8. Sampling Flashcards
Samples help to
- to develop effective and efficient audit procedures
- to measure the persuasiveness of results
- to conclude the quality/characteristics of the population from the sample
Sampling vs. 100% analyses
- Less time
- Less costs
- Testing can be “destructive” in terms of the sampled items (however, less a problem in auditing)
- Complete analyses are frequently impossible
Audit Procedures with and without Samples
Audit procedures with samples
Application of the audit procedure to less than 100% of a population, e.g., sampling of a group of transactions:
– Statistical sampling
– Non-statistical sampling
Audit procedures without samples
- Full analysis of the population
- Analytical procedures
- Observations and interviews
- Non-audited areas
– E.g., low risk areas or not material
Representative Samples
- The auditor should choose the sampled items so they represent the population
- Representativeness means the same probability for each item to be selected
- A representative sample is one in which the characteristics in the sample are approximately the same as those of the population
- In practice, an auditor never knows whether a sample is representative, even after all testing is complete
Sampling Risk and Non-Sampling Risk
Sampling Risk
Probability that a sample is not representative and the auditor reaches an incorrect conclusion because the sample is not representative of the population
Non sampling risk
The risk that the auditor reaches an incorrect conclusion for any reason not related to sampling risk.The auditor might fail to recognize an exception, even if exceptions exist
Statistical and Non-statistical Sampling
Statistical Sampling (probability or random sampling)
Each population item has a known probability of being included in the sample. The auditor cannot subjectively influence which items are included in the sample.
Non-statistical Sampling (judgmental sampling)
Subjective sampling procedure. Subjectivity can be of use due to prior results, in order to focus on high-risk items
Attribute Sampling
- Used to estimate the percent of items in a population containing a characteristic or attribute of interest
- This percent is called the occurrence rate or exception rate, i.e., the ratio between the number of items exhibiting the attribute and the number of items in the population
- The auditor is interested in the following types of exceptions in populations of accounting data:
– Deviations from the client’s established internal controls
– Monetary misstatements in populations of transaction data
– Monetary misstatements in populations of account balance details
Steps for planning a sample
(1) State the objectives of the audit test
(2) Decidewhetherauditsamplingapplies
(3) Defineattributesandexceptionconditions (4) Define the population
(5) Define the sampling unit
(6) Specify the tolerable exception rate
(7) Specify acceptable risk of overreliance
(8) Estimate the population exception rate
(9) Determine the initial sample size
Tolerable Exception Rate (TER)
TER represents the highest exception rate the auditor will permit in the control being tested and still be willing to conclude the control is operating effectively
– TER can have a significant impact on sample size. A larger sample size is needed for a low TER than for a high TER
– Since a lower TER used for significant account balances, the auditor requires a larger sample size to gather sufficient evidence about the effectiveness of the control or absence of monetary misstatement
Acceptable Risk of Overreliance
- The risk that the auditor concludes that controls are more effective than they actually are is the risk of overreliance
- Vs. risk of under reliance – risk that the auditor will erroneously conclude that the controls are less effective than they actually are
- ARO measures the risk the auditor is willing to take of accepting a control as effective (or a rate of misstatements as tolerable) when the true population exception rate is greater than TER.
– ARO represents the auditor’s measure of sampling risk
– An ARO of 5%, leads to a confidence level of 95%
– ARO is based on the assessed control risk: the lower the assessed control risk, the lower ARO
– Like for TER, there is an inverse relationship between ARO and planned sample size
Estimate Population Exception Rate
- EPER represents the exception rate the auditor estimates in advance of the audit to plan the appropriate sample size
– In case the auditor expects exceptions in the population, more sample items must be examined, in order to confirm that the actual exception rate in the population does not exceed the planned TER
– To determine EPER, the auditor has to consider:
- Exception rates of prior audits
- Changes in procedures of the unit audited
- Information available from other procedures
Sample Size
- The sample size is influenced by the amount of sampling risk the auditor is willing to accept
− The lower the accepted sampling risk, the larger the sample size
- To determine the initial sample size, the auditor should consider:
− The sampling risk
− The tolerable error
− The expected error
− The size of the population
Sample size in practice
− The auditor wants to reduce the sample size
− Other audit procedures cover the risks
− Application of alternate procedures, if the auditor concludes that the client’s internal control system is not acceptable
Selection of Sample and Performance of Audit Procedures (steps 10 and 11)
(10) Select the sample
Probabilistic (random) or non-probabilistic (judgment) sample selection
(11) Perform the audit procedures
The auditor performs the audit procedures by examining each item in the sample to determine whether it is consistent with the definition of the attribute and by maintaining a record of all the exceptions found
Evaluate the results ( steps 12-14 )
srep 13: analyze Exceptions
- In addition to determining SER for each attribute, auditors must analyze individual exceptions
- Errors can be caused by many factors, such as:
– Carelessness of employees
– Misunderstood instructions
– Intentional failure
- The nature of an exception and its causes have a significant effect on the auditor’s qualitative evaluation of the system
Sample Exception Rate (SER)
and Computed Upper Exception Rate (CUER
Sample Exception Rate (SER)
– Actual number of exceptions divided by the actual sample size
Computed Upper Exception Rate (CUER)
– Maximum exception rate that is probable in the population at a
given ARO
– CUER is derived from a table
Evaluate the Results
Important:
– TER and ARO → determined by the auditor before selecting the
sample
– CUER → results from the sample
If CUER (based on the current sample size) d TER (based on ARO), the population can be accepted and the control risk can be lowered
If CUER > TER, one of four courses of actions must be followed:
– ReviseTERorARO
– ExpandtheSampleSize
– ReviseAssessedControlRisk
– CommunicatewiththeAudit Committee or Management
The population cannot be accepted
