Accounting Process Mapping for Agentic Systems
Map the accounting pipeline an automated system runs — from source transactions through recognition to financial statements — and write the multi-entity rules it applies down to authority: cited, effective-dated, and provably findable by the system that must apply them.
Issued by National Center for Secure AI Education · Valid for 2 years
What it covers
- The automated accounting pipeline: ingestion → recognition → statements → tax mapping → forms
- Process mapping in BPMN 2.0 — swimlanes, gateways, events, and trust boundaries
- Transaction ingestion and completeness across bank, card, brokerage, and manual sources
- Multi-entity attribution: which entity a transaction belongs to, and why
- Shared costs, management fees, allocations, and intercompany transactions as related-party arrangements
- Transaction categorization against a chart of accounts
- Recognition treatment as explicit, testable rules — R&D capitalization, stock compensation, revenue recognition, investment income
- Authoring a rule corpus for retrieval: citation, authority hierarchy, chunking, effective dates
- Proving a rule is findable: adversarial retrieval against a corpus you wrote, and the worked example that shows the treatment is right
- Trial balance to financial statements, per entity and consolidated — and why statements are derived, never configured
How it is earned
Earned by completing all required modules of the Accounting Process Mapping for Agentic Systems course and passing review of the capstone: a contribution to a live automated accounting pipeline build. For an assigned stage of that pipeline the holder delivers the discovery memo and its source list; the BPMN 2.0 stage model with its actors, trust boundaries, control points, and audit-trail requirements; the attribution, categorization, and recognition decision-rule table for the stage, marking every rule that depends on a fact the transaction does not carry; a rule corpus contribution authored to standard — cited to authority, chunked, ordered by authority hierarchy, and effective-dated — with the adversarial retrieval log showing that each rule is returned for the transactions it governs and that the treatment it produces is correct on a worked example; and, where the assigned stage produces them, the statement-generation specification from trial balance to entity and consolidated statements. Review is by the instructor, with partner engineering input on whether the specification is precise enough to build from and the rule corpus sound enough to apply.
The credential you receive
Earn this certification and National Center for Secure AI Education issues you a credential: a signed Open Badges 3.0 record with its own page, and the printable sheet below. The specimen shows the layout with a sample holder — a real credential carries the holder's name, its issue date and a verification link anyone can check.
Specimen — not an issued credential. Machine-readable Open Badges achievement