What Are Analytical Procedures in Auditing?

Analytical procedures are evaluations of financial information made by studying plausible relationships among both financial and non-financial data. Auditing standards in the United States, set by the American Institute of Certified Public Accountants (AICPA) for private companies and the Public Company Accounting Oversight Board (PCAOB) for public companies, define these procedures as a part of the audit process. Auditors use them to identify fluctuations or relationships that are inconsistent with other relevant information or differ from expected values by a significant amount. This process allows auditors to direct their attention toward areas that may contain potential misstatements.

The Purpose and Premise of Analytical Procedures

The purpose of analytical procedures is to identify potential risk and misstatement within a company’s financial statements. During the planning stage, these procedures help determine the nature and extent of other audit tests. During substantive testing, they are used to obtain evidence about specific account balances. At the end of the audit, they assist in forming an overall conclusion on the financial statements.

The practice of using analytical procedures is built on the premise that plausible relationships among data are expected to exist and continue. For instance, a company’s revenue is expected to correlate with changes in its customer base or production volume. If a hotel’s revenue increases without a corresponding increase in occupancy rates, this signals an inconsistency that warrants further investigation.

This expectation of consistency applies to financial data, like comparing revenue year-over-year, and relationships between financial and non-financial data, such as comparing payroll expenses to the number of employees. When these expected relationships do not hold true, it suggests a heightened risk of material misstatement that must be examined.

Types of Analytical Procedures

Trend Analysis

Trend analysis is the comparison of current account balances with data from prior periods to identify unusual changes that deviate from historical patterns. An auditor might compare a company’s monthly sales for the current and prior year. A sudden, unexplained spike in sales that does not align with seasonal patterns could indicate a potential overstatement of revenue.

This method is useful for accounts expected to be stable, such as monthly rent or insurance. For example, if a company’s consistent monthly rent expense suddenly jumps, it would be flagged. The auditor would then investigate the reason for this variance, which could be a legitimate rent increase or a potential misclassification of an expense.

Ratio Analysis

Ratio analysis involves comparing key financial ratios to benchmarks, such as the company’s prior-period ratios, budgets, or industry averages. This technique provides insight into the relationships between financial accounts and the company’s overall performance. Common ratios include liquidity, profitability, and leverage ratios.

A significant deviation in a ratio can signal a change in business operations or a potential misstatement. For instance, if a retail company’s gross margin percentage suddenly increases without a clear explanation, it could suggest an issue. The auditor would then investigate whether revenue is overstated or if the cost of sales is understated.

Reasonableness Testing

Reasonableness testing involves developing an expectation for an account balance and comparing it to the amount recorded by the company. This method often uses non-financial data to create a model for what an account balance should be. It is effective for estimating balances in accounts that have a predictable relationship with operational data.

A common example is estimating a company’s total payroll expense. An auditor can develop an expectation by multiplying the total number of employees by their average salary and factoring in payroll tax rates. If the recorded payroll expense is significantly different from this expectation, it would trigger an investigation into potential errors.

Regression Analysis

Regression analysis is a statistical method that evaluates the relationship between two or more variables to develop a precise expectation. For example, an auditor might use regression to predict sales revenue based on variables like advertising spending, store square footage, and regional economic data. This statistical model allows auditors to more effectively identify significant, unexplained variances.

The Four-Step Application Process

The application of analytical procedures follows a structured, four-step process:

• Develop an expectation: The auditor develops an independent expectation of what a recorded account balance or ratio should be. This prediction is based on the auditor’s understanding of the company, its industry, prior-period data, and other relevant information.
• Define a tolerable difference: The auditor must define a threshold, which is the maximum amount the company’s recorded figure can differ from the expectation without causing alarm. This amount is a matter of professional judgment and depends on the desired level of assurance and the precision of the expectation.
• Compare the recorded amount to the expectation: The auditor compares the company’s recorded amount or ratio against the independent expectation. If the difference is smaller than the tolerable difference, the auditor can accept the recorded amount as reasonable.
• Investigate significant differences: If the computed difference exceeds the tolerable threshold, the auditor investigates the discrepancy. This begins with making inquiries of management and then corroborating their explanations with other audit evidence to determine if the difference is due to a plausible business reason or a potential misstatement.