Case 4: Souper Bowl Inc.
You were recently promoted to audit senior at your firm, Buckeye CPAs LLP, and one of your primary
clients is Souper Bowl Inc. Souper Bowl (‘‘the company’’) is a privately held business headquartered in
Maine, and has a fiscal year-end of December 31. The company has been in business for nine years and
prides itself on offering creative soups at a reasonable price and that are made with locally sourced
ingredients. The most popular soups include sweet potato corn chowder, curried root vegetable and lentil,
and maple-roasted butternut squash. Souper Bowl typically experiences increased sales during winter
months since soup hits the spot on a cold and snowy day. To further encourage sales on days when
customers often avoid venturing outside, the company provides a delivery service and guarantees that
soup can be delivered to anyone no matter what the weather. The company found this strategy to be
particularly successful in 2015 when New England (including Maine) experienced record snowfall during
February and March.
Souper Bowl sells their soup at several restaurant locations throughout Maine. The company employs
three managers that direct the day-to-day operations for a group of stores that are organized by
approximate geographic region: northern Maine (Store Type 1), mid-Maine (Store Type 2), and coastal
Maine (Store Type 3). Appendix A provides a map of these store locations. Each manager knows their
local market well and has the flexibility to advertise and offer promotions with the overall goal of
increasing sales year over year. If total sales at the end of the year exceed total sales from the prior year
for that manager’s set of locations (i.e., ‘‘Store Type’’), then the manager earns a monetary bonus from
An audit of the company is required to comply with debt covenants related to a large bank loan that the
company entered into when it began operations. Specifically, Souper Bowl must provide audited annual
financial statements to the bank within 90 days of the fiscal year-end. The company must also provide
unaudited quarterly financial statements to the bank within 45 days of the end of each quarter. The debt
contract includes a financial covenant that requires pre-tax income in each quarter to be greater than zero.
If not met, the bank has multiple remedies at its disposal, including calling the loan such that the entire
balance is due immediately, seizing the company’s assets that are posted as collateral, or providing a
waiver for the violation. Souper Bowl’s net income for the year ended December 31, 2016 is $468,810,
while net income for the prior year ended December 31, 2015 was $825,229.
As part of your new role as audit senior, you will be performing a large portion of the planning and
testing of sales for the 2016 audit of Souper Bowl. AU-C Section 240.26 states that ‘‘when identifying
and assessing the risks of material misstatement due to fraud, the auditor should, based on a presumption
that risks of fraud exist in revenue recognition, evaluate which types of revenue, revenue transactions, or
assertions give rise to such risks.’’ During planning for the audit, the partner and manager determined that
the following three management assertions represent significant risks for revenues:
(1) recorded sales occurred;
(2) sales are accurately recorded; and
(3) sales are recorded in the proper period.
In prior years, the audit approach relied on random sampling to test revenues. However, the partner
wanted to develop more focused procedures in the current year to hone in on potentially riskier sales
transactions. As a result, the plan is to perform disaggregated sales analytics to identify unusual trends in
the daily sales data with the goal of identifying sales on specific days at specific store locations that
Case 4: Souper Bowl Inc.
should be subjected to substantive testing due to heightened risks. The remainder of the population would
then be sampled using a random sampling approach.
Based on your experience from prior audits, you know that Souper Bowl’s daily sales fluctuate with
temperature and snow accumulation. To perform your revenue analytics, you request a file from the client
that includes daily sales by store location for both 2016 (current year) and 2015 (prior year). You also
retrieve daily weather data from the National Oceanic and Atmospheric Administration’s (NOAA)
website for the weather centers closest to Souper Bowl’s store locations. Total revenue for the current
year ended December 31, 2016 is $18.8 million, while total revenue for the prior year ended December
31, 2015 was $19.1 million. The audit team’s workpapers include the following lead sheet for revenue
testing, and the total balances for each year agree to the trial balance and the company’s draft financial
statements for 2016.
Your manager stated that your firm recently adopted a data visualization tool and she suggested that you
use it to perform these sales analytics. Since she is busy overseeing the planning and testing of other audit
areas, she wants you to take the first pass and then document your results in a memo for her review. The
manager wants you to provide thoughtful analyses and a thorough exploration of the possible
relationships in the data. You are eager to impress her with your work, especially following your recent
promotion to senior.
1. Auditing standards specifically require auditors to identify revenue recognition as a fraud risk in
most audits. Based on your understanding of the company, what factors may increase the risk of
fraudulent financial reporting in Souper Bowl’s 2016 revenues?
2. Use the daily sales by location as provided by the client (2016 and 2015) and the weather data
from NOAA to perform disaggregated sales analytics. Your goal is to develop visualizations that
identify potential outliers in the 2016 daily sales data related to the significant risks identified by
the partner and manager. Document your analyses and conclusions as to the specific daily sales
from certain locations that you recommend selecting for focused substantive testing. These
should be documented in a memo for the audit file.
Note: Your conclusion needs to be precise enough to pull specific transactions—for example, you would
not list the ‘‘month of March’’ in store 1010 because this would result in too many observations to
feasibly test. Also, you should not recommend testing observations from 2015. Your engagement team
completed that audit in the prior year—instead, you are using 2015 data as a component of your baseline
prediction for 2016.
Case 4: Souper Bowl Inc.
Appendix A: Map of Store Locations for Souper Bowl Inc.
THE MEMO BELOW IS A TEMPLATE FOR QUESTION #2.
There is no template for Question #1.
EXAMPLE MEMO TEMPLATE
Souper Bowl Inc.—December 31, 2016
Disaggregated Revenue Analytics
Purpose: The purpose of this memo is to document plausible trends and expectations for disaggregated revenue data and to identify specific days and locations that warrant further substantive investigation.
Data: I obtained a listing of daily sales by location from the client’s IT system. I tested the details for mathematical accuracy, as summarized in the table below:
Total Sales, 2015
Total Sales, 2016
Store Type 1
Store Type 2
Store Type 3
Procedures: Based on my risk assessment process, I identified the following assertions as significant risks related to revenues/sales:
Because Souper Bowl’s operations are solely in the state of Maine, I obtained disaggregated data that reports daily sales by store location and store type. Based on discussions with management and my review of the board of director minutes, I am unaware of any new store locations or other major changes to operations during the year. Therefore, I expect the prior year to be a reasonable baseline expectation for this year’s revenues (e.g., similar seasonal trends). Because the business can also be impacted by weather conditions, which varies by year, I also perform analyses that consider changes in weather patterns to predict expected changes from the prior year’s sales. I performed several analytics to identify unusual trends compared to the prior year’s sales, taking weather conditions into consideration. The purpose of these analytics is to identify specific observations (or specific sets of observations) to select for further substantive testing. The analytics that I performed are as follows:
[Provide a description of the relationship you expected to observe in the data, along with screenshots of the visualization results. Clearly identify (using circles, arrows, etc.) the part of the visualization that leads you to believe that a specific location/day is an anomaly. Ensure that all tables and graphics are properly labeled (x axis, y axis, etc.).]
Conclusion: Based on the procedures described above, the audit team will pull supporting sales information to substantively test transactions from the following locations and days: