Hello NVIDIA Developer Community,
I’m sharing FinC2E, a governance-first AI system designed for AML / KYC / CDD triage, risk classification, and audit-ready reasoning, built explicitly as an advisory layer — not an autonomous enforcement system.
FinC2E was developed to address a recurring gap we see in regulated environments:
models can be accurate, but decision legitimacy, traceability, and accountability are often missing.
🔹 What FinC2E is
Human-in-the-loop AI — no autonomous blocking, freezing, or penalties
Policy-referenced reasoning — outputs include assumptions, rule context, and risk logic
Audit-ready narratives — suitable for compliance officers, committees, and regulators
Enterprise-first integration — designed to sit upstream of existing governance workflows
🔹 What FinC2E is NOT
No autonomous enforcement
No replacement of compliance officers
No black-box outcomes
Responsibility always remains with the human decision-maker.
🔹 Architecture & intent
FinC2E operates as an upstream cognitive compliance layer, focusing on:
Case triage and prioritization
Risk narrative generation
Scenario / stress-logic support (FSAP-style views)
Committee-ready summaries
The system is intentionally scoped for controlled pilots and PoC deployments, with governance rules defined before evaluation.
🔹 Current status
Public Model Card (Hugging Face)
Advisory-only, enterprise-oriented release
Ready for evaluation, feedback, and discussion
🔗 Canonical overview:
I’m particularly interested in feedback from developers and evaluators working with:
Regulated AI deployments
Governance, auditability, and explainability
NVIDIA ecosystem tooling for enterprise inference & evaluation
Looking forward to the discussion.
— Edin