TL;DR

Screen 100% of the general ledger using configurable risk criteria and simple AI checks - no more ad-hoc filters. Turn PBC requests into digitally sealed evidence packets linked to each item; measure impact with three numbers: review time per 1k rows, first-pass closure rate, and rework %.

Why move beyond spreadsheets (without a big overhaul)?

Spreadsheets are great for templates and quick checks-but during audit season, work scatters: formulas differ from file to file, evidence hides in email threads, and reviewers spend time stitching context. Finspectors.ai adds one organized layer: screen the full population, show clear reasons for every item, and package evidence so anyone can re-perform the work quickly.

What Finspectors adds (no rip-and-replace)

1. Triage first, not sample first. Every entry is screened against your risk criteria (e.g., duplicates, cut-off risk, big round numbers, unusual narration) plus automated checks. Reviewers jump straight to the riskiest slices.

1. Reasons you can trust. Each flag comes with a short, plain-English “why this was flagged,” and a quick way to repeat the check.

1. Evidence that holds up. Requests → uploads → verification become one flow; each exception gets a digitally sealed packet (think: a tamper-evident bundle with a timestamp).

1. One audit-ready trail. Approvals, threshold changes, and notes live in a single place, making EQCR and peer review faster.

Migration blueprint (run these 4 tracks in parallel)

1) Data & Inputs Agree the GL export format (column names, data types, date formats) and your evidence request list. Add a quick pre-load check so bad files are caught early - not during review.

2) Screening & Triage Set up your risk criteria and start with conservative thresholds. Make “reason for flag” human-readable. Keep a simple change log when thresholds move.

3) Evidence & Packetization Convert PBC to in-product requests. Use a clear naming pattern, include a quick checklist (support, tie-back, reviewer note), and digitally seal each packet. Export packets back into your binder structure.

4) Review & Governance Write down what “done” means for reviewers (reason understandable, packet complete, tie-back repeatable). Share short extracts of the activity log (who/what/when) so re-performance is straightforward.

What to track (agree this up front)

1. Review time per 1k rows: Aim for 25 - 40% faster than your current baseline.

1. First-pass closure rate: Aim for +15 - 30% (fewer loops).

1. Rework rate: Aim for 20 - 30% lower.

1. Trail completeness: Packets sealed; rule/threshold versions recorded.

Risks & simple fixes

- Key point: GL format drifts from file to file

Set a data contract + quick pre-load check.

Too many flags at the start

Begin conservatively; adjust with a visible change log.

Reviewer skepticism

Every flag shows a clear risk-criterion reason + how to re-check it.

Evidence chaos

Use a standard packet template and seal each packet.

Tool sprawl worries

Keep planning/forms in your suite; use Finspectors only for triage + packets; export back to binders.