Case study
Real-time fraud detection that pays for itself in a quarter.
We replaced a rules-only engine with an agentic fraud and AML platform — cutting losses 40% while shrinking false positives.
A top-25 national bank was losing ground to faster, AI-driven fraud while a brittle rules engine drowned analysts in false positives. We deployed a real-time scoring platform: streaming transaction features, agentic case triage, and explainable model decisions wired into their existing core. Analysts now see ranked, evidence-backed alerts instead of raw rule hits.
What we deliver
- Real-time transaction scoring at sub-100ms latency
- Agentic case triage that drafts the analyst's first pass
- Explainable decisions for every flagged transaction
- AML transaction monitoring aligned to regulator expectations
Outcomes
Lower losses
Net fraud losses fell 40% within two quarters of go-live.
Fewer false alarms
False positives dropped by more than half, freeing analyst capacity.
Faster triage
Average case handling time dropped from minutes to seconds.
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