What it means
An audit uses two broad toolkits. Tests of controls ask whether the systems producing the numbers are working as intended, while substantive procedures go directly at the numbers themselves.
Substantive work is the one source of assurance an auditor can never dispense with entirely, which is why every audit contains some of it regardless of how good the controls look. Substantive procedures come in two forms.
Tests of detail examine individual items, such as agreeing a sample of sales invoices to bank receipts or writing to customers to confirm what they owe. Substantive analytical procedures instead build an independent expectation of a figure and investigate the difference, for example predicting rental income from floor area and rent per square metre.
Sample sizes are driven by risk and materiality rather than by any fixed percentage of the population. The more likely a misstatement and the smaller the amount that would change a reader's view, the larger the sample the auditor must test.
For the company being audited, the practical consequence is workload. A business with tidy reconciliations, clear approval trails and a well prepared audit file faces a lighter and faster audit, while one with weak controls hands over far more documents and pays a noticeably larger fee.
Finance teams who invest in preparation genuinely shorten the process. Data analytics has shifted the picture in recent years, because auditors can now test entire populations rather than samples for some balances.
Sampling still dominates in judgemental areas such as provisions, revenue cut off and asset valuations, where the question is not arithmetic but reasonableness.
In practice
Real-world examples.
Example
An auditor of a wholesale distributor sends confirmation letters to 40 customers covering 68% of the receivables balance by value. Two customers report lower balances than the ledger shows, which leads to the discovery that credit notes were being raised in the wrong period.
Example
A charity's auditor predicts payroll cost by multiplying average headcount by average salary and comparing the result to the ledger. The prediction lands within 2% of the recorded figure, so the auditor needs only a small sample of individual payslips to complete the work.
Example
A manufacturer's stock count is attended by the audit team, who test count 50 lines and trace them both ways between the physical shelves and the records. Three discrepancies in slow moving parts lead to a wider recount and a $180,000 write down.
Think of it
“Substantive testing verifies the numbers directly-checking if amounts are right.
Formula
Calculation
Monetary unit sample size = (Population value x Risk factor) / Tolerable misstatement
An auditor is testing a trade receivables balance of $12,000,000 and has set performance materiality, the tolerable misstatement for this balance, at $600,000. Expecting no errors and seeking a 95% level of assurance, the auditor uses a standard risk factor of 3.0.
Sample size = ($12,000,000 x 3.0) / $600,000 = $36,000,000 / $600,000 = 60 items. The sampling interval is $12,000,000 / 60 = $200,000, which means every single invoice above $200,000 is selected automatically and smaller invoices are picked with a probability proportional to their value. If one sampled invoice of $80,000 turned out to be worth only $60,000, the error of $80,000 - $60,000 = $20,000 represents 25% of that item, and projecting 25% across the $200,000 interval gives $200,000 x 0.25 = $50,000 of likely misstatement to weigh against the $600,000 tolerable figure.Case study
Seen in the real world.
The following is an illustrative and entirely fictional story. Pentland Marine Supplies, an invented ship chandler, had grown from one depot to six without changing its accounting routines, and reconciliations were being done twice a year at best. Its auditor concluded that controls could not be relied upon and moved to a fully substantive approach, testing far more individual transactions than in previous years.
The audit took eleven weeks rather than four, and the fee rose by roughly 60%. The testing also found $410,000 of purchase invoices recorded in the wrong period across two depots, which reduced the reported profit and delayed the filing.
Pentland's fictional finance director responded by introducing monthly reconciliations and a documented approval workflow for purchase invoices. The following year the auditor was able to rely on those controls, reduced substantive sample sizes accordingly, and the audit was completed in five weeks at close to the original fee.
Watch out
Common mistakes.
- Believing that strong internal controls remove the need for substantive testing, when some substantive work is required on every material balance regardless.
- Assuming auditors test a fixed percentage of transactions, when sample sizes follow risk and materiality and can vary hugely between balances.
- Treating a clean audit as proof that no fraud exists, when substantive testing is designed to detect material misstatement rather than to guarantee its absence.
Questions
People also ask.
What is the difference between substantive testing and a test of controls?
Substantive testing checks whether a figure is right, while a test of controls checks whether the process that produced it operates properly.
Can analytical procedures alone provide enough evidence?
For predictable, low risk balances such as rent or depreciation they often can, but judgemental areas still need tests of detail.
Why did our audit fee rise when nothing changed in the business?
Often because the auditor found controls less reliable than before and shifted the mix towards substantive testing, which is more labour intensive.
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