Lecture 8 - Evidence and Sampling Flashcards

1
Q

What is audit evidence

A

Information + Procedures = Evidence

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2
Q

What is an appropriate audit procedure

A

The auditor shall design and perform further audit procedures whose nature, timing, and extent are based on and are responsive to the assessed risks of material
misstatement at the assertion level.

The Key Characteristics of an audit procedure are:
NATURE TIMING EXTENT

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3
Q

Nature of procedures to gain evidence

A
  • Substantive procedure: An audit procedure designed to detect material
    misstatements at the assertion level. Substantive procedures comprise:
    ~ Tests of details (of classes of transactions, account balances, and
    disclosures)
    ~ Substantive analytical procedures
  • Test of controls:An audit procedure designed to evaluate the operating effectiveness of controls in preventing, or detecting and correcting, material misstatements at the assertion level
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4
Q

What are the procedures to gain evidence

A
  • Inspection of tangible assets: Inspection (physical examination) of tangible assets that are recorded in the accounting records confirms existence, but does not confirm rights and obligations or valuation. For example, machinery recorded in asset register can be inspected by assurance providers. Confirmation that assets seen are recorded in accounting records gives evidence of completeness.
    STRENGTHS & WEAKNESSES: inspection of assets is a good procedure, particularly in the case of assets that the entity could not function without for example its production plant. Weaknesses of inspections is that assets not used in daily production could be hidden from assurance providers and not included in financial statements.
  • Inspection of documentation: Inspection of documents involves examining records or documents, for example, looking at a sales contract or a share certificate. What inspection of documents achieves depends on the nature of the document. For example, looking at a share certificate gives evidence of the existence of the investment. Looking at source documents (eg, sales invoices) and tracing to financial statements gives evidence of completeness (eg, of revenue). Inspection also provides evidence of valuation (for example, a purchase invoice gives evidence of the cost of inventory), rights and obligations (for example, a hire purchase agreement gives evidence in relation to ownership of non-current assets) and the nature of items (presentation and disclosure). It can also be used to compare documents (and hence
    test consistency of audit evidence) and confirm authorisation.
    STRENGTHS & WEAKNESSES: Strength depends on what is being inspected to give evidence. For instance, inspection of a purchase invoice gives better quality evidence than inspection of sales invoice, because a purchase invoice is created by a third party.
  • ObservationThis involves watching a procedure being performed (for example, post opening).
    STRENGTHS & WEAKNESSES: This procedure is relatively weak, as it only confirms that the procedure is being performed correctly when the assurance
    -Inquiry: This involves seeking information from client management or staff or external sources and evaluating responses.
    STRENGTHS & WEAKNESSES: The strength or weakness of this procedure will depend on of whom the inquiry is being made - a member of client staff could misrepresent matters to the assurance provider if they misunderstand the nature of thequestion, or they are seeking to conceal a misstatement or fraud.
  • Recalculation: Checking mathematical accuracy of client’s records, for example, adding up ledger accounts. Recalculation is evidence created by the assurance provider so is strong evidence.
  • Reperformance: Competenty e auth techniques covered be, either manually or through the use of Again, the fact that the assurance provider carries out the performance of a control themselves makes it strong evidence.
  • Analytical procedures: Evaluating and comparing financial and/or non-financial data for plausible relationships and investigating unexpected fluctuations. Evidence here is limited by the strength or weakness of the underlying accounting system. However, this can be a strong procedure if comparison is made to items that do not rely on the same accounting system or that the assurance provider can corroborate outside the
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5
Q

Types of Substantive Procedures

A

Substantive Analytical Procedures (SAPs)
Tests of detail

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6
Q

Substantive Analytical Procedures (SAPs)

A

The auditor develops an expectation of recorded amounts:
●The data used to develop the expectation must be tested for completeness and accuracy
●If difference between the expectation and recorded amount is not within an acceptable tolerance further investigation is required

Wages Substantive Analytical Procedure

CY Wages = PY wages x CY wage rise x CY increase in staff

  • Obtain staff numbers from Human Resources records for the current and prior years (test for completeness and accuracy to HR records)
  • Obtain standard pay rates in current and prior years and details and dates of pay increases (check for completeness and accuracy e.g. to Board Minutes)
  • Create Expectation (as above)
  • Establish tolerable difference (based on materiality and risk)
  • Compare expectation to recorded amount – if difference is not tolerable further investigation is required
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7
Q

When are SAPs appropriate?

A
  • Suitability: analytical procedures are more applicable to large volumes of transactions that tend to be predictable (for example payroll), depends on the purpose of the test since some analytical procedures will provide persuasive evidence and others will provide corroboration of other tests, other audit tests directed to the same assertions
  • Reliability of the data: the source of the information used (third party or internal, for example), the comparability of the information (for example, an industry standard may not be useful if the company is unusual within the industry), nature and relevance of the information used (for example, if comparing something to budget, is the budget realistic or more of a target?), whether there are controls over the production of the information used to ensure completeness, accuracy, validity.
  • Precision: the accuracy with which results in test area can be predicted (for example, compare gross margin with a less predictable item, for example,advertising), the extent to which information can be disaggregated (for example, by division), availability of required information.
  • Acceptable difference: this is influenced by materiality and the desired level of assurance. As assessed risk rises, the amount of difference from expected results considered acceptable without investigation will reduce.
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8
Q

Tests of Detail

A

Tests of detail involve the auditor obtaining direct audit evidence that responds to risks of and account balance at the assertion level

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9
Q

Sampling

A

Assurance providers do not normally test all the information available to them as to do so would be impracticable and unlikely to be cost effective – sampling techniques are used

When is it appropriate
Large populations
Relatively homogenous (similar items)
Lower value items (compared to materiality)
Lower risk items
Appropriate population information can be obtained

The population must be appropriate for the risk. You cannot get evidence of completeness from sampling into the recorded amount – you need a reciprocal population
- Sampling unit must be relevant to the objective of the test
- The sample size will be based on for:
Controls – Risk and Expected Rate of Deviation
Test of Detail - Risk and Tolerable Error (based on Performance Materiality)

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10
Q

Sampling – Sample selection methods

A

Random selection (e.g. by random number generation)
Systematic selection (e.g. every fifth item)
Haphazard selection (e.g. “luck dip”)
Sequence or block selection (rare)
Monetary Unit Sampling (MUS) (frequently used)

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11
Q

Drawing Conclusions from Sampling

A

misstatements: difference between the amount of a reported financial statement item and the amount that is required to be in accordance with the applicable financial reporting framework

Where misstatements are identified they are projected across the whole of the population…

… unless the misstatement is an anomaly – which are rare and require further procedures to establish

Determining the Nature and Cause of misstatements is essential to evaluation of the impact of misstatements

Reassess risk and, if necessary, complete further audit procedures

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12
Q

Evaluation of Misstatements

A

Misstatements that are larger than the clearly trivial threshold identified in the audit are assessed individually and in aggregate

Management and Those Charged with Governance are requested to correct any of these misstatements that are not corrected in the financial statements

Assessment of misstatements is both quantitative and qualitative (particularly considering the risk of fraud and management bias)

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13
Q

Quantitative vs Qualitative Assessment

A

Misstatements smaller than materiality may be considered qualitatively material because they are important to the users of financial statements.

For example if they relate to:
Indication of fraud ( e.g. intentional misstatement to “hide” something)
Indication of non-compliance with laws and regulations (e.g. disclosure of fines or penalties)
Management bias (e.g. to manipulate trends in financial statements)
To hide or postpone bad news (e.g. subsequent events)

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14
Q

Accounting Estimates

A

An accounting estimate is an approximation of a monetary amount in the absence of a precise means of measurement
Examples of management estimates:
Receivables provisions
Pension liabilities
Inventories write downs-scrap /NRVs
Warranties
Damages in a legal claim

Accounting estimates are difficult to audit because they cannot be “directly” substantiated and therefore require a specific combination of audit procedures

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15
Q

Testing Accounting Estimates

A

Test management’s process
Develop an auditor’s estimate
Review events up to date of audit report

The standard requires specific consideration of Model used, Data, and Assumption used

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