Accounting & Financial Services

LedgerLens: Accounting QA Automation

28 Hours Back Per Close: How a NZ Accounting Firm Automated Month-End QA

LedgerLens: Accounting QA Automation
67%
Faster Reviews
for monthly transaction checks
41%
Fewer Rework Cycles
after first-pass QA
96%
Anomaly Recall
trained on your firm's historical exception patterns, improving over time
28
Hours Saved
per close cycle

The Problem

Manual transaction review created bottlenecks and inconsistency across accountants.

High-Volume Line Items

Reviewers were manually checking 4,000+ line items per close cycle. At that volume, edge cases were inevitable and regularly surfaced too late to fix without a deadline scramble.

Inconsistent Exception Handling

Each reviewer handled exceptions differently, so identical transactions often received different treatment and required partner rechecks before sign-off.

Late Discovery of Errors

Misclassifications and posting errors were often discovered in the final days of close, triggering late nights and avoidable back-and-forth with clients.

Limited Audit Traceability

Review notes lived across spreadsheets, emails, and ledger comments, making audit prep slower and partner review harder to defend.

Our AI-Powered Solution

LedgerLens combines deterministic accounting rules with AI reasoning to surface risky transactions early.

Automated Rule Engine

Applies chart-of-account, tax code, and period-specific checks before human review starts.

Reduced repetitive checklist work across the team

Anomaly Detection Layer

Flags unusual patterns by amount, vendor, description, and posting behaviour.

Prioritised high-risk entries first

Reviewer Workbench

Presents grouped exceptions with suggested resolutions and evidence.

Faster decision-making with less context switching

Audit Trail Export

Captures every flag, decision, and correction for partner and audit review.

Improved compliance readiness

Firm-Level Templates

Reusable policy templates for AU/NZ accounting workflows and engagement types.

Standardised quality across client portfolios

Close Process Improvements

After rollout, the firm reported:

67%

Review Time Reduction

Month-end checks completed significantly faster

41%

Less Rework

More issues caught correctly during first pass

96%

Anomaly Recall

High capture rate on previously observed error types

28 hours

Saved Per Close

Freed senior staff for advisory work

We now start each close with a clean exception list instead of digging through ledgers manually. LedgerLens made our QA process far more predictable.

Director, Business Services
Accounting Practice, New Zealand

Ready to Transform Your Operations?

Running a practice where month-end still means late nights? Let's fix that.