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Evidence and Sampling
Mohammad Salahuddin Chowdhury, ACA
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Computer Assisted Audit techniques
With so many accounting systems now held on computer,
the assurance provider may wish to make use of CAATs.
There are two main types of CAAT : Test data
Audit software
Test data
Under this test of control, the assurance provider
supervises the process of running data through the
clientssystem. The stages are
Notes controls in client's system
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Computer Assisted Audit techniques
Decide upon test data, the options include
Dummy data
Real dataDummy data against a verified copy of the
clientssystem
Run the test data
Compare results with those expected
Conclude on whether controls are operating properly
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Computer Assisted Audit techniques
Worked example:
To carry out such a test the assurance provider
identifies a control in the clients system. Theassurance provider then predicts the systemsreaction
to the test data. For example:
An invoice which does not cast should be rejected when entered
in the system.
An invoice with an invalid supplier code should be rejected
Dates outside the current year should be rejected.
The assurance provider then runs the test data
through the clientssystem and compares the results
with those expected.
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Computer Assisted Audit techniques
Audit Software
Audit software makes use of the assurance providers
own specialised software. There are a number of off theshelf packages available, or the assurance provider
could have a tailor made system. Audit software works
on the basis of interrogating the clients system and
extracting and analysing information. It can therefore
carry out a whole range of substantive procedures,
across all sorts of different data.
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Computer Assisted Audit techniques
Audit Software
Examples of what audit software can do include:
Extracts a sample according to specified criteria Random
Over a certain amount
Below a certain amount
At certain dates
Calculates ratios and select those outside set criteria
Check calculations and casts performed by the system
Prepare reports (actual vs budgeted)
Follow items through a system and flag where they are
posted.
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Computer Assisted Audit techniques
Audit Software
Examples of what audit software can do include:
Extracts a sample according to specified criteria Random
Over a certain amount
Below a certain amount
At certain dates
Calculates ratios and select those outside set criteria
Check calculations and casts performed by the system
Prepare reports (actual vs budgeted)
Follow items through a system and flag where they are
posted.
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Evidence and Sampling
Directional Testing
Broadly speaking, substantive procedures can be said to
fall into two categories:
Tests to discover errors (resulting in over orunderstatement)
Tests to discover omissions (resulting in
understatement)
Tests to discover errors
Tests to discover errors will start with the accounting
records in which the transactions are recorded and check
from the entries to supporting documents or other
evidence. Such tests should detect any overstatement
through causes other than omission.
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Evidence and Sampling
Tests to discover errors (Worked example)
If test is designed to ensure that sales are priced
correctly, the test would begin with a sales
invoice selected from the receivables ledgere.
Prices on that invoice would then be checked to
the official price list.
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Evidence and Sampling
Tests for omission
Tests for omission must start from outside the accounting
records and then check back to those records.
Understatements through omission will never be revealedby starting with the account itself as there is clearly no
chance of selecting items that have been omitted from the
account.
Example: If the test is designed to discover whether allraw material purchases have been properly processed, the
test would start, say, with goods received notes, to be
checked to the inventory records or payables ledger.
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Evidence and Sampling
Tests for omission
Omission is usually more of a problem for certain account
balances, such as liabilities, than others, such as sales, as
a company might be more inclined to understate liabilitiesto create a good position in the financial statements.
However, this is where the auditorsunderstanding of the
entity is important, as the auditor must make judgments
about the situation of the entity at the moment-for
example, a company with a large VAT commitment might
want to understate sales.
Directional testing is particularly appropriate when testing
the financial statement assertions of existence,
completeness, rights and obligations and valuation.
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Evidence and Sampling
Tests for omission
An assurance firm may use directional testing to identify
over and understatements.
Directional testing is particularly appropriate when testingthe financial statement assertions of existence,
completeness, rights and obligations and valuation.
Test are therefore designed in the following way.
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Evidence and Sampling
Test item Example
Test debit items (expense or assets)
for overstatement by selecting debit
entries recorded in the nominal
ledger and checking value and
existence
If a non-current asset entry in the
nominal ledger of BDT 1000 is
selected, it would be overstated if it
should have been recorded at
anything less than BDT1,000 or if the
company did not own it, or indeed if
it did not exist.
Test credit items (income or
liabilities) for understatement byselecting items from appropriate
sources independent of the nominal
ledger and ensuring that they result
in the correct nominal ledger.
Select a despatch note and check
that the resultant revenue has beenrecorded in the nominal ledger
revenue account. Sales would be
understated if the nominal ledger did
not reflect the transaction at all or
reflected it at less than full value.
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Evidence and Sampling
Audit of Accounting Estimates
The auditor often has to audit estimated figures, such as
those for product warranties, depreciation, inventory or
receivable provisions, where the values included in thefinancial statements are not the result of transactions with
third parties (which are fairly reliable) but result from
judgments made by management. Yet these figures can
have a significant effect on reported profits.
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Evidence and Sampling
The audit approach required is set in BSA 540 Audit of
Accounting Estimates. Essentially the auditor has three
methods to use:
Method
Example
Test the process that
management used to
estimate the figure
Management may use a formula to calculate the provision for
doubtful accounts receivable. The auditor can test this by:
Looking at past experience
Checking the calculation Considering if anything this year is likely to have changed
the estimate
Use an independentestimate
If a provision is required in respect of legal action against thecompany, the auditor can use evidence from the companys
legal advisors.
Review subsequent
events
If a settlement is reached after the year end regarding a claim
against the company which requires a provision, the auditor
can use the evidence of the agreement to establish the correct
figure for the financial statements. In this case there is usually
no need to use the other two methods.
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Evidence and Sampling
Having done the detailed work on the accounting estimate,
the auditor checks the reasonableness of the figure and
then reaches a conclusion about whether it is fairly stated.
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Evidence and Sampling
The Concept of Sampling
Assurance providers do not normally examine all the
information available to them; it would be impracticable to
do so and using sampling will produce valid conclusions
provided it is carried out properly.
BSA 530 Audit Sampling and Other Means of Testing
states that whendesigning audit procedures, the auditor
should determine appropriate means for selecting itemsfor testing so as to gather sufficient appropriate audit
evidence to meet the objectives of the audit procedures.
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Evidence and Sampling
Audit Sampling
Audit sampling involves the application of audit
procedures to less than 100% of the items within an
account balance or class of transactions such that all
sampling units have a chance of selection. This will enable
the auditor to obtain and evaluate audit evidence about
some characteristic of the items selected in order to form
or assist in forming a conclusion concerning the
population from which the sample is drawn.
Population
Population is the entire set of data from which a sample is
selected and about which an auditor wishes to draw
conclusions.
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Evidence and Sampling
Statistical Sampling
Statistical sampling is any approach to sampling that
involves random selection of a sample, and use of
probability theory to evaluate sample results, includingmeasurement of sampling risk.
Non-statistical Sampling
Non-statistical sampling is a subject approach toinference, in that mathematical techniques are not used
consistently in determining sample size, selecting the
sample, or evaluating sample results.
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Evidence and Sampling
The auditor may alternatively select certain items from a
population because of specific characteristics they possess.
The results of items in this way cannot be projected onto the
whole population but may be used in conjunction with other
audit evidence concerning the rest of the population. High Value or Key Items: The auditor may select high
value items or items that are suspicious, unusual or
prone to error.
All Items over a Certain Amount: Selecting items this
way may mean a large proportion of the population canbe verified by testing a few items.
Items to obtain information about the clientsbusiness,
the nature of transactions, or the clientsaccounting and
control systems.
Items to test procedures, to see whether particularprocedures are being performed.
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Evidence and Sampling
Design of the Sample
When designing the sample, the BSA requires the auditor
to considerthe objectives of the audit procedures and the
attributes of the population from which the sample will be
drawn, and to consider the sampling and selection
methods.
Assurance provider must consider the specific audit
objectives to be achieved and the audit procedures thatare most likely to achieve them. The assurance providers
also need to consider the nature and characteristics of the
audit evidence sought, possible error conditions and the
rate of expected error. These will help them to define what
constitutes an error and what population to use for
sampling.
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Evidence and Sampling
Error
Error means either control deviations, when performing
tests of control, or misstatements, when performing
substantive procedures.
Expected Error
Expected error is the error that the auditor expects to be
present in the population.
The population from which the sample is drawn must beappropriate and complete for the specific audit objectives.
The BSA distinguishes between situations where
overstatement or understatement is being tested.
Assurance providers must define the sampling unit in
order to obtain an efficient and effective sample to achievethe particular audit objectives.
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Evidence and Sampling
Sampling Units
Sampling units are the individual items constituting a
population.
Example: Sampling Units
Cheques listed on the deposit slip
Credit entries on bank statements
Sales invoices
Receivables balances
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Evidence and Sampling
The BSA requires that the auditor shouldselect items for
the sample with the expectation that all sampling units in
the population have a chance of selection.This requires
that all items in the population have an opportunity to be
selected.
In obtaining evidence, the auditor should use professional
judgment to assess audit risk and design audit procedures
to ensure this risk is reduced to an acceptably low level. In
determining the sample size, the auditor should considerwhether sampling risk is reduced to an acceptably low
level.
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Evidence and Sampling
Sampling Risk
Sampling risk arises from the possibility that the auditors
conclusion, based on a sample of a certain size, may be
different from the conclusion that would be reached if the
entire population were subjected to the same audit
procedures.
Non-sampling Risk
Non-sampling risk arises from factors that cause theauditor to reach an erroneous conclusion for any reason
not related to the size of the sample. For example, most
audit evidence is persuasive rather than conclusive, the
auditor might use inappropriate procedures, or the auditor
might misinterpret evidence and fail to recognize an error.
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Evidence and Sampling
Tolerable Error
Tolerable error is the maximum error in the population that
the auditor would be willing to accept.
Tolerable error is considered during the planning stage
and for substantive procedures, is related to the auditors
judgment about materiality. The smaller the tolerable error,
the greater the sample size will need to be.
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a) In tests of control, the tolerable error is the maximum rate
of deviation from a prescribed control procedure that
assurance providers are willing to accept in the
population ands still concludes that the preliminary
assessment of control risk is valid.
b) In substantive procedures, the tolerable error is the
maximum monetary error in an account balance or class
of transactions that assurance providers are willing to
accept so that, when the results of all audit procedures areconsidered, they are able to conclude, with reasonable
assurance, that the financial statements are not materially
misstated.
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Evidence and Sampling
The size and frequency of errors is important when
assessing the sample size; for the same overall error,
larger and fewer errors will mean a bigger sample size
than for smaller and more frequent errors. If the expected
error rate is high then sampling may not be appropriate.When considering expected error, the assurance providers
should consider:
Errors identified in previous audits
Changes in the entitys procedures
Evidence available from other procedures
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Evidence and Sampling
Selecting the Sample
There are a number of selection methods available.
a) Random Selection
Random selection ensures that all items in thepopulation have an equal chance of selection, e.g. by
use of random number tables or computerized
generator.
b) Systematic Selection
Systematic selection involves selecting items using aconstant interval between selections, the first interval
having a random start. When using systematic
selection assurance providers must ensure that the
population is not structured in such a manner that the
sampling interval corresponds with a particularpattern in the population.
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c) Haphazard Selection
Haphazard selection may be an alternative to random
selection provided assurance providers are satisfied
that the sample is representative of the entire
population. This method requires care to guardagainst making a selection that is biased, for
example towards items that are easily located, as they
may not be representative. It should not be used if
assurance providers are carrying out statistical
sampling.
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Evidence and Sampling
d) Sequence or Block Selection
Sequence sampling may be used to check whether
certain items have particular characteristics. For
example, an auditor may use a sample of 50
consecutive cheques to check whether chequesare signed by authorized signatories rather than picking
50 single cheques throughout the year. Sequence
sampling may, however, produce samples that are
not representative of the population as a whole,
particularly if errors only occurred during a certainpart of the period, and hence the errors found cannot
be projected onto the rest of the population.
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Evidence and Sampling
e) Monetary Unit Sampling (MUS)
This is a selection method that ensures that every CU
1 in a population has an equal chance of being
selected for testing. The advantages of this selection
method are that it is easy when computers are used,and that every material item will automatically be
sampled. Disadvantages include the fact that if
computers are not used, it can be time consuming to
pick the sample, and that MUS does not cope well with
errors of understatement or negative balances.
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Evidence and Sampling
Drawing Conclusion from Sampling
When the assurance providers have tested a sample
of items, they must then draw conclusions from that
sample. The purpose of sampling the items was to
enable them to project the conclusion they draw from
the sample to the whole population.
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Any Questions ?