Performing Further Procedures & Obtaining Evidence (30-40%) Flashcards
What are some key things to understand when evaluating whether audit evidence is ‘sufficient’ and ‘appropriate?’
SUFFICIENT - relates to QUANTITY of audit evidence obtained - based on assessed levels of risk & quality of evidence gathered
APPROPRIATE - relates to QUALITY of audit evidence obtained
CONSIDERATIONS FOR QUALITY OF EVIDENCE:
- highly reliable when obtained from independent sources outside entity (confirmations)
- more reliable for auditor to rely on controls pertaining to evidence, when audit evidence obtained internally from client
- higher quality when obtained directly from auditor (ex: observing controls operating effectively vs. asking EE if they perform control)
- hard copy is more reliable than conveyed orally (looking at document vs. someone telling you something happened)
- higher quality when original document vs. copy
What are the sampling techniques?
ATTRIBUTE sampling:
- used to perform TEST of CONTROLS
- looking at transactions to determine if control was performed or not
- assess RMM too low - audit ineffective
- assess RMM too high - audit inefficient
VARIABLE sampling:
- used for SUBSTANTIVE testing of populations, usually to test an ending balance in an account
What are the steps for attribute sampling? for variable sampling?
ATTRIBUTE sampling - steps:
- identify what objective of test is
- define what a deviation is based on test
- define & acquire population
- choose sampling method (statistical-random or judgmental-haphazard/arbitrarily selecting)
- choose sampling size
- test transactions & deviations
- calculate deviation/tolerable deviation rates and a confidence interval
- upper precision limit compared to deviation rate (can only rely on internal controls if deviation rate is less than/equal to stated tolerable rate)
- decide if any other factors have implications on decision to rely on or not (if not & DR is lower than TR, will rely on)
*population size has little/no effect on sample size, however, tables for sample size are based on assumption of very large populations
**VARIABLE sampling - steps - essentially the same as above, except that transactions will be dollar amounts - auditor tests all transactions that are individually material (not being sampled - tested 100%)
What is the formula for accept/modify questions?
sample error rate (SER) - number of deviations actually found in sample (3 deviations in 100 - sample size error rate of 3%)
then, add the ‘allowance for sampling risk’ (ASR) rate to ‘sample error rate’ to get your ‘upper error limit’ (UEL) - if ASR is 2%, you add this to SER found, which would give you 5% UEL in this example
then, compare this UEL to your tolerable rate (TR) - if TR was 5%, you can rely on IC - if TR was 4%, you need to modify planned level of control risk (cannot rely on IC)
. SER + ASR = UEL UEL < / > TR -if UEL < TR = can rely -if UEL > TR = cannot rely
What is the basic formula for calculating a sample size? and what are the elements within?
n = sample size SD = estimated standard deviation Z = is the Z-coefficient is the measure of reliability for population N = size of population A = allowance for sampling risk
[ SD x Z x N ] ^2 n = [ ---------------- ] [ A ]
What is stratification?
separating a population into groups of transactions that are similar - such as, transactions over a certain dollar amount
stratifying a population can decrease a sample size
What are some other concepts?
- increase in TR (tolerable misstatement) would decrease sample size & vice versa - if more mistakes are allowed, sample size can be smaller - if less mistakes are allowed, larger sample size needs to be tested to gain assurance a lower number of mistakes exist
- if assessed level or control risk increases, sample size needs to be larger & vice versa - auditor thinks a population has a high risk of material misstatement, then sample size will be larger
- falsely conducting that a material misstatement does not exist based on a sample is ‘incorrect acceptance’ - this is a type 2 error
How does Observation & Inspection work for testing operating effectiveness of controls?
- observing the control in action
- inspecting documents for indications that control has been performed
steps:
- auditor asks EE - how does this control work?
- EE explains steps of process
- auditor documents how EE says control is supposed to work
- auditor randomly selects number of transactions that should have gone through control being tested
- find the original documents & inspect them
- if no deviations, auditor can rely on
- if more deviations found than acceptable amount, auditor concludes controls are weak & requires additional substantive testing (not rely on)
How does Recalculation & Reperformance work for testing operating effectiveness of controls?
recalculating a figure to test for accuracy (common ex: recalculating depreciation expense to verify its accuracy)
auditor re-executes a control/procedure that was originally performed by EE to see if get same result - done manually or through computer-assisted techniques
What are Analytical Procedures? How are they used?
evaluations of financial information based on relationships among both financial data and non-financial data
- used in planning (preliminary) strategy (required)
- used as substantive procedures (not required)
- used in final review (required)
- usually do all 3
What are factors to consider when deciding how to use analytics to test an assertion?
- does nature of assertion lend itself to analytical procedures?
- is there plausible & predictable relationship?
- is data used to develop the expectation reliable?
- is the expectation precise?
*some assertions can be tested solely through analytics, others require combination of analytics & test of details, or some might not need analytics
What are 5 factors used to develop an expectation?
- comparable information from a prior period (if sales increased by similar % in past 3 years, expect similar in CY)
- anticipated results of entity from budgets/forecasts (if management forecasted sales of $50K at BOY, auditor would expect sales close to at EOY)
- similar industry information such as ratios compared to industry averages (gross margin % compared to its industry averages/benchmarks)
- relationship between elements of financial information (if sales increased certain %, similar increase in AR expected)
- relationship between financial and non-financial information (payroll costs compared to # of EEs)
How are Analytical Procedures used in the Planning Stage?
auditor will use high-level analytics
- looking at quarterly reports
- unaudited financial information provided by client
makes analytical comparisons as a starting point for identifying areas to take a closer look
ex: comparing CY sales to PY sales for significant changes
focus in planning stage - use analytics to enhance auditor’s understanding of business & transactions that have happened since the last audit
How are Analytical Procedures used in the Final Review Stage for forming overall conclusions?
wide variety of analytical procedures may be used when forming overall conclusions
- reading FS
- considering the adequacy of evidence gathered in response to unusual/unexpected balances identified during course of audit & unusual/unexpected balances or relationships that were not previously identified
results may indicate additional evidence is needed
analytics should be performed by manager or partner that has comprehensive knowledge of clients business & industry
What are External Confirmations?
sent by auditor to third party, in order to confirm a balance/transaction that they have or have had with company being audited
auditor controls the requests & responses, or it defeats the purpose of trying to confirm with third party
best addresses assertions of existence & occurrence
3 types of confirmation requests:
- POSITIVE - asking for response whether or not third party agrees on amount (if not enough responses received, auditor will perform alternate procedures - AR: look at cash receipts, AP: look at cash disbursements)
- NEGATIVE - only asks for response if third party disagrees with amount (less reliable than positive)
- BLANK - asks third party to fill in information/amounts
What is ADAs (Audit Data Analytics)?
the science & art of discovering & analyzing patterns, identifying anomalies, & extracting other useful information in data underlying or related to subject matter of an audit through analysis, modeling, & visualization for the purpose of planning or performing the audit
ADAs can be used during risk assessment or for substantive procedures at relevant assertion level
What are the 5 steps of ADAs (Audit Data Analytics)?
1) PLAN - plan the ADA
2) ACCESS & PREPARE - access & prepare data for purposes of the ADA (will prepare data using ETL process-extract, transform, load)
3) CONSIDER - consider relevance & reliability of data used (characteristics data should have)
4) PERFORM - perform the ADA (identify any notable items)
5) EVALUATE - evaluate the results (have objectives been achieved? + document procedures performed & results of)
