AI-Assisted Cross-Border FinCrime Analyst Review
BeaconGuard is engineered for high-risk, human-reviewed workflows where AI output may assist a regulated decision path, while policy control remains deterministic and reviewable.
Workflow Context
In this workflow, AI can assist analysis for cross-border AML and fraud review, but no model inference proceeds without BeaconGuard approval and preserved decision evidence.
The Enforcement Sequence
- Application Input: The financial or analyst application submits a cross-border case for AI-assisted summarization or recommendation.
- Gateway Intake: BeaconGuard intercepts the payload.
- Trust & Replay Validation: The payload is cryptographically validated and checked for replay. Deny path is executed if invalid.
- Deterministic Policy Evaluation: The request is checked against governed policy constraints for required AML, KYC, or workflow evidence. Deny path is executed if incomplete or out of bounds.
- Control Outcome: BeaconGuard returns an explicit control outcome after deterministic policy enforcement.
- Decision Evidence: A structured JSON decision record is retained for architecture review and security inspection.
High level component boundaries and trust domains in the control architecture
Decision Evidence
The workflow emits structured enforcement records only after BeaconGuard has decided allow or deny. Reviewers inspect the decision signal, enforcement fields, trust validation, and evidence hashes to determine exactly what control path executed.