Case studies
Financial Services
Financial Services – B2B Payments Fintech: Fraud & Merchant Monitoring AI
Timeline: Build: 13 weeks. Deploy: shadow mode first. Optimization: continuous graph features.
Business overview
Industry: payments/fintech. Complexity: AML/BSA obligations.
Common pain points
Alert fatigue, slow investigations, inconsistent SAR quality.
Full AI automation system (PrimeAxiom solution)
Graph Agent, Case Brief Agent, Evidence Agent, SAR Draft Agent.
Automation workflow (detailed system flow)
1. Transaction stream. 2. AI scores risk clusters. 3. Cases instantiated. 4. Analyst reviews brief. 5. SAR draft generated. 6. Compliance attests. 7. Feedback improves graph.
AI agents & logic
Detection Agent, Narrative Agent, Export Agent.
Technical architecture
Real-time + batch, enterprise LLM with PII controls, immutable case logs.
Tools & integrations
Snowflake, case management, PostgreSQL, OpenAI, graph DB
Results
Alert precision +37%; analyst cases/day +2.1x; time-to-SAR −58%; fraud loss rate −24%.
Timeline
Build: 13 weeks. Deploy: shadow mode first. Optimization: continuous graph features.