AI Alert Triage for Transaction Monitoring
A triage layer that gathers context for every alert, ranks it by risk, drafts the investigation narrative and lets analysts close obvious false positives in seconds.
More than 90% of alerts were false positives, but each still needed a person to pull customer history and write a note. The backlog grew every month.
The approach.
- 01Analysed a year of closed alerts to learn which patterns were consistently benign.
- 02Assembled customer, counterparty and transaction history automatically for every alert.
- 03Ranked alerts by risk and drafted a narrative an analyst can accept or edit.
- 04Kept every disposition with an analyst and logged the AI's reasoning for examiners.
Claude summarises the alert context, compares it with similar past cases and drafts the disposition note with its reasoning, for an analyst to approve.
How we measure it.
Handling time and backlog come from the case management system. Ranking quality is checked weekly against analyst dispositions on a held-out sample.
Before you ask.
The analyst owns every note and disposition. Beyond Technologies logs what the AI saw and suggested, so the audit trail is clearer than before.
No. It works on alerts the existing rules produce. Rule tuning stays with the compliance team, informed by the patterns the triage data shows.
Want this measured on your own data? Start with a pilot.
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