Module 3 forced our seniors to stop clearing every weekend-posted entry “because the tool flagged it.” We now sample clears and keep a short rationale — EQCR comments on that section dropped to zero last season.
Flagship course
Governed Ledger Review
Six live sessions on financial auditing guidance for AI-assisted ledger review governance — from tool scoping to working-paper language that survives inspection.
Learning outcomes
- Draft a model scope memo that separates automated screening from human-only judgments.
- Build an exception triage grid with risk ranks, clear-out criteria, and escalation paths.
- Write conclusion wording that cites procedure design rather than unexplained model scores.
- Archive version, threshold, and reviewer identity in a form EQCR teams recognize.
Modules
- Module 1 — Where AI may enter the ledger file Account selection, period windows, and prohibited judgment zones. Lab: mark a sample trial balance for automated vs. manual coverage.
- Module 2 — Thresholds without theater Setting materiality-linked cutoffs, seasonality allowances, and change-control for threshold edits mid-engagement.
- Module 3 — Exception queues that partners trust Ranking hits, sampling cleared items, and documenting overrides when the model is wrong but confident.
- Module 4 — Evidence language for AI-assisted review Phrasing that survives EQCR: what to cite, what to omit, and how to avoid implying the tool “audited” the account.
- Module 5 — Vendor and version discipline Evaluating updates, prompt packs, and export formats so next year’s file still reconstructs this year’s decisions.
- Module 6 — File walkthrough lab End-to-end exercise on a sanitized manufacturing ledger with planted cut-off and round-amount issues.
Instructor
Sooyeon Lim
Former senior manager in assurance with twelve busy seasons across manufacturing and retail groups in Korea. Sooyeon designs the lab ledgers and facilitates peer critique of decision logs. She does not represent any AI software vendor.
Informational pricing
Field Seat for this course is listed at ₩890,000 per person. Practice Cohort and Firm Desk options bundle additional clinics — see Pricing. No payment is processed on this website.
FAQ
Do I need a specific AI ledger product installed?
No. Labs use exported CSVs and screenshots that mimic common tool outputs. You can apply the governance patterns to whatever platform your firm selects later.
Is this a substitute for firm methodology training?
No — and that is a real limitation. We complement your methodology; we do not replace ISA training, industry CPE requirements, or your firm’s quality manual. Graduates still need local partner approval before changing file templates.
What language are sessions delivered in?
Live sessions and materials are in English. Bilingual workpaper examples (English/Korean labels) appear in Module 4 for teams filing under Korean group reporting calendars.
How large are cohorts?
Public Field Seat cohorts cap at eighteen participants so every decision log receives at least one peer critique.
Reviews from this course
★★★★☆
Strong on documentation. I wished Module 5 spent one more hour on API export quirks — our vendor’s CSV columns shifted mid-year and we had to invent a mapping sheet ourselves.