Transaction monıtoring

 AML transaction monitoring analyses payments and account activity to spot patterns linked to money laundering or fraud. Modern platforms support near real-time streams for urgent channels and scheduled batch jobs for the long tail, so the same policies run consistently across channels. You get timely alerts without losing the ability to run end-of-day or end-of-month controls for deeper reviews.

 Use flexible filters (transaction type, channel, timing, customer tenure) and conditional logic, then target scenarios to specific populations with pre-filters and CRM features. Test changes safely with champion–challenger runs and guardrail KPIs such as precision, recall, backlog impact and SAR yield per analyst hour. Promote only the winners, with full versioning and rollback to avoid operational risk.

 Yes. Scenario jobs can be scheduled like calendar events—hourly, daily or at close of business—so monitoring continues even when teams are offline. Once configured, runs trigger on time, produce alerts and feed downstream investigation queues without manual effort. This improves coverage and keeps day-to-day operations predictable for investigators and managers.

 Alerts land as cases with full context: related transactions, customer profile and the rule contributions that triggered the alert. Analysts follow a two-level approval path, add notes and attachments, and everything is audit-trailed. When a case meets reporting criteria, the platform generates regulator-ready SAR or FIU files, including XML where required, so submissions are consistent and traceable.

 At minimum: core transaction records, customer and account attributes, channel or device context, and scenario metadata (thresholds and parameters). Many institutions also include historical alert outcomes for calibration, plus sanctions results and adverse-media indicators to improve prioritisation. The richer the context, the better the system can distinguish routine behaviour from genuinely suspicious activity.

Risk scores, sanctions outcomes and adverse-media hits can drive monitoring intensity and thresholds for specific customers or segments. Conversely, transaction alerts and dispositions can update KYC profiles. This two-way loop creates truly risk-based monitoring and review cycles, reduces noise in low-risk populations and concentrates analyst time where the probability of true suspicious activity is highest.