medium, low) using rules and AI to detect anomalies, reduce false positives, and provide clear review justifications.
Conducts automated periodic KYC reviews by continuously monitoring investor profiles and transactional behavior. Identifies changes in risk posture based on activity trends, thresholds, and behavioral deviations.
Monitors investor transactions in real time and batch mode. Assigns risk scores (Low / Medium / High) using predefined rules and AI-driven risk models. Detects suspicious activity including unusual transaction size, frequency, geography, or counterparties.
Uses machine learning models to establish normal behavioral patterns for each investor. Flags abnormal deviations from historical patterns that may indicate AML, fraud, or sanctions risks. Continuously improves detection accuracy through feedback loops.
Combines rules-based logic with AI modeling to minimize unnecessary alerts. Prioritizes high-risk and high-confidence alerts for human review. Improves operational efficiency and reduces compliance workload.
Clearly explains why an alert was triggered and why a review is required. Provides transparent, regulator-friendly justifications for decisions. Supports audit trails and regulatory examinations.



