Every large financial institution has thousands to millions of alerts. False positives dominate and can overwhelm processing. Existing tools are often legacy rules engines + workflow, versus intelligent modern AI-based reasoning. Regulators care deeply about consistency and explainability and this is something that Thunk.AI excels at.
Related Financial Services workflows: trade exception resolution and enterprise client onboarding (KYC), part of the Financial Services suite. See how agents extract data from public sources in credit research automation.
Workflow goal
Efficiently investigate AML alerts, recommend dispositions, and produce consistent, regulator-defensible narratives with human approval.
Outputs & Metrics
Alert clearance time
Investigator throughput
SAR quality consistency
False positive reduction
End-to-End Agentic Flow
1
Alert Intake
• Ingest transaction alert + triggering rule
2
Context Assembly
• Pull customer profile, historical behavior, peer group
• Retrieve prior alerts and dispositions
3
Investigation Reasoning
• Apply typologies
• Identify inconsistencies or benign explanations
4
Disposition Recommendation
• Clear / escalate / monitor
5
Narrative Drafting
• Draft SAR / STR narrative with citations
6
Human Review & Approval
• Investigator edits, approves, or overrides
7
Learning Loop
• Feedback improves future recommendations
Platform features highlighted
Multi-system reasoning
Explainable decision chains
Human-in-the-loop controls
Regulatory-grade documentation
Control Points
Mandatory human approval
Full decision trace
Read-only access to core banking data