Certification

FDE-Finance certification for financial AI deployment capability

The certification page explains what is assessed: financial scenario understanding, AI tool deployment, knowledge-base configuration, agent workflow design, security boundaries, and delivery acceptance.

Capability assessment
Verifiable records
No external endorsement claim
Assessment Scope

What FDE-Finance focuses on

Train specialists who can understand financial scenarios, deploy AI tools, build knowledge bases, design agent workflows, and deliver enterprise work.

Financial scenarios

Understands research, compliance, KYC/AML, family office, RWA, IR, and managed operations.

Knowledge-base work

Can organize documents, retrieval boundaries, citations, permission tiers, and update routines.

Risk boundaries

Keeps licensed judgement, legal review, compliance accountability, and internal approvals with humans.

Certification Flow

A transparent path from training to verification

The MVP keeps the verification API and page ready for certificate lookup without fabricating any issued records.

01

Training

FDE Financial AI Bootcamp

02

Scenario work

Diagnosis, knowledge base, workflow, governance

03

Assessment

Evidence review and practical acceptance

04

Verification

Lookup through a certificate identifier

Verification API

Ready for certificate lookup when real records exist

The API returns a conservative not-found response unless a verifiable record is added. This prevents fake credential claims.

Lookup endpoint

/api/certifications/verify

No fake records

Until issuance records are explicitly provided, the site presents certification as a path and capability framework, not as proof of existing certified people.

Enterprise Procurement Route

Start with non-sensitive context, then move into an accepted AI deployment route

FDE.HK connects intake, diagnosis, solution design, delivery, and managed operations into one enterprise buying path for business, technology, compliance, and management teams.

Non-sensitive first
Sensitive materials wait until NDA, permission, and data boundaries are confirmed
Diagnose before build
Clarify scenarios, users, data, budget, and acceptance criteria first
Accepted delivery
Plans, workflows, training, operations, and acceptance checklists stay traceable