Module 6: Audit sampling 4/19/15

Transcription

1 Instructor Michael Brownlee B.Comm(Hons),CGA Course AU1 Assignment reminder: Assignment #2 (see Module 7) is due at the end of Week 7 (see Course Schedule). You may wish to take a look at it now in order to familiarize yourself with the requirements and to prepare for any necessary work in advance Module 6: Audit sampling 6.1 Audit sampling: Introduction 6.2 Statistical and non-statistical sampling 6.3 Sampling and non-sampling error 6.4 Attribute sampling and tests of controls 6.5 Determining sample size and selecting the sample 6.6 Evaluating test results 6.7 Audit sampling for substantive testing 1

2 6.8 Sampling procedures for substantive testing 6.9 Determining sample size in substantive testing 6.10 Evaluating test results for substantive testing 6.11 Dollar-unit sampling 6.1 Audit sampling: Introduction Explain why auditors use sampling, and describe the two applications of audit sampling. (Level 1) Important acronyms 2

3 As we have discussed, time and money limit auditors from doing a 100% audit. We are seeking reasonable assurance not absolute assurance. Sampling allows us to perform audit procedures on a limited number of transactions in order to draw a conclusion about an entire class of transactions or account balance. Two Applications We use sampling to test controls when assessing control risk (compliance tests) Secondly, we use sampling to test balances to determine whether balances are materially misstated (substantive tests) Module notes Exhibit

4 Nature, Extent, Timing Nature is referring to the six general techniques: Recalculation/reperformance Observation Confirmation Enquiry Inspection Analysis Timing is when procedures are performed. Nature & timing relate to appropriateness of audit evidence. Extent is how much audit work is to be done. Audit sampling is concerned with extent. 4

5 6.2 Statistical and nonstatistical sampling Explain statistical and non-statistical sampling, describe the advantages of each method, and explain when each method should be used. (Level 1) Statistical sampling Using mathematical probabilities to select random samples Important points are that the samples must be randomly selected and that statistical calculations are used to measure and express results Cannot use non-random samples for statistical sampling as the laws of probability do not apply to non-random samples. Statistical models can be used to estimate preliminary sample size. Statistical sampling cont d Use statistical sampling when: Random numbers can be associated with population items Objective results that can be defended mathematically are desired Auditor has insufficient knowledge of the population to justify non-statistical method. A representative (random) sample is required Staff are adequately trained in statistical auditing 5

6 Statistical sampling cont d Advantages Precise and definite approach to audit Evaluation shows direct relation between sample results and the entire population Auditors must specify and quantify risk and materiality judgments Does not eliminate professional judgment Allows more objective control of audit risks Better planning and documentation when properly implemented Non-statistical sampling Also called judgmental sampling Auditors do not use statistical calculations to express results Sample selection can be random or some other non-mathematical method Uses statistical risk without actually using statistical theory to measure the risk. Non-statistical sampling cont d Use when: Association of population items with random numbers is difficult and/or expensive Auditor s knowledge about population justifies it with an expectation of reasonable conclusion Representative sample is not required (for example, an account with 2 large transactions and a couple of immaterial transactions) Population is diverse with error prone segments 6

7 Non-statistical sampling cont d Advantages: Approach to audit can be less rigidly defined. Auditors can apply professional judgment based on factors additional to the sample evidence Need less detail on risk and materiality judgments Auditors can assert standards of subjective judgment 6.3 Sampling and non-sampling error Explain sampling error, including errors arising from alpha risk (Type 1 error), beta risk (Type II error), and nonsampling error. (Level 2) Sampling risk The risk that a sample may not be representative of the entire population. The error that results from sampling risk is the sampling error. Sampling risk is reduced by increasing sample size When using statistical sampling, sampling risk can be quantified (probability) 7

8 Sampling Error Auditor forms an incorrect opinion about the population based on the sample Occurs because auditor examines less than 100% of the population Two types of sampling error Type I and Type II Type I Error Auditor incorrectly concludes account balance is materially misstated when it is not or a control is ineffective when it actually is. Also called Alpha risk Consequence of Alpha risk is usually inefficiency in the audit (e.g. conclude controls are not effective leading to CR set to max and further substantive testing when not necessary) Type II Error Auditor incorrectly concludes account balance is fine when it is actually materially misstated. Also called beta risk The consequence of Beta risk is more concerning for auditor as it will result in no further testing therefore missing out on detection of material misstatement. 8

9 Non-sampling risk All risk other than sampling risk. Using the Audit risk model for understanding: AR = IR x CR x DR Non-sampling risk can arise from: Misjudging IR will do less work if mistakenly believes low inherent risk; may fail to detect problems Misjudging CR overly optimistic reliance on controls may lead to fewer audit procedures Poor choice of procedures and mistakes in execution related to DR; procedures inappropriate to objective confirm recorded A/R when objective is finding unrecorded A/R Failure to recognize an exception or error in a sample 6.4 Attribute sampling and tests of controls Outline the seven-step framework for conducting attribute sampling for tests of control. (Level 2) Statistical sampling for tests of controls For tests of controls, sampling risk is that auditor will incorrectly assess Control Risk (CR) because sample is not representative of the population Attribute sampling an attribute is a characteristic in which the auditor is interested in the case of tests of controls the attribute is whether or not the control failed. Deviations must be defined in advance so that they can be recognized and treated consistently 9

10 Test of Controls for Assessing Control Risk Sampling for test of controls is a structured, formal approach in seven steps: 1. Specify the audit objectives. 2. Define deviation conditions. 3. Define the population. 4. Determine the sample size. 5. Select the sample. 6. Perform the test of controls procedures. 7. Evaluate the evidence. Seven Step Framework 1. Specify audit objectives Auditor should identify key controls and limit audit work to key controls (remember materiality) 2. Define conditions for deviations Deviation, error, occurrence and exception are all synonyms in test of controls Clearly defining what constitutes a deviation helps reduce sampling risk 3. Defining the population Specifying the control test audit objectives and deviation conditions defines the population Sampling unit and population unit are same thing Defining population is important as your audit conclusion can only be made regarding the population the sample was selected from Population has same issue in that test of controls are usually done on interim basis when the whole population is not available must take into consideration time between interim and year end. 10

11 Physical representation of population must be complete and correspond with actual population (i.e. file drawer full of sales invoices is physical representation of I/S account for sales.) Must also be accessible cannot select sample from population where half the documents are stored off-site where they are not acessible. 6.5 Determining sample size and selecting the sample Describe the factors that influence sample size determination in attribute sampling, and determine the sample size for a test of controls using statistical sampling. (Level 2) 4. Determining the sample size Auditors must consider four factors in determining sample size Sampling risk the more you know about population the less of a chance for wrong conclusion Tolerable Deviation Rate (TDR) quite simply how many deviations is the auditor willing to accept within a given population page 397 gives example of 1% TDR being lowest acceptable material misstatement it would relate to a CR of As the Deviation rate increases so to does CR. The lower the Deviation rate and therefore CR, the larger the sample needs to be. TDR is determined by the decision on where to assess CR. 11

12 Step 4 cont d Expected Population Deviation Rate (EPDR) based on knowledge or judgment (prior year audit info, industry expectations) auditor may have an idea of how many deviations may exist. This is EPDR. Estimate of ratio of number of expected deviations to population size If last years deviation rate was 1%, this year s expected rate could be 1% which then produces a minimum sample size. EPDR must be less than TDR otherwise no reason to perform any tests of controls. Closer EPDR is to TDR, the large the sample needed to conclude that deviations do not exceed Tolerable rate. (Make sure I explain in plain language what this means...) EPDR some will put a number to this and others will not. Simplified approach does not quantify the EPDR results in effective rate of zero also results in smallest sample sizes possible Population size is the fourth factor in determining sample size Calculating sample size: Formula per text n=r/p where: n is sample size R is confidence level factor P is materiality level or upper limit rate auditor considers material for the population being tested 12

13 See exhibit 10-5 from text book for sample size relationships (page 398) Two key points where formulas and tables are used in statistical sampling are 1 sample size planning and 2- sample evaluation Dollar Unit Sampling is common as it is efficient can be used for tests of controls and substantive testing using same formula and table Back to the formula (keep in mind this whole module is level 2) For test of controls and substantive tests solve for n in the formula: R=nP Or R= CL R K where CL is Confidence level and K is acceptable number of errors. It is a unique Confidence level factor for each combination of confidence level(cl) and acceptable number of errors(k) see page 427 for R Value table P is also referred to as the UEL(upper error limit) We use professional judgment to specify K, CL and P. Step 5 select the sample Two important requirements 1. sampling units must come from population that audit conclusion will apply to 2. sample must be representative of population Random sample selection helps to ensure but does not guarantee representation because of sample risk Again sample risk is reduced by increasing sample size and randomness of sample selection 13

14 Different methods : Unrestricted random selection assign number to each sample unit and use Excel function RAND to randomly select numbers. Systematic random selection population and predetermined sample size a random starting point in physical representation is chosen then every kth unit is selected Non-random sampling Haphazard selection any unsystematic method of selecting sample units Block sampling choosing a set block of sample units (i.e. date range) 6.6 Evaluating test results Describe how the auditor evaluates the results of a test in the contexts of nonstatistical and statistical sampling. (Level 2) 14

15 Step 6 Performing test of controls audit procedures covered in later module (8 or 9) Step 7 Evaluating the test results Will either support or refute preliminary assessment. Number of deviations will help determine whether controls are reliable Auditor is concerned with Sampling risk as it relates to the risk of assessing control risk too low. Evaluate using table 15

16 Compute UEL for a given ARACR, sample size and number of deviations found in test of controls UEL is statistical calculation to estimate the population deviation rate. Sample deviation rate (deviations/sample size) may be higher or lower than population deviation rate Since we are concerned with assessing CR too low we want to know what the upper limit is so we can estimate how high the EPDR might be Non-statistical sampling doesn t calculate UEL; auditor uses professional judgment to consider sample error and extrapolate sample deviation rate to PDR. 16

17 6.7 Audit sampling for substantive testing Describe the nature of audit risk, sampling risk, and materiality in the context of substantive testing. (Level 1) Sampling for substantive testing is more related to AR (risk that auditor will issue an unqualified opinion when F/S are materially misstated) Sampling risk refers to probability the auditor will come to an incorrect conclusion about an account balance based on results of a sample from the population. Sampling error still Type I and Type II Type I or alpha risk of incorrect rejection Type II or beta risk of incorrect acceptance 17

18 Here we are now considering Tolerable Misstatement which is usually the same as overall materiality Risk model expansion yay! We now learn that DR is a factor of two risks analytical procedures risk (APR) and Risk of incorrect acceptance (RIA) APR probability that analytical procedures will fail to detect material errors RIA probability that test-of-detail procedures will fail to detect material errors DR = APR x RIA So, AR = IR x CR x APR x RIA Still a conceptual model Auditors use professional judgment to assess IR, CR, AR and APR Given these four factors, RIA can be determined 18

19 RIA = AR/(IR x CR x APR) With AR, IR and APR constant, RIA varies inversely with CR Also true with RMM since RMM=IR x CR 6.8 Sampling procedures for substantive testing Outline the seven-step framework for audit sampling in substantive testing, and explain how an auditor can use stratification to reduce sample sizes in audit sampling. (Level 2) Main objective in substantive testing is detecting a material misstatement in an account balance (balance sheet method) We have a similar seven step framework for determining sample size in substantive testing 19

20 Sampling Steps for Account Balance Audit 1. Specify the audit objectives. 2. Define the population. 3. Choose an audit sampling method. 4. Determine the sample size. 5. Select the sample. 6. Perform the substantive-purpose procedures. 7. Evaluate the evidence. Two main differences to the test of controls 7 step method: No need to identify conditions for deviation recorded dollar amount differs from audited amount Substantive method auditor must choose sampling method(in test of controls the only option is attribute sampling) Seven step Framework 1. Specify the audit objective concerned now more with balance sheet assertions Objective is to decide whether the client s assertions about existence, rights, and valuation are materially accurate. Hypothesis testing: auditors hypothesize that the book value is materially accurate and test that hypothesis. 20

21 Step 2. Define the population Since we deal with dollar values and we are looking at materiality CAS 530 requires us to evaluate if any population units should be separated from the population and audited independently Stratification is one method of subdividing population Example on whiteboard Step 3 Choose an audit sampling method Can use statistical or non-statistical If using statistical must choose between Variable (not covered in this course) or Dollar Unit Sampling (DUS) which is the most popular. Each dollar in a population is a population unit. If using non-statistical auditor uses professional judgment does not require all population units to have an equal chance of selection Usually targets larger dollar amounts and unusual transactions. Non-statistical sampling does not provide as good evidence when extrapolating results of the sample to the entire population 21

22 6.9 Determining sample size in substantive testing Describe the factors that influence sample size determination in substantive testing. (Level 2) Step 4. Determine Sample size First need decision criteria for RIA(Risk of incorrect Acceptance), RIR(Risk of incorrect Rejection) and Material misstatement Also estimate expected dollar amount of misstatement RIA Is a factor of AR, IR, CR and APR Varies inversely with combined product of the other factors Sample size varies inversely with RIA 22

23 RIR Is controlled by increasing sample size DUS deals with RIR by increasing sample size above minimum with K=0 (remember K= acceptable number of errors) Material misstatement usually same as overall materiality Expressed in dollar amount or as proportion of total amount Sample size varies inversely with amount of misstatement considered material Expected dollar misstatement estimated based on prior year audit or other knowledge Directly related to sample size 23

24 When population dollar values have larger range (e.g. $1 to $10,000) need a larger sample to make sure representative of population When using classical statistical sampling methods the population standard deviation must be estimated (not needed in DUS as each dollar is a separate unit so has equal value and therefore no variation) Sample sizes calculated same way n= R/P P now means materiality as a proportion of the recorded balance Step 5 Select the Sample Same as test of controls samples must be representative Unrestricted random selection and systematic selection DUS Haphazard and block same drawbacks as test of controls 24

25 6.10 Evaluating test results for substantive testing Explain how the auditor evaluates the results of a test in substantive testing. (Level 2) Step 6 - perform substantive-purpose procedures Covered in modules 8 and 9 Step 7 Evaluate the results of evidence obtained Evaluation is based on whether substantive-purpose audit procedures support or refute management assertions Quantitative evaluation 25

26 Total amount of actual monetary error is the Known Misstatement (or IM) Project the Known Misstatement to the population; this is the likely misstatement Compare the likely misstatement to the material misstatement for the account and consider the RIA (LM is less than MM) and RIR (LM is greater than MM) Must also consider: Sampling risks the less you know about a population (due to small sample) the greater the RIA or RIR Qualitative evaluation did you notice missing controls, misunderstanding of accounting principles, simple mistakes or carelessness, intentional irregularity or management override? How do these relate to other amounts (i.e. overstatements in A/R might mean overstatement in sales) What do these qualitative observations say about test of control areas? Dualpurpose testing they can confirm or refute conclusions of test of controls. 26

27 Evaluation of amount of misstatement Known misstatement and likely misstatement are combined and compared to materiality. Sample risk gives rise to possible misstatements. Misstatements that remain undetected in units not sampled. Can be calculated where statistical methods are used. Timing of Substantive Procedures Account balances can, in part, be audited at an interim date. Auditor will extend the interim date audit conclusions to balance sheet date. Audit work is performed at interim dates: to spread auditor s workload over the year, and to allow for timely production of audit report following year end. Poor controls, or significant business risk may preclude performing procedures at interim Dollar-unit sampling Describe and demonstrate the dollarunit sampling process to test an account balance. (Level 2) 27

28 Can be used for both testing of controls and substantive testing. Method for selecting sample Each dollar in a given population is an individual unit. Couple of things to remember about misstatements. Balances can be overstated remember this when you read about Upper error bounds Balances can also be understated remember this when you read about Lower error bounds Some downsides Populations with a zero recorded balance have no chance of being selected even though they may be misstated Small balances that are significantly understated have little chance of selection Negative numbers will not be selected 28

29 Assignment 2 due end of Module 7 Quiz this week Look at questions relating to this module to get an idea of what you may be asked as most of Module 6 is Level 2. Have a great week. if you have questions concerns mike@thorntonandco.com 29