Audit Testing : Need For Sampling and Approaches to Statistical Sampling | Auditing and Secretarial Practice - B Com PDF Download

Audit Testing

An audit test is a procedure performed by either an external or internal auditor in order to assess the accuracy of various financial statement assertions. The two common categorizations of audit tests are substantive tests and tests of internal controls. Both types of tests are used in external and internal audits in order to reach established audit objectives, as can be outlined in audit checklists or determined based on the results of audit questionnaires. Audit tests typically are performed on a sample basis over an existing group of similar transactions. Sampling approaches can either be statistical or non-statistical, with the ultimate goal being to obtain the most representative sample of the population before testing begins.

A substantive audit test is a direct test that validates a financial statement balance, while internal control tests are focused on key controls, such as management reviews or standardized templates that are designed to prevent and detect material misstatements. Substantive testing often requires a large deal of recalculating, confirming, and vouching. For example, when an auditor substantively tests an inventory balance, the auditor will go to the on-site location of the inventory, run reports that list the amount of inventory stored on the premises, and physically count each inventory item on a sample basis. Using the same example under an internal control testing approach, an auditor would assess the systems generating the reports, consider the experience level of the personnel on the premises that manage the inventory, and review shipping and receiving documents for the appropriate sign-offs instead of counting the actual inventory on the premises.

Sampling in Audit Testing

Sampling is a process of selecting a subset of a population of items for the purpose of making inferences to the whole population. Accounting populations usually consist of a large number of items (debtors, creditors), often totalling millions of rupees, and a detailed examination of all accounts is not possible. Audit sampling is defined as

“The application of audit procedures to less than 100% of the items within an account balance or class of transactions to enable the auditor to obtain and evaluate evidence about some characteristic of the items selected in order to form or assist in forming a conclusion concerning the population which makes up the account balance or class of transactions”

A fundamental element of any audit programme will be the selection of transactions to be tested as a sample of all available transactions. Sampling is used in both compliance and substantive testing and is described in numerous textbooks in auditing

Need for Audit Sampling

Formalized audit sampling procedures offer innumerable benefits to all auditors. These include:

1. Developing a consistent approach to audit areas;
2. Providing a framework within which sufficient audit evidence is obtained;
3. Forcing clarification of audit thinking in determining how the audit objectives will be met;
4. Minimising the risk of over-auditing; and
5. Facilitating more expeditious review of working papers

Statistical Sampling in Audit

Statistical sampling involves the random selection of a number of items for inspection and is endorsed by the accountancy bodies. In statistical sampling, each item has a calculable chance of being selected.

A commonly held misconception about statistical sampling is that it removes the need for the use of the professional judgement. While it is true that statistical sampling uses statistical methods to determine the sample size and to select and evaluate audit samples, it is the responsibility of the auditor to consider and specify in advance factors such as, materiality, the expected error rate or amount, the risk of over-reliance or the risk of incorrect acceptance, audit risk, inherent risk, control risk, standard deviation and population size, before the sample size can be determined.

Statistical sampling allows an auditor’s judgement to be concentrated on those areas of the audit where it is most needed. It allows the quantification of key factors and the risk of errors. This is not to suggest that statistical sampling methods remove the need for professional judgement, but rather that they allow elements of the evaluation process to be quantified, measured and controlled.

The advantages of statistical sampling are numerous:

1. The sample result is objective and defensible. Nearly all phases of the statistical process are based on demonstrable statistical principles.
2. The method provides a means of advance estimation of sample size on an objective basis. The sample size is no longer determined by traditional methods of guesswork; it is determined by a statistical method.
3. The method provides an estimate of error. When probability sampling is used, the results may be validated in terms of how far the sample projection might deviate from the value that could be obtained by a 100% check.
4. Statistical samples may be combined and evaluated, even though accomplished by different auditors. That the entire test operation has an objective and scientific basis makes it possible for different auditors to participate independently in the same test and for the results to be combined as though accomplished by one auditor.
5. Objective evaluation of test results is possible. Thus, all auditors performing this audit would be able to reach the same conclusion about the numerical extent of error in the population. While the impact of these errors might be interpreted differently, there can be no question as to the facts obtained, since the method of determining their frequency in the population is objective.

Approaches to Statistical Sampling 

In statistical sampling, samples during an audit are normally selected through one of the probability sampling methods — random, systematic or stratified. Probability sampling provides an objective method of determining sample size and selecting the items to be examined. Unlike non-statistical sampling, it also provides a means of quantitatively assessing precision (how closely the sample represents the population) and reliability (confidence level, the percentage of times the sample will reflect the population).

Simple Random Sampling

In auditing, this method uses sampling without replacement; that is, once an item has been selected for testing it is removed from the population and is not subject to re-selection. An auditor can implement simple random sampling in one of two ways: computer programs or random number tables.

Systematic (Interval) Sampling

This method provides for the selection of sample items in such a way that there is a uniform interval between each sample item. Under this method of sampling, every “Nth” item is selected with a random start.

Stratified (Cluster) Sampling

This method provides for the selection of sample items by breaking the population down into stratas, or clusters. Each strata is then treated separately. For this plan to be effective, dispersion within clusters should be greater than dispersion among clusters. An example of cluster sampling is the inclusion in the sample of all remittances or cash disbursements for a particular month. If blocks of homogeneous samples are selected, the sample will be biased.

Remember, an essential feature of probability sampling methods is that each element of the population being sampled has an equal chance of being included in the sample and, moreover, that the chance of probability is known. Only in this way, is a probability sample representative of a population