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Microlesson · 5-min read

Steps When Using Analytical Procedure as a Substantive Test

## Using Analytical Procedures as a Substantive Test — Four-Step Process

When the auditor chooses to rely on AP as a substantive procedure (not merely for risk assessment), SA 520 requires four specific steps:

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### Step 1 — Determine Suitability of the Specific AP

AP is more suitable when:

  • There is a large volume of predictable transactions (e.g., utility expense, payroll).
  • A stable relationship among data elements is expected to continue in the absence of known contrary conditions.

Suitability depends on:

  • Auditor's assessment of the likelihood of detecting material misstatement through that procedure.
  • The nature of the assertion being tested (e.g., completeness vs. existence).

> Note: In some cases, even an unsophisticated predictive model can be highly effective.

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### Step 2 — Evaluate Reliability of Data (Mnemonic: SCNC)

Before using data to form an expectation, the auditor evaluates:

FactorDetail
(S) SourceExternal sources are more reliable than internal sources
(C) ComparabilityIndustry comparisons must be relevant (same industry, size, geography)
(N) Nature & RelevanceData must be pertinent to the account/assertion being tested
(C) ControlWhether budget figures reflect expected outcomes vs. aspirational targets; controls over preparation of data

> Auditor may test the operating effectiveness of the entity's controls over information preparation to justify relying on internally prepared data.

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### Step 3 — Develop a Sufficiently Precise Expectation

  • The auditor must develop an expected amount or ratio from the reliable data.
  • The expectation must be precise enough that any material misstatement would create a detectable difference between expected and recorded amounts.
  • If the precision band is too wide, the procedure will not catch a material error.

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### Step 4 — Determine Acceptable Difference (Threshold)

  • Set the maximum difference between Expected Amount and Recorded Amount that can be accepted without further investigation.
  • Any difference exceeding this threshold must be investigated.

> Key formula: `Unexplained Difference = Expected Amount − Recorded Amount`

> If |Unexplained Difference| > Threshold → Investigate further.

Worked example

### Example 1

Step 1 — Suitability check: The auditor wants to use SAP to test rental income. The entity has 200 identical units, all rented at market rate. The relationship (units × rent × occupancy) is stable and predictable → SAP is suitable. Contrast: Testing a one-off insurance settlement — highly non-routine and unpredictable → SAP not suitable.

### Example 2

Step 2 — Reliability of data: The auditor uses industry average cost-to-revenue ratio (external data) to benchmark the client's cost structure. External data is more reliable than the client's own budget. However, the auditor also checks that the industry data is comparable (same sub-sector, similar scale).

### Example 3

Step 3 — Precision of expectation: The auditor computes expected interest expense = average loan balance × weighted average interest rate = ₹5 Cr × 8% = ₹40 lakh. This expectation is precise because both inputs are objectively verifiable. Recorded interest = ₹38 lakh → difference = ₹2 lakh → within materiality threshold → no further work needed.

### Example 4

Step 4 — Threshold breach: Expected commission = ₹1.5 Cr; Recorded commission = ₹2.3 Cr; Acceptable threshold (set at 5% of expected = ₹7.5 lakh). Unexplained difference = ₹80 lakh >> ₹7.5 lakh threshold → auditor must obtain explanations and additional corroborating evidence.

### Example 5

Budget reliability pitfall: The client's budget was set as a 'stretch target' (aspirational goal), not as a realistic forecast. Using this budget to form an AP expectation would be unreliable — the auditor should use independently derived expectations instead.

⚠️ Common exam mistakes

  • Skipping Step 2 (reliability check) and blindly using management-prepared data — budget figures aimed at motivating staff (goals) are very different from realistic forecasts and should not be used as AP benchmarks.
  • Setting an excessively wide acceptable-difference threshold in Step 4, which effectively renders the AP unable to detect any material misstatement.
  • Forming a vague expectation in Step 3 (e.g., 'revenue should be similar to last year') without a precise numerical prediction — this fails the 'sufficiently precise' requirement.
  • Confusing the suitability of SAP with its execution — even if SAP is suitable (Step 1), it can still fail if the underlying data is unreliable (Step 2) or the expectation is imprecise (Step 3).
Reference: SA 520 — Paragraphs 5(b) and A15–A21 — SA 520 — Analytical Procedures (ICAI)
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