Smart Neural AI
Financial auditing guidance for teams that let models surface ledger exceptions — then govern every acceptance, override, and working-paper note.
How engagements change
Three habits that keep AI review defensible
Scope the model before it runs
Define which accounts, periods, and risk hypotheses the tool may touch — and which judgments stay human-only.
Triage exceptions with rationale
Rank outliers by engagement risk, record why a hit was cleared, and stop treating raw scores as evidence.
Archive governance, not screenshots
Capture prompt versions, thresholds, reviewer identity, and conclusion wording that EQCR reviewers recognize.
Field focus
Built for Korea-based assurance work
Instruction assumes bilingual workpapers, group reporting calendars, and the documentation density Korean firms expect when tools assist substantive testing.
Programs
Courses for ledger review with machine assistance
Each path pairs model oversight with the documentation partners expect when AI touches the general ledger.
Governed Ledger Review
Flagship program on scoping AI tools, exception governance, and evidence language for AI-assisted review.
Exception Triage Studio
Short clinic on ranking model hits, clearing seasonality noise, and writing clear-out notes.
Model Oversight for Leads
For managers who approve tool selection, threshold changes, and file sign-off under time pressure.
“After Governed Ledger Review, our team stopped pasting model scores into workpapers. We now keep a decision log for every cleared exception — partners finally stopped asking what the tool ‘meant.’”— Hyejin Cho, audit manager, Seoul-based mid-tier firm
Ready to govern the next review cycle?
Compare seating options or write to the Yecheon-gun desk with your engagement calendar.