Audit sampling is a fundamental technique auditors use to gather sufficient appropriate audit evidence efficiently. It involves selecting and evaluating less than 100 percent of a population, which the auditor expects to be representative of the entire population and will, in turn, provide a reasonable basis for drawing conclusions about that population. This allows auditors to form an opinion on financial statements or the effectiveness of internal controls without examining every single transaction or item, saving significant time and resources.
The Core Process of Audit Sampling
The process of audit sampling can be broken down into several key stages, each crucial for ensuring the reliability and validity of the auditor's conclusions.
1. Planning the Sample
The initial stage involves carefully planning the audit sample to align with the audit objectives.
- Define the Audit Objective: Clearly identify what the auditor aims to achieve. For instance, testing the operating effectiveness of a control over sales invoices or verifying the accuracy of accounts receivable balances.
- Define the Population: Identify the complete set of data from which the sample will be drawn. This could be all sales transactions recorded in a fiscal year, all inventory items, or all employee expense reports. The population must be appropriate for the specific audit objective.
- Define the Sampling Unit: Determine the individual items that constitute the population. If testing sales, the sampling unit might be an individual sales invoice; if testing inventory, it could be a specific inventory item.
- Determine Sample Size: This is a critical step influenced by several factors:
- Tolerable Misstatement/Deviation: The maximum monetary misstatement or rate of deviation from prescribed control procedures that the auditor is willing to accept without concluding that the financial statements are materially misstated or that controls are ineffective.
- Acceptable Sampling Risk: The risk that the auditor's conclusion based on the sample might be different from the conclusion had the entire population been tested (e.g., the risk of accepting a balance as correct when it is materially misstated).
- Expected Error Rate/Misstatement: The auditor's estimate of the frequency of errors or the total misstatement within the population.
- Population Size: While less significant for very large populations, it can still be a factor for smaller ones.
2. Selecting the Sample Items
Once the sample size is determined, the next step is to choose the actual items to be tested from the population. The method of selection is crucial for ensuring the sample is representative.
- Random Selection: Each item in the population has an equal chance of being selected. This can be done using random number generators or tables.
- Example: Using a software tool to randomly select 50 sales invoices from a list of 5,000.
- Systematic Selection: Involves selecting items at a uniform interval from a population after a random starting point.
- Example: If selecting 100 items from 1,000, an auditor might select every 10th item after a random start between 1 and 10.
- Monetary Unit Sampling (MUS): A statistical sampling method that gives greater probability of selection to items with larger monetary values. It is often used for substantive testing of account balances.
- Example: If testing accounts receivable, an invoice for $10,000 has a higher chance of being selected than an invoice for $100.
- Haphazard Selection: The auditor selects items without following a structured technique, but also without any conscious bias. While simpler, it carries a higher risk of not being truly representative compared to random or systematic methods.
- Example: An auditor might pick invoices from a file drawer without a specific pattern, trying to avoid any personal bias.
3. Performing Audit Procedures
After selecting the sample items, the auditor applies the planned audit procedures to each selected item. This involves examining documents, performing calculations, making inquiries, or observing processes to gather evidence.
- Documenting Findings: For each sampled item, the auditor records the results of the audit procedure, including any identified errors or deviations. This documentation is crucial for the evaluation phase and for supporting the overall audit conclusion.
4. Evaluating Sample Results
The final stage involves analyzing the findings from the sample and projecting them to the entire population to draw a conclusion.
- Project Errors: If errors or deviations are found in the sample, the auditor projects these findings to the entire population. For instance, if 2% of sampled sales invoices lacked proper authorization, the auditor might project that 2% of all sales invoices in the population also lack authorization.
- Consider Sampling and Non-Sampling Risk:
- Sampling Risk is the risk that the auditor's conclusion based on a sample may be different from the conclusion if the entire population were subjected to the same audit procedure. This can lead to:
- Risk of Incorrect Acceptance (Type II Error): Concluding that a material misstatement does not exist when it does (for substantive tests) or that a control is effective when it is not (for tests of controls). This impacts audit effectiveness.
- Risk of Incorrect Rejection (Type I Error): Concluding that a material misstatement exists when it does not, or that a control is ineffective when it is effective. This impacts audit efficiency.
- Non-Sampling Risk encompasses all aspects of audit risk that are not due to sampling. Examples include using inappropriate audit procedures, misinterpreting audit evidence, or failing to recognize an error.
- Sampling Risk is the risk that the auditor's conclusion based on a sample may be different from the conclusion if the entire population were subjected to the same audit procedure. This can lead to:
- Formulate Conclusion: Based on the projected errors, the acceptable risk levels, and other audit evidence, the auditor forms a conclusion about the population. This conclusion determines whether the financial statements are fairly presented or if the internal controls are operating effectively. If the projected error exceeds the tolerable misstatement, the auditor may need to expand the sample or perform alternative procedures.
Types of Audit Sampling Approaches
Auditors primarily use two approaches to sampling: statistical and non-statistical.
| Feature | Statistical Sampling | Non-Statistical Sampling (Judgmental Sampling) |
|---|---|---|
| Methodology | Uses mathematical theory of probability. | Relies on auditor's judgment and experience. |
| Sample Size | Objectively determined using statistical formulas. | Subjectively determined by the auditor. |
| Selection | Random, systematic, or probability-proportional-to-size. | Haphazard, block selection, or targeted selection of specific items. |
| Evaluation | Quantifies sampling risk; projects errors statistically. | No statistical quantification of sampling risk. |
| Objectivity | Higher degree of objectivity. | More subjective. |
| Examples | Attributes sampling, variables sampling, Monetary Unit Sampling (MUS). | Selecting items based on size, risk, or past experience. |
Statistical Sampling provides a quantitative measure of sampling risk, allowing auditors to objectively determine sample size and evaluate results.
- Attributes Sampling: Primarily used in tests of controls to estimate the rate of deviation from a prescribed control.
- Variables Sampling: Used in substantive tests to estimate the monetary amount of misstatement in an account balance.
- Monetary Unit Sampling (MUS): A popular method that combines elements of both attributes and variables sampling, often used for substantive testing of account balances. It is particularly effective for populations containing a few large items and many small items.
Non-Statistical Sampling (also known as judgmental sampling) relies on the auditor's professional judgment to determine sample size and select items. While it can be more flexible and cost-effective in certain situations, it does not allow for a statistical quantification of sampling risk.
Practical Insights and Examples
- Testing Authorization of Payments: An auditor might select a sample of payment transactions from the general ledger. For each selected payment, they would examine supporting documentation (e.g., invoice, purchase order) to confirm it was properly authorized according to company policy. If several payments lack authorization, this could indicate a weakness in internal controls.
- Verifying Accounts Receivable Balances: To confirm the existence and valuation of accounts receivable, an auditor might select a sample of customer accounts and send confirmation requests. The responses are then compared to the company's records. Any discrepancies are investigated, and the overall misstatement is projected to the entire accounts receivable balance.
- Inventory Observation: During a physical inventory count, an auditor may select a sample of inventory items to independently count and compare to the company's records, assessing the accuracy of the inventory count procedures.
Benefits of Audit Sampling
- Efficiency: Significantly reduces the time and cost required compared to a 100% examination, especially for large populations.
- Feasibility: For very large populations, examining every item might be impossible or impractical. Sampling provides a feasible alternative.
- Objectivity: When statistical methods are used, sampling provides a more objective and defensible basis for conclusions.
- Reduced Burden: Minimizes disruption to the client's operations by not requiring access to every single record.
In conclusion, audit sampling is a critical methodology that allows auditors to draw reasonable conclusions about entire populations based on evidence from a carefully selected subset. By following a structured process from planning to evaluation and understanding the associated risks, auditors can efficiently and effectively fulfill their responsibilities.
