Fraud investigation assistant
Fraud analysts spend 60 to 80 percent of case time on evidence-gathering across systems, before the analysis even starts. Backlogs build; the good cases wait.
An AI agent gathers case evidence across your core systems, builds a narrative, links the activity to policy and flags anomalies for the analyst to investigate.
- 01
When a case is opened, the agent pulls transaction history, KYC data, device telemetry and linked parties.
- 02
It builds a case narrative in the format your investigators already use.
- 03
Policy links are inserted where the activity matches known typologies.
- 04
Anomalies outside the typology library are flagged with their own evidence for the analyst.
- 05
The analyst's decision is captured as structured feedback so the agent gets better case after case.
with two to three times the analyst throughput.
Ranges drawn from production deployments and public enterprise benchmarks. For a specific rupee or dollar figure tailored to your volume, use the calculator below.
Prerequisites for a clean deployment.
- Integrations with core banking, KYC, transaction and device-telemetry systems
- An approved typology library and policy references
- A case management system with feedback capture
- Senior investigator oversight for model updates
Put your own numbers on it.
“At 200 briefs a month and a loaded monthly cost of ₹1,50,000 per person, fraud investigation assistant would typically save ₹3.8 L to ₹5.6 L a year.”
Range uses this use case’s typical automation rate (40 to 60 percent) against the baseline time per task for research work, with your cost per person converted at 160 working hours a month.
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