AI agents on the DaasLabs Data Fabric Framework do the work end to end across wealth, investment banking, correspondent banking, cards & payments, retail, corporate banking and trade finance. Policy decides what goes straight through, and people approve the exceptions.
| Agent | Case | Status | Confidence | Summary | When |
|---|---|---|---|---|---|
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Each agent plans, calls tools on governed data and drafts an outcome with its evidence.
Confidence, amount limits and autonomy level decide straight-through or human approval.
A named owner reviews, edits or rejects: only the cases that need judgement.
Every step, tool call and decision is kept as an audit trail. See governance →
Every agent has a named human owner, an autonomy level set by governance, a tool list it is allowed to use and a stated line it never crosses without a person. Metrics cover the last 7 days.
Reported results from vendors and banks; independent verification varies. Figures link to their source.
Reported cut in reconciliation task time from AI agents; break investigation more than 73% faster (reported 30 Sep 2026).
comparethecloud.net ↗Reported faster client onboarding in tests with AI agents for trade accounting, reconciliation and onboarding/KYC, with human oversight.
Business press, Feb 2026Reported "digital employees" with their own system access; 20,000 staff building agents on an internal platform.
axios.com ↗Agents one practitioner can supervise in financial-crime agent squads; productivity gains of 200–2,000%.
mckinsey.com ↗Reported fewer false alerts at one large retail bank; another global bank reported 2–4x more true positives.
ibm.com ↗