FinC2E — Financial Cognitive Compliance Engine

Governance-First AI for AML/KYC & Audit-Ready Decision Support (Human-in-the-Loop)

FinC2E is a governance-first AI advisory system designed for regulated, high-stakes environments where decision legitimacy, traceability, and accountability are more critical than automation or speed.

FinC2E is developed under BPM RED Academy — HumAI MightHub as a controlled, enterprise-grade cognitive layer supporting human decision-makers in compliance, risk, and audit workflows.

Core positioning (non-negotiable)

Advisory-only AI — Human-in-the-Loop by design
No autonomous enforcement
No replacement of compliance officers
No black-box decisions
Responsibility always remains with the human decision-maker

FinC2E is intentionally not an autonomous compliance system.

What FinC2E does

FinC2E supports regulated teams by generating structured, reviewable reasoning, not decisions.

Primary capabilities include:

Case triage & prioritization support
Risk-oriented reasoning signals for human review
Policy-referenced reasoning
Outputs explicitly reference assumptions, rule context, and logic paths
Audit-ready narratives
Structured explanations suitable for auditors, regulators, and committees
Scenario & stress-logic support
FSAP-style views and counterfactual reasoning
Committee-ready summaries
Clear, human-readable briefs for decision boards

What FinC2E is NOT

Not an automated blocking or freezing system
Not a penalty or enforcement engine
Not a legal authority or regulator
Not a “push-button compliance” product

FinC2E does not take actions.
It supports human judgment under governance constraints.

Intended users

FinC2E is designed for:

Banks and financial institutions (AML / KYC / CDD teams)
RegTech providers
Audit and compliance consultancies
Institutional risk and compliance committees
Government, FIU, and sovereign deployments (controlled and policy-bound)

It is not intended for consumer or retail use.

Governance & design principles

FinC2E is built around the following principles:

Human accountability first
Traceable reasoning over opaque accuracy
Policy alignment before model optimization
Auditability as a core requirement, not an add-on
Controlled deployment over unrestricted access

These principles define both system behavior and engagement models.

Commercial & Institutional Use (Licensing)

FinC2E is available for commercial, institutional, and governmental use under a separate license.

Commercial licensing is required for any:

production use,
institutional deployment,
internal corporate use beyond evaluation,
integration into paid products or services.

Institutional pricing

Early Governance Adoption Window (50%)

As part of an early institutional governance onboarding window, FinC2E is currently offered under special terms:

New Year Governance Adoption Offer — valid until January 2nd, 2026

These terms are intended for organizations preparing for stricter AI governance, audit, and accountability requirements in 2026.

Current onboarding terms (50%):

Evaluation PoC (controlled scope): €75,000
(standard institutional price: €150,000)
Institutional Pilot (policy-bound, audited, monitored): €300,000
(standard institutional price: €600,000)
Annual Enterprise License: from €750,000
(standard institutional price: from €1,500,000)

Final pricing depends on:

jurisdiction and regulatory context,
deployment model (on-prem / sovereign cloud / controlled environment),
governance depth and audit requirements.

Contact for licensing and institutional engagement

Website: https://www.bpm.ba/FinC2E
Email: [email protected]
Suggested subject: “FinC2E — Governance Licensing / Institutional Pilot”

Deployment models (commercial)

FinC2E may be deployed under controlled conditions via:

Evaluation PoC — limited scope, non-production
Institutional pilot — policy-defined, monitored, auditable
On-prem / sovereign cloud deployments — where required by regulation

Note: Any “Deploy” or hosting options shown by platform interfaces (e.g. Hugging Face Spaces or inference tooling) refer to technical serving mechanisms only.
Commercial deployment of FinC2E is governed exclusively through licensing and contractual engagement.

Evaluation context & ecosystem alignment

FinC2E has been developed, iterated, and evaluated within the NVIDIA ecosystem, using enterprise-grade tooling aligned with regulated AI deployment standards.

Across a three-month evaluation period, the system demonstrated consistent exponential growth in evaluator engagement and institutional interest, driven by:

governance-first positioning,
human-in-the-loop design,
audit-ready reasoning outputs.

Evaluation focused on:

decision traceability and narrative integrity,
stability of policy-referenced reasoning,
suitability for high-stakes, regulated environments.

This evaluation phase informed the system’s current commercial and institutional readiness.

Evaluation notes (for serious evaluators)

Recommended evaluation criteria:

Auditability of reasoning paths
Preservation of human accountability
Policy alignment and explainability
Integration with committee and case-management workflows
Reproducibility under controlled inference conditions

Feedback is welcomed from teams working in:

regulated AI deployments,
governance, audit, and explainability,
enterprise inference and evaluation tooling.

Canonical reference

FinC2E — Financial Cognitive Compliance Engine
Governance-first AI for AML/KYC, risk classification, and audit-ready reasoning.
Advisory-only. Human-in-the-Loop.

Legal & compliance disclaimer

FinC2E provides decision support only and does not constitute legal advice.
All final decisions remain with qualified human reviewers and accountable officers.

— Edin

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