AS 2305 Requirements for Substantive Analytical Procedures

Substantive analytical procedures are a technique in public company audits allowing auditors to evaluate financial information by studying plausible relationships among both financial and non-financial data. These procedures are governed by standards from the Public Company Accounting Oversight Board (PCAOB) that guide how auditors plan, perform, and document their work. The effectiveness of this approach hinges on data predictability and the auditor’s ability to develop a precise expectation to compare against company records.

While this article outlines the requirements of AS 2305, the PCAOB proposed a new standard in mid-2024 to replace it. The proposal aims to enhance auditor responsibilities, focusing on the precision of expectations and the investigation of significant differences.

The Auditor’s Objective with Analytical Procedures

Substantive analytical procedures are a type of audit test used to obtain evidence about the accuracy of account balances or classes of transactions. They involve making comparisons between a company’s recorded financial data and an expectation developed by the auditor. The objective, as outlined in PCAOB Auditing Standard (AS) 2305, is to obtain relevant and reliable audit evidence regarding specific financial statement assertions. These assertions are management’s claims about the numbers on the financial statements, such as completeness or valuation.

These procedures are distinct from “tests of details,” which involve examining individual transactions or items that make up an account balance. While a test of details might involve examining a sample of sales transactions, a substantive analytical procedure evaluates the reasonableness of the total revenue figure. For example, an auditor might use data on a retailer’s average sales per square foot and the total square footage of its stores to develop an independent expectation for total revenue.

The decision to use analytical procedures depends on the auditor’s professional judgment about their effectiveness. Their use is most appropriate when the relationships within the data are stable and predictable. For instance, income statement accounts, like salary expense, tend to be more predictable over time than balance sheet accounts. The reliability of the underlying data used to form the expectation is also a factor in whether the procedure can provide persuasive audit evidence.

An auditor might test a company’s total salary expense by multiplying the number of employees at year-end by the average salary, adjusted for any known pay raises. If the company’s recorded salary expense is very close to this expectation, it provides the auditor with assurance that the recorded amount is not materially misstated. This approach allows for efficient testing of large volumes of transactions by focusing on high-level relationships.

The persuasiveness of the evidence from these procedures is linked to the quality of the expectation and the reliability of the data used. A vague expectation or one based on unreliable information yields weak audit evidence. Therefore, the standards require the auditor to consider the plausibility and predictability of the relationship being tested before deciding to rely on an analytical procedure.

Designing the Procedure and Developing an Expectation

The design of a substantive analytical procedure involves developing the auditor’s expectation. This expectation is not a rough estimate; AS 2305 requires it to be precise enough to identify a potential misstatement that could be material to the financial statements. The precision of this expectation is influenced by several factors, including the level of detail used. Analyzing revenue on a monthly or quarterly basis, for instance, will produce a more precise expectation than analyzing it annually, as it can better account for seasonality.

Auditors employ several methods to form an expectation, each suited to different circumstances. These include:

• Trend analysis, which involves analyzing changes in an account balance over time, such as comparing current monthly sales figures to the same months in prior years.
• Ratio analysis, which involves comparing relationships between financial statement accounts or between financial and non-financial data, like comparing a company’s gross margin percentage to industry benchmarks.
• A reasonableness test, which forms an expectation using a model based on operational or financial data, such as estimating hotel revenue by multiplying the number of rooms, average daily rate, and average occupancy rate.
• Regression analysis, a more statistically advanced method that identifies the relationship between a dependent variable (e.g., sales) and one or more independent variables (e.g., advertising spend).

Auditors must assess the reliability of the data used to build the expectation. They consider the source of the data, preferring information from independent outside sources over data generated internally by the company. They also assess the comparability of the information, ensuring that industry data is from companies of a similar size and nature. The auditor must also evaluate the nature and relevance of the information, considering if it logically relates to the account being tested. The controls over the preparation of the data are also important, as strong internal controls give the auditor more confidence in its reliability.

Before the comparison is made, the auditor must establish the “tolerable difference.” This is the maximum acceptable variance between the auditor’s expectation and the company’s recorded amount. This threshold is set in relation to the performance materiality for the audit and the desired level of assurance from the procedure. Any difference that exceeds this amount is considered significant and requires further investigation.

Evaluating Outcomes and Fulfilling Documentation Requirements

Once the auditor compares their expectation to the company’s recorded amount, the outcome dictates subsequent actions. If the difference between the two figures exceeds the predetermined tolerable difference, the auditor is required to investigate the variance. This investigation must go beyond simply asking management for an explanation and accepting it at face value. The objective is to obtain sufficient corroborating evidence to support any explanations provided.

For example, if an analytical procedure on revenue results in an unexpectedly high amount, management might explain it was due to a large, one-time sale. Strong corroborating evidence would include examining the signed contract for that sale, the shipping documents, and the subsequent cash receipt. Weak evidence would be an internal email from the sales manager merely stating the sale occurred. The auditor must apply professional skepticism to evaluate whether the evidence gathered adequately explains the difference.

The documentation of substantive analytical procedures is specified by auditing standards to ensure the work can be reviewed. The auditor’s workpapers must document several elements, including:

• The expectation and the factors considered in its development, including the specific data used, its source, and the method employed.
• The amount of the tolerable difference that was established during the planning phase.
• The result of the comparison between the auditor’s expectation and the company’s recorded amount.
• The detailed procedures performed to investigate any variance that exceeded the tolerable amount, including management inquiries, corroborating evidence, and the auditor’s final conclusion.