Burlingham Bees 1. AU 329 a. Based on the standards, describe the guidelines for developing an expectation and conducting analytical procedures when those procedures are intended to provide substantive evidence (para. 9-22). i. .09 Reliance on substantive tests: may be derived from tests of detail, from analytical procedures, or from a combination of both. The decision about which procedure to use is based on the auditor’s judgment. ii. 10 Level of assurance: analytical procedure may provide effective level of assurance for some assertions, but some of the assertions may be more effective to reach desired level of assurance by using test of details. iii. .11 Identifying potential misstatement: identifying potential misstatement depends on: 1. The nature of assertion .12 Analytical procedures may test for assertions in which potential misstatements would not be apparent from an examination of the detail evidence or in which detailed evidence is not readily available. 2.
The plausibility and predictability of the relationship . 13 Reasons of making relationship plausible are that data sometimes appear to be related when they are not and sometimes an unexpected relationship can provide important evidence when appropriately scrutinized. .14 More predictable relationships are required to develop the expectation as higher levels of assurances are desired from analytical procedure. i. Relationships in a stable environment are more predictable. ii. Relationships involving income statement accounts are more predictable than relationships involving only balance sheet. ii. Relationships involving transactions subject to management discretion are sometimes less predictable. 3. The availability and reliability of the data used to develop the expectation . 15 To test completeness assertion, expected sales for some entities might be developed from production statistics or square feet of selling space. .16 The consideration of reliability of data is based on: i. Whether the data was obtained from independent sources ii. Whether sources within the entity were independent of those who are responsible for the amount being audited. iii.
Whether the data was developed under a reliable system with adequate controls. iv. Whether the data was subjected to audit testing in the current or prior year. v. Whether the expectations were developed using data from a variety of sources. 4. The precision of the expectation .17 The expectation should be precise enough to provide the desired level of assurance . 18 Many factors can influence financial relationships. More effective identification of factors that significantly affect the relationship is generally needed as the desired level of assurance from analytical procedures increases. iv. 20 In planning the analytical procedures as a substantive test, the auditor should consider the amount of difference from the expectation that can be accepted without further investigation. v. .21 The auditor should evaluate significant unexpected differences. vi. .22 When an analytical procedure is used as the principal substantive test of a significant financial statement assertion, the auditor should document all of the following: a. The expectation, where that expectation is not otherwise readily determinable from the documentation of the work performed, and factors considered in its development. . Results of the comparison of the expectation to the recorded amounts or ratios developed from recorded amounts c. Any additional auditing procedures performed in response to significant unexpected differences arising from the analytical procedure and the results of such additional procedures. b. What are the advantages of developing an expectation at a detailed level (i. e. , using disaggregated data) rather than at an overall or aggregated level? .19 Expectations developed at a detailed level generally have a greater chance of detecting misstatement of a given amount than do broad comparisons.
Monthly amounts will generally be more effective than annual amounts and comparisons by location or line of business usually will be more effective than company-wide comparisons. The level of detail that is appropriate will be influenced by the nature of the client, its size and its complexity. Generally, the risk that material misstatement could be obscured by offsetting factors increases as a client’s operations become more complex and more diversified. Disaggregation helps reduce this risk. 2. ) Develop a precise expectation, using the detailed or disaggregated data provided, for ticket revenues for the 2008 fiscal year. Weekend 25% more than weekday: X= weekday attendance per game 1. 25 X = weekend attendance per game 10% more attendance with promotion Weekday attendance= (7*1. 1*X)+(43-7)*X=43. 7 X Weekend attendance= (10*1. 25X*1. 1)+(29-10)*1. 25X=37. 5X Attendance equation= [(7*1. 1*X)+(43-7)*X]+[(10*1. 25X*1. 1)+(29-10)*1. 25X]=434348=total attendance X= =434348/81. 2=5349. 1133 43 + 29 = 72 games in 2008. 434348/72 = 6,032 people per game 6032 X . 5 = 1508 1508 + 6032 = 7540 ( 25% increase in weekend games) 7540 (29) + X (43) = 434348 X = 5016 (avg. attendance per weekday game) total sales per weekday game: 5,016 * . 30 = 1,504. 8 * 10 = 15,048 5,517. 6 * . 30 = 1,655. 28 * 10 = 16,552. 8 5,016 * . 35 = 1,755. 6 * 6 = 10,533. 6 5,517. 6 * . 35 = 1,931. 16 * 6 = 11,586. 96 5,016 * . 20 = 1,003. 2 * 4 = 4,012. 8 5,517. 6 * . 20 = 1,103. 52 * 4 = 4,414. 08 5016 * . 15 = 752. 4 * 2 = 1,504. 8 5,517. 6 * . 15 = 827. 64 * 2 = 1,655. 28 $31,099. 2 34,209. 12 31,099. 2 * 36 + 34,209. 12 * 7 = $1,359,035. 04 for all weekday games otal sales per weekend game: with promotions: 7,540 * . 25 = 1,885 * 10 = 18,850 8,294 * . 25 = 2,073. 5 * 10 = 20,735 7,540 * . 30 = 2,262 * 6 = 13,572 8,294 * . 30 = 2,488. 2 * 6 = 14,929. 2 7,540 * . 25 = 1,885 * 4 = 7,540 8,294 * . 25 = 2,073. 5 * 4 = 8,294 7,540 * . 20 = 1,508 * 2 = 3,016 8,294 * . 20 = 1,658. 8 * 2 = 3,317. 6 42,978 47,275. 8 42,978 * 19 + 47,275. 8 * 10 = $1,289,340 for all weekend games expected ticket revenue: 1,359,035. 04 + 1,289,340 = $2,648,375. 04 b) Assess the reliability of each data item you used to develop your precise expectation. i.
Park attendance: park attendance data is reliable because the data is obtained from an independent sources—the 3rd party, Tickets R Us. ii. Number of games: number of games is reliable because the source and condition of the information is public. iii. Per-Game Ticket prices: Ticket price data is reliable because the source and condition of the information is public. iv. Sales mix: Sales mix data is reliable because it has remained fairly constant over the last several years. v. Number of games promotions: Reliable. Data is reliable because the source and condition of the information is public. ) Develop an expectation using the aggregated data provided. ** vi. 2007 ticket revenue is $2. 2 million, and 2008 cumulative season attendance is 10% more than prior season. 2008= 2. 2 *1. 1= $2. 42 million vii. Ticket price increase 10% in 2008 Therefore, the expected ticket revenue is 2. 42*1. 1=$2. 66 million d) Which expectation do you believe is more reliable? Why? Expectation developed at a disaggregated level is more reliable because a greater detail provides a greater chance of detecting misstatement of a given amount than do broad comparisons. . (a) How close does the Bees’ reported ticket revenue for 2008 have to be to your expectation for you to consider reported ticket revenue reasonable or fairly stated? (Hint: You need to compute your materiality threshold. Use net income before taxes as the base. ) Assume Hickman and Snowden’s materiality guidelines are: * Combined misstatements in the income statement should ordinarily be measured at 3% to 6% of operating income before taxes. * Tolerable misstatement for any account cannot exceed 60% of preliminary judgment.
The 2008 Burlingham Bee’s net income before tax is $480,100 480,100 * 3% = 14,403 (60% = $8,642) 480,100 * 6% = 28,806 (60% = $17,284) 2008 unaudited ticket revenue is $2,580, 420 Expectation ticket revenue is $2,592,662 Difference: (2592662-2580420) = $12,242 As the difference of reported and expectation revenue is less than 60% of preliminary judgment, the reported ticket revenue is fairly stated. (b) Ignoring your answer to Part 3 (a), assume that reported ticket revenues are outside your “reasonableness range. ” What could explain the difference?
If the reported ticket revenues are outside our reasonable range, there are several factors that could be used to explain the difference. First, the allocation of tickets for the weekend and weekday games could have been different than the actual tickets sold for each day. To calculate this number, we just assumed the average per day was the same before accounting for increases in ticket sales due to promotions. Another factor that could explain for the difference is weather conditions. Obviously, when the weather is bad, people are less likely to attend games.
Because our data does not account for the decrease in ticket sales on days which had bad weather, this could also be an explanation for our reported ticket revenues being outside of our reasonableness range. Another factor that could explain the difference is lost ticket sales or double counting of tickets. 4. (a) What are the advantages of using analytical procedures as substantive tests? (b) If the engagement team decides to use analytical procedures for the Bees’ audit, how will the audit plan differ from prior years? (c) Discuss whether you believe analytical procedures should be used as substantive tests for the Bees 2008 audit?