Audit Sampling
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Transcript of Audit Sampling
Audit Sampling Sampling for test of Control Substantive test sampling
Used to address sufficient audit evidence
When the application of 100% testing is not feasible or efficient
Sampling is the application of an audit procedure to less than 100 percent of the items within an account balance or class of transaction for the purpose of evaluating some characteristics of the entire balance or class
The risk the auditor’s conclusions reached from a sample maybe different from the conclusions he/she reached if the test were applied to the whole population
3 Factors affecting the determination of sample size: The desired level of assurance in the
results ( confidence level) Acceptable defect rate ( tolerable error /
materiality level ) The historical defect rate (expected error)
Confidence level is the complement of sampling risk
If the auditor set sampling risk for a particular sampling application at 5 percent, it will result to a confidence level of 95 percent
Once the desired confidence level is established, the sample size is determine largely by how much the tolerable error exceeds the expected error
Once the desired confidence level is establiched, the sample size is determine largely by how much the tolerable error exceeds the expected error
TYPES OF EVIDENCE AUDIT SAMPLING USED ?
Inspection of tangible assets
Inspection of records Reperformance Recalculation Confirmation Analytical procedure Scanning Inquiry observation
Y / N Y / N Y / N Y / N Y / N Y / N Y / N Y / N Y / N
Testing all items with a particular characteristics Population is made up with a few larger items Qualitative factors large items
E.g: choose journal entries posted by finance Director – For fraud testing over journal entries
Applicable for highly automated information systems process transactions consistently unless the systm or porgrams are changed
The auditor may test the general controls over the system and any program changes, but test only few transactons processed by the IT system
Nonstatistical ( judgemental ) Audtor does not use statistical technoques to determine
sample size, select the sample items or measure sampling risk
Statistical use the law of probability to compute sample size and evaluate the sample results
Attribute samplingMonetary unit sampling classical variable sampling
Attribute sampling Used to estimate the proportion of a population
that possess a specific characteristics. Commonly used in test for controls
Monetary unit sampling MUS uses attribute sampling theory to
estimate the dollar amount of misstatement for a class of transaction or account balance
Classical variable sampling Inference about the population based on
sample data Used when we have assessed risk as high,
we expect more than a few errors and we wish to estimate their potential monetary effects
Risk of assessing control risk too low The risk that the assessed level of control
risk based on the sample supports the planned assessed level of control risk when the true operating effectiveness of the internal control, if known, would not be considered adequate to support the planned assessed level
Risk of assessing control risk too high
Steps: Plan Perform Evaluate Document
Determine test of objectives Define the population characteristics
Define sampling population Define sampling unit Define the control deviation
Determine the sample test The desired confidence level The tolerable deviation rate The expected population deviation rate
Select sample items: Random number selection Systematic selection
Perform the audit procedures Voided document Unused or inapplicable documents Missing sample items
Calculate the sample deviation and upper deviationr ate
Draw final conclusions
Determining the sample size An auditing firm may establish a sampling
policy;i.e. low risk of failure took 15-20 samples, moderate took 25-35 samples, high took 40-60 samples
Selecting sample items Allows the use of random or systematics
selection but also permits oother method; i.e haphazard sampling ( choose sample
without bias )
Calculating the upper deviation rate Auditor can calculate the sample deviation
rate, but cannot quantify the computer upper deviation rate and sampling risk associated with the test
Risk of incorrect acceptance ( type 1) The risk that sample supports the
conclusion that the recorded account balance is not materially misstated when it is materially misstated
Risk of incorrect rejection ( type 2 )
MUS uses attribute sampling theory to estimate the percentage of monetary units in a population that might be misstated and then multiplies this percentage by an estimate of how much the dollars are misstated. Commonly used for test of details
When the auditor expects no misttatemens, MUS usually result in a smaller sample size than classical variable sampling
The calculation of the sample size and evaluation of the sample results are not b ased on the variation between items in t epopulation
Whenapplied using the probability to proportional to size procedure, MUS automatically results in a stratified sample
The selection of zero or negative balances generally requires special design consideraton
The general approach to MUS assumes that the audited amount of the sample item is not in the error by more than 100%
When more than one or two misstatements are detected, the sample results calculations may overstate the allowance for sampling risk
MUS is not effective in detecting understatements
The sampling unit for non statistical sampling is normally a customer account, an individual transaction or a line item on a transactions
When using non statistical sampling, the following items must be considered Identify individually significant items Determining the sample size Selecting sample items Calculation the sample result
Uses normal distribution theory to evaluate the characteristics of a population based on sample data. Auditors commonly use classical variables sampling to estimate the size of misstatement
When the auditors expect a large number of differences between book and audited values this method will result in smaller sample size than MUS
The techniques are effective for both overstatements and understatements
The selection of zero balance generally does not require special sample design considerations
To determine sample size, the auditor must estimate the standard deviation of audited value of differences
If few misstatements are detected in the sample data, the true variance tends to be underestimated, and the resulting projection of the misstatements to the population is likely not to be reliable