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.