How External Audit Testing Evolve as Data Volumes and Risk Increase

External audits have never been simple. But they are becoming more complex every year.

Audit teams are expected to deliver high-quality assurance under tighter deadlines, increasing regulatory scrutiny, and expanding reporting requirements, from revenue recognition and lease accounting to ESG disclosures. At the same time, transaction volumes continue to grow, systems become more interconnected, and client data is spread across ERPs, documents, and spreadsheets.

Yet much of external audit testing still depends on manual, sample-based procedures.

Invoice matching. Approval checks. Recalculations. Contract reviews. Reconciliations. Journal entry testing. The fundamentals have not changed, but the scale certainly has.

The reality of External Audit testing today

Across audit engagements, teams are routinely required to verify whether:

• Expenses included in batch payments are valid, authorized, accurately recorded, and properly classified
• Accounts payable invoices were approved in line with authorization matrices and segregation of duties
• Royalty income or expense is accurately calculated based on contractual terms such as rates, tiers, territories, and time periods
• Revenue is complete, accurate, properly cut off, and correctly valued
• Accounts receivable sub-ledgers reconcile to the general ledger and supporting documentation
• Journal entries are appropriate, authorized, and free from management override
• Opening balances are consistent with prior-period audited closing balances
• New leases are fully captured, correctly classified, and accurately measured
• ESG disclosures reconcile to underlying operational data, calculations, and evidence

These procedures sit at the core of audit quality. But executing them manually often across large populations, creates tension between coverage, efficiency, and audit risk.

Why traditional sampling is under pressure

Sampling has long been an accepted audit technique. It allows auditors to draw conclusions without reviewing every transaction.

However, modern audit risks do not always behave predictably.

High-volume payment runs, automated revenue processes, complex contracts, and system-generated journal entries mean that misstatements can be isolated, systematic, or buried in unexpected places. When audits rely heavily on small samples:

• Misstatements may remain undetected until late in the engagement
• High-risk areas such as revenue and royalties receive limited coverage
• Manual testing consumes disproportionate audit hours
• Evidence becomes fragmented across spreadsheets, PDFs, and screenshots
• Audit teams face pressure during review and inspection cycles

In practice, sampling alone can reduce confidence, especially in areas regulators already view as high risk.

A shift toward broader, evidence-led audit procedures

Leading audit firms are not lowering standards. They are rethinking how audit evidence is gathered and validated.

Rather than relying exclusively on limited samples, engagement teams are increasingly exploring approaches that support broader testing, such as:

• Automated matching between payment runs, invoices, and general ledger postings
• AI-based extraction of key invoice fields across large populations
• Outlier detection to identify duplicate payments, unusual amounts, or non-standard vendors
• Expanded sample sizes without expanding manual effort
• AI-assisted interpretation of contracts to extract royalty terms
• Automated recalculation using sales or usage data
• Variance analysis between expected and recorded amounts
• Scenario testing for tiered or volume-based agreements

These approaches help auditors identify misstatements earlier, strengthen compliance with accounting standards, and improve confidence in high-risk audit areas.

What this means for audit quality and engagement teams

When audit testing becomes more systematic and data-driven, the benefits extend beyond efficiency:

• Earlier identification of potential misstatements
• Stronger audit evidence in revenue and royalty testing
• Reduced reliance on walkthrough screenshots and narrative explanations
• Clearer linkage between audit procedures and conclusions
• Improved defensibility during reviews and inspections

Most importantly, auditors spend less time assembling evidence and more time applying professional judgment where it matters most.

Excel’s continued role in External Audit

Despite advances in audit technology, Excel remains central to external audit workflows. It is where testing is performed, reconciliations are built, and conclusions are documented.

What is evolving is how repetitive audit tasks inside Excel are supported.

Some firms are beginning to explore ways to assist document matching, data extraction, recalculation, and anomaly detection directly within Excel, without changing audit methodology or removing auditor control.

How AI Agents help External Audit teams

Not as a replacement for audit judgment. Not as a black-box solution. But as a way to help audit teams scale testing, increase coverage, and strengthen assurance while continuing to work in the environment they trust.

As audit expectations rise, the future of external audit may depend less on working harder and more on modernizing how core audit procedures are executed.