CIA P2 Information Gathering, Analysis and Evaluation: practice questions with answers

Question 1

During a review of purchasing at Harlow Medical Supplies, the procurement manager explains in an interview that every supplier invoice is matched to an approved purchase order and a goods received note before payment. What should the internal auditor do next to obtain more reliable evidence that the process operates as described?

1. A Perform a walkthrough of actual invoices through the process, inspecting the matched documents at each step
2. B Ask the procurement manager to sign a written statement confirming that the description given in the interview is accurate
3. C Interview a second member of the procurement team and accept the description if both accounts agree
4. D Accept the description because the manager is the person accountable for the process and knows it best

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Answer: A. Inquiry (interviews) is a useful starting point but is the least persuasive form of evidence on its own. A walkthrough traces real transactions from start to finish, letting the auditor inspect the purchase order, goods received note and invoice and see the matching step performed. This corroborates the manager's description with documentary and observational evidence and confirms the auditor's understanding of the process and its controls.

Question 2

An internal auditor is planning an attribute sample to test whether shipping documents are matched to sales orders. Holding all other factors constant, which change will increase the required sample size?

1. A A decrease in the tolerable deviation rate
2. B An increase in the acceptable risk of over-reliance on the control
3. C A decrease in the expected population deviation rate
4. D An increase in the tolerable deviation rate

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Answer: A. Attribute sample size increases when (1) the tolerable deviation rate decreases, (2) the acceptable risk of over-reliance decreases (higher confidence), or (3) the expected deviation rate increases. Population size has only a small effect unless the population is small. Therefore a lower tolerable deviation rate is the only change listed that increases the sample.

Question 3

At Asterley College, purchase orders above $10,000 require a second approval. Which data analytic is best designed to identify staff who may be splitting purchases to avoid the second approval?

1. A Identify purchase orders where the same purchase order number has been recorded more than once in the system
2. B Compare supplier names, addresses and bank details with the data held in the employee master file
3. C Group orders by requester, supplier and short period, flagging sub-$10,000 orders whose total exceeds $10,000
4. D Test the purchase order number sequence for gaps, missing numbers and numbers out of range

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Answer: C. Split purchasing means breaking one requirement into several smaller orders so that each stays within a lower approval limit. An analytic that groups orders by requester, supplier and date window, and flags clusters of individually sub-threshold orders whose combined value exceeds the limit, targets this behavior. A frequency check of orders falling just under $10,000 can support it. Flagged clusters are then followed up, since some may be legitimate separate needs.

Question 4

Internal audit at Northwick University is designing a staff survey about a new procurement system. One draft question reads: 'Do you agree that the new system is faster and easier to use than the old one?' What is the main problem with this question?

1. A It is open-ended, so the answers will be difficult to summarize across a large number of responses
2. B It is leading and asks about two things at once, so the answers may be biased and hard to interpret
3. C It does not name the system supplier, so staff may be unsure which system the question refers to
4. D It asks for staff opinions, which are not appropriate for an internal audit survey to collect

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Answer: B. A good survey question is neutral and asks about one thing. This draft is a leading question ('Do you agree that…') and a double-barreled question (speed and ease of use). Respondents who find the system fast but hard to use cannot answer accurately. Better wording would be two separate, neutral questions, such as 'How does the time needed to raise an order compare with the old system?' with a balanced response scale.

Question 5

To test the pricing logic of the billing system at Hamblin Telecom, internal audit sets up a fictitious business customer in the live system and processes test calls for it alongside real customer activity. What is the main risk this technique must manage?

1. A The technique cannot test the billing system as it actually operates in the live production environment
2. B Test transactions could distort live records and reports unless they are flagged and reversed
3. C The technique requires all production data to be copied into a separate test environment
4. D The technique can test only transactions that were processed in earlier periods

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Answer: B. This is an integrated test facility (ITF): a dummy entity is created within the production system and auditors process test transactions through it with live data. It shows how the actual programs in use handle the test cases. Its main risk is contamination of live data, such as revenue, receivables and management reports, so ITF transactions must be clearly identified and reversed or filtered out, with management aware of the arrangement.

Question 6

An internal auditor is developing an expectation of annual revenue for a chain of 30 fitness clubs owned by Tolland Active. Which approach is likely to give the most precise expectation?

1. A Compare total revenue for the whole chain with the total recorded for last year
2. B Apply the industry's average revenue growth rate to last year's total revenue
3. C Use the revenue budget that management prepared and approved at the start of the year
4. D Model each club's monthly revenue from tested membership data and current fee rates

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Answer: D. The precision of an analytical expectation improves when (1) the data are disaggregated (by location and month rather than in total), (2) the expectation is based on plausible, predictable relationships with underlying drivers (memberships x fees), and (3) the input data are reliable (for example, membership data from a tested system or an independent source). A precise expectation makes it more likely that a significant misstatement or irregularity will show up as a difference.