Sas 99 fraud risk factors

Tesla Case (High Quality, Grad-Level)

ISSUES IN ACCOUNTING EDUCATION American Accounting Association Vol. 33, No. 2 DOI: 10.2308/iace-51973 May 2018 pp. 19–34

Fraud Risk Brainstorming at Tesla Motors

Megan F. Hess Washington & Lee University

Lindsay M. Andiola Virginia Commonwealth University

ABSTRACT: This instructional case offers students the opportunity to explore the fraud risk assessment process and participate in a simulated fraud brainstorming session as required by AS 2401 (formerly SAS 99) for financial statement audits. Drawing on publicly available information about Tesla, Inc. (formerly Tesla Motors), the revolutionary company behind the popular Model S all-electric vehicle, the case materials guide students through multiple learning objectives. These objectives include learning how to: (1) recognize the factors that contribute to financial statement fraud risk; (2) identify and evaluate the likelihood and severity of fraud risks; (3) analyze the ways that fraud risks can lead to material misstatements in the financial statements; (4) understand the purpose of and how to conduct a fraud brainstorming session; and (5) develop audit procedures that respond to assessed fraud risks. In a post-case learning assessment, students reported significant improvement in their knowledge, comprehension, and application of these learning objectives. Students also indicated that they enjoyed learning about these concepts in the context of this popular company. This case has both an individual and a group component, and it is designed for use in an auditing or forensic accounting course at either the undergraduate or the graduate level.

Keywords: fraud risk factors; fraud triangle; brainstorming session; fraud risk matrix; AS 2401; SAS 99.

INTRODUCTION

O ne of the most important skills needed by accountants today is the ability to analyze and detect fraud risks (Carpenter

2007; Center for Audit Quality [CAQ] 2010; PricewaterhouseCoopers [PwC] 2015). The Association of Certified

Fraud Examiners (ACFE 2016) estimates that the typical organization loses 5 percent of its revenues every year to

fraud. Beyond these losses, financial statement frauds also have far-reaching negative consequences on investors, employees,

suppliers, and other stakeholders of the corporation. Because of the importance of fraud detection to the integrity of our

markets, auditing standards (i.e., Public Company Accounting Oversight Board [PCAOB] 2016a, 2016b, AS 2401; American

Institute of Certified Public Accountants [AICPA] 2006, AU Section 316; International Federation of Accountants [IFAC]

2008, ISA 240) require that accountants fulfill their responsibility to obtain reasonable assurance that the financial statements

they audit are free of material misstatement due to error or fraud. In particular, Auditing Standard (AS) 2401 (formerly

Statement on Auditing Standards No. 99), Consideration of Fraud in a Financial Statement Audit, requires that fraud risk brainstorming sessions be incorporated into every audit engagement. These sessions are designed to increase the probability

that auditors will detect intentional misstatements and to help set the right tone for professional skepticism and heightened

sensitivity to fraud risk throughout the engagement (Ramos 2003).

YOUR TASK

This case requires you to imagine that you have been asked to participate in a fraud risk brainstorming session as part of

the planning procedures for the 2016 financial statement audit of Tesla Motors. This case has two parts. In Part I, you will read

We thank Allen D. Blay (associate editor) and two anonymous reviewers for their valuable input and guidance. We also thank Mary Durkin, Jared Eustler, Gary Sullivan, and Kim Westermann, as well as participants at the 2016 AAA Forensic Section Midyear Meeting for their feedback and assistance. Finally, we thank Anthony Williams for his research assistance.

Supplemental materials can be accessed by clicking the links in Appendix B.

Editor’s note: Accepted by Valaria P. Vendrzyk.

Submitted: March 2016 Accepted: November 2017

Published Online: November 2017

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background information on Tesla Motors, learn how the concept of the ‘‘fraud triangle’’ is used to identify fraud risk factors,

and work to complete the Part I case requirement questions designed to help you identify some of the financial statement fraud

risks associated with this company.

In Part II, you will learn how to conduct a fraud risk brainstorming session and how to adapt your planned procedures to

respond to identified fraud risks. After reading Part II, you will work as part of an audit team to conduct a fraud risk

brainstorming session. During this session, your team will be responsible for completing a fraud risk matrix and writing up a

memo for the audit file that documents the results of your fraud risk assessment and identifies how your team believes the

nature, timing, and extent of the audit procedures should be altered to respond to these identified risks.

It is important to note that as of September 2017, Tesla Motors has not been accused of financial statement fraud.

Nevertheless, you and your team should resist the natural inclination to presume that management is honest, and exercise

professional skepticism in evaluating fraud risks at this company. Auditing standards remind us that we should conduct the

engagement with a mindset that recognizes the possibility that a material misstatement due to fraud could be present, regardless

of any past experience with the entity and regardless of the auditor’s belief about management’s honesty and integrity (PCAOB

2016a).

PART I

Tesla Motors Case Background

Founding and History of Tesla Motors

Tesla Motors (NASDAQ: TSLA) was founded in 2003 by a group of engineers in Silicon Valley with the vision of

accelerating the world’s transition to sustainable transport. To that end, Tesla Motors has created ‘‘cars without compromise’’—

that is, all-electric vehicles that offer all of the torque, power, and style of high-end automobiles with none of the emissions.

The company’s mission is ‘‘to accelerate the advent of sustainable transport by bringing compelling mass market electric cars to

market as soon as possible’’ (Tesla Motors 2015). Tesla’s first release was the Roadster in 2008, which offered 0 to 60 mph

acceleration in 3.7 seconds and a range of 245 miles per charge of its lithium-ion battery. In 2012, Tesla launched the Model S,

a four-door sedan that was named Motor Trend’s 2013 Car of the Year. At the beginning of 2016, with more than 107,000 vehicles on the road worldwide, Tesla’s product line expanded to include the Model X, a crossover vehicle that entered volume

production at the end of 2015, and the Model 3, a lower-priced vehicle with an expected release in 2017. However, Tesla does

not limit its vision to only automobiles. The company is described as ‘‘a technology and design company with a focus on

energy innovation’’ (Tesla Motors 2016b).

Tesla has revolutionized the automobile industry in many ways. In addition to proving that all-electric vehicles can

perform as well, if not better than, gas-powered vehicles, Tesla has challenged the conventional approach of how vehicles

are sold. Rather than selling through dealership franchises, Tesla sells and services its vehicles through its own network,

including acceptance of online orders. To help establish the value of the Tesla brand and encourage early adopters to buy

their vehicles, Tesla offers ‘‘resale value guarantees’’ to customers. Under this program, customers have the option of selling

their vehicle back to Tesla Motors during the period of 36 to 39 months after delivery for a pre-determined resale value

(Tesla Motors 2016b).

Due to widespread publicity and generally positive reviews of the vehicles, Tesla has enjoyed greater demand for its

vehicles than it can fulfill. As such, the company has been collecting deposits from customers at the time they place an order for

a vehicle and, in some locations, at certain additional milestones up to the point of delivery. In addition, a closer look at Tesla’s

income statement reveals that Tesla sells much more than just cars. Tesla also earns revenue from related services, including

access to its Supercharging network and software updates on the vehicles. Tesla also earns revenue from the sale of regulatory

credits from energy tax credits and from the sale of components to other manufacturers. Finally, Tesla earns revenue from

‘‘Tesla Energy,’’ a division of the company offering battery-powered energy solutions for home, businesses, and utilities (Tesla

Motors 2016b). Tesla’s income statement and balance sheet for the past three years are presented in Exhibit 1 and 2,

respectively.

Tesla launched an initial public offering in June 2010 that raised $226 million in equity. At the time, the company

employed less than 1,000 employees and had less than $150 million in revenue. The company has since experienced rapid

growth. During the period 2011–2015, revenues have grown more than 1,000 percent from $204 million in 2011 to $4.1 billion

in 2015. After several years of trading between $22 and $33 per share, Tesla’s surprise announcement of quarterly profits in

2013 drove the stock into the triple-digits (Taylor 2013). In March 2016, the company enjoyed a market capitalization of

almost $30 billion and traded at about $200 per share. Tesla Motors stock performance for the period 01/01/2014 to 03/31/2016

is provided in Exhibit 3.

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Tesla’s Leadership

Tesla Motors is led by CEO and co-founder Elon Musk. Mr. Musk made his fortune as a co-founder of PayPal, which was

acquired by eBay in 2002 for $1.4 billion. He is also the CEO of Space Exploration Technologies Corp., better known as

SpaceX, a company that aims to develop the world’s first private spacecraft for commercial space travel, and he is chairman of

the board of SolarCity Corporation, a company that aims to expand the availability of clean, affordable energy. A self-made

man and serial entrepreneur, Mr. Musk’s innovations and charisma have earned him the reputation as a ‘‘real-life Iron Man’’ in

reference to the Marvel Comics super hero (Smith 2014).

Mr. Musk is known for his bold vision and his even bolder proclamations. In a live interview in 2009, he called a New York Times journalist that wrote a critical review of Tesla an ‘‘idiot’’ (https://www.youtube.com/watch?v¼rwDU–NPqZ0; see also, http://www.businessinsider.com/elon-musk-calls-times-writer-a-huge-douchebag-and-an-idiot-video-2009-4). In an early 2015

earnings call with analysts, Mr. Musk also declared that he thought Tesla’s market capitalization could rival Apple Inc.’s $700

billion in the next ten years, which would be more than the market capitalizations of Ford Motor Company, General Motors

Company (GM), Honda Motor Company, Ltd., Toyota Motor Corporation, BMW, and Mercedes-Benz combined. Mr. Musk

made this declaration in the face of production delays, weakening market conditions, and falling gas prices, which has

traditionally made the sale of electric cars more difficult.

Tesla’s future prospects appear to depend on Mr. Musk’s ability to achieve feats that other carmakers would never dream

of. As an incentive for him to make his bold vision a reality, Tesla’s Board of Directors granted 5,274,901 stock options to Mr.

Musk that will ‘‘vest’’ or become available to him to exercise based on his ability to lead the company toward meeting specific

production and performance goals, including the successful completion of the Model X and Model 3 prototypes and reaching

100,000 units in total vehicle production (Tesla Motors 2016b).

In addition to overseeing Mr. Musk’s plans and providing the company with guidance, Tesla’s Board of Directors is tasked

with protecting the interests of Tesla’s stockholders, including the responsibility for risk oversight. Following best practices for

corporate governance, Tesla’s guidelines suggest that the majority of Tesla’s directors should be ‘‘outsiders,’’ meaning non-

company employees, and it has a standing Audit Committee to which both internal and external auditors report directly (Tesla

Motors 2016a). Some have raised concerns, however, about whether Tesla’s board is as independent as it appears. CtW

EXHIBIT 1 Tesla Motors Income Statement

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http://www.businessinsider.com/elon-musk-calls-times-writer-a-huge-douchebag-and-an-idiot-video-4
http://www.businessinsider.com/elon-musk-calls-times-writer-a-huge-douchebag-and-an-idiot-video-4
https://www.youtube.com/watch?v=rwDU--NPqZ0
Investment Group, which works with union-based pension funds and holds 200,000 shares of Tesla, recently called on the

company to separate the chairman of the board and CEO roles, both of which Elon Musk now holds, and to prohibit immediate

family members from serving on the board (Sage 2016). Mr. Musk’s brother, Kimbal Musk, currently serves on the boards of

both Tesla and SpaceX. Board member Brad Buss is also a former employee of SolarCity, Mr. Musk’s related company.

Tesla’s Employee Culture

Tesla’s culture has been described as ‘‘high risk, high reward,’’ and the company prides itself on operating like an internet

startup (Fehrenbacher 2015). Employees regularly work long hours and the atmosphere has been described as ‘‘grueling.’’

Nevertheless, many employees have enjoyed big payouts because of their association with Tesla. In mid-2015, Jerome Guillen,

then Tesla’s Vice President of Sales and Services, exercised options and sold shares netting him $4 million. Guillen has

subsequently taken a leave of absence from Tesla. In addition, Tesla’s longtime CFO, Deepak Ahuja, has recently retired from

Tesla after making millions by exercising his stock options in 2015. While the environment may be one of high pressure for

employees, many may enjoy working in the innovative and mission-driven environment Tesla promotes. As an example of

Tesla’s commitment to transparency and the advancement of energy alternatives, Tesla made the radical announcement that it

would not initiate patent lawsuits against anyone who, in good faith, wanted to use its technology (Tesla Motors 2015).

EXHIBIT 2 Tesla Motors Balance Sheet

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Challenges for Tesla and Its Future

Despite the company’s rapid growth and popularity, Tesla has also experienced a number of setbacks. The company has

struggled to reach desired production levels, which has resulted in lengthy delays for customers. Competitors, such as BMW,

Nissan Motor Company Ltd., and GM, have been developing all-electric alternatives and boast much higher production and

distribution capabilities than Tesla. Exhibit 4 presents a peer comparison of Tesla’s financials with current competitors. In

addition, analysts have raised questions about Tesla’s reliance on emissions credits to shore up losses and the company’s

exposure to lawsuits and lobbying by dealership unions to block states from allowing direct automotive sales to consumers

(Taylor 2013).

Moreover, while Tesla’s Model S achieved an overall five-star safety rating by the National Highway Traffic Safety

Administration, questions about the safety of Tesla’s new technology have continued to plague the company. In November

2013, a class action lawsuit was filed against Tesla and Mr. Musk, alleging that he had made false and/or misleading

representations with respect to the safety of the Model S. The case was dismissed in September 2014 by the trial court, but the

plaintiff’s appeal is still pending as of early 2016 (Tesla Motors 2016b).

Tesla has big plans for the future of its business. With the popularity of Tesla’s vehicles continuing to climb, the company

has begun to expand its operations. Among these expansions, the company has invested in an assembly facility in The

Netherlands and a specialized production plant in Lathrop, California. Tesla has also entered into strategic partnerships with

companies like Panasonic Corporation to focus on reducing the costs of lithium-ion battery packs. In addition, Tesla recently

announced the beginning of construction on its multi-billion-dollar investment in a ‘‘Gigafactory’’ in Nevada that will facilitate production of more affordable electric vehicles and battery-powered energy alternatives (Tesla Motors 2015).

According to the company’s 2015 annual report, Tesla plans to continue expanding stores and its service infrastructure

worldwide. The company will invest $1.5 billion in capital expenditures in equipment to support cell production at the

Gigafactory, to begin installation of Model 3 vehicle production machinery, to open about 80 retail locations and service

centers, and to energize about 300 new Supercharger locations (Tesla Motors 2016b). These bold expansion plans could put

Tesla at the center of an energy revolution, or they could cause the company to implode under the weight of significant debt

levels and even greater expectations.

EXHIBIT 3 Tesla Motors (TSLA) Stock Performance

(01/01/2014–03/31/2016)

Source: Stock chart from Yahoo! Finance.

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Using the Fraud Triangle to Identify Fraud Risk Factors

Auditing standards define fraud as an intentional act that results in a material misstatement in the financial reports (PCAOB

2016a). Research shows that fraud is more likely when three conditions are present: incentives or pressures, opportunities, and

attitudes or rationalizations. These three conditions are known collectively as the ‘‘fraud triangle’’ (Cressey 1953). Auditors use

the fraud triangle as a tool to help identify areas of risk during the fraud risk brainstorming process. These risks are referred to

as fraud risk factors. The next section describes each of the three conditions in more detail and provides examples from recent research of how each condition is linked with fraud.

The first leg of the fraud triangle is incentives or pressures. This condition is present whenever management and/or employees have incentives or are under pressures to commit fraud (Arens, Beasley, and Alvin 2010). Research shows that when

management compensation is tied to earnings and/or stock performance (e.g., bonuses, stock options), the likelihood of fraud is

higher (Healy and Wahlen 1999; Fields, Lys, and Vincent 2001). Other incentives than greed can also contribute to fraud risk.

A recent study finds that CFOs may become involved in deceptive accounting practices not for personal financial gain, but

rather to appease their CEOs and protect their jobs (Feng, Ge, Luo, and Shevlin 2011). Performance pressures also cause

managers and employees to engage in fraud. A recent survey finds that 64 percent of employees engage in unethical behavior

because they feel pressure to ‘‘do whatever it takes’’ to meet business targets (KPMG 2013). Changes in the external

environment, such as declines in customer demand, increased competition, or new regulations can threaten the financial

stability of a firm and generate pressure to ‘‘cook the books’’ and create the appearance of success while the firm attempts to

adapt to the environmental changes. Paradoxically, both high-performing firms (e.g., MacLean 2008; Mishina, Dykes, Block,

and Pollock 2010) and low-performing firms (e.g., Harris and Bromiley 2007; Zhang, Bartol, Smith, Pfarrer, and Khanin 2008)

have higher risks of financial statement fraud because both situations put pressure on executives to meet or exceed last period’s

earnings. Managers at poorly performing firms may also feel pressure to manipulate earnings or inflate asset balances in order

to meet debt covenant requirements and avoid defaulting on loans.

EXHIBIT 4 Peer Comparison

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The second leg of the fraud triangle is opportunities. This condition is present whenever circumstances allow management or employees to commit and conceal fraudulent behavior (Arens et al. 2010). Many different factors create opportunities for

fraud. The use of significant accounting estimates creates opportunities for earnings management and fraud, especially in the

area of reserves, allowances, and depreciation (PCAOB 2016c). Difficulty in verifying estimates and valuations also creates

opportunities for manipulation, particularly in areas such as intangible assets and Level 3 fair market valuations (PCAOB

2016d). In addition, fraud risks are higher when internal controls are weak or ineffective, when company policies are

ambiguous or enforced unevenly, or when oversight of financial reporting is inadequate; all of these circumstances make it

easier to commit and conceal fraudulent activity. Finally, transactions and financial relationships with related parties can create

opportunities to commit and conceal fraud (PCAOB 2016b).

The last leg of the fraud triangle is attitudes or rationalizations. This condition is present whenever management or employees exhibit an attitude, character, or set of ethical values that would enable committing a dishonest act (i.e., ‘‘bad apples’’) or whenever the environment imposes sufficient pressure on management or employees to cause good people to rationalize engaging in bad behavior (i.e., ‘‘bad barrels’’) (Treviño and Youngblood 1990; Arens et al. 2010). Auditors should be alert to the risk of bad apples for situations in which management has a history of being dishonest and violating laws and

regulations, or a reputation for making overly aggressive or unrealistic forecasts. In these circumstances, auditors should be

skeptical of management’s integrity and the veracity of their statements. Auditors also need to identify circumstances in which

good people may be tempted to make bad choices. Under the right pressure(s), managers and employees can rationalize

fraudulent activity as acceptable or even necessary, and thus disengage from the feelings of guilt and regret that normally

prevent people from behaving dishonestly. For example, management might rationalize financial statement fraud if the act

prevents the loss of jobs or the closure of the business. Employees can also rationalize stealing from a company as ‘‘getting what they are due’’ if they feel underpaid or underappreciated. Finally, managers might rationalize committing fraud if they suspect that competitors are doing the same.

Detecting rationalization risks can be difficult, but auditors should be alert for potential indicators such as the use of

euphemistic language, social norms in the company and/or industry that treat dishonesty as a part of doing business, and the

tone at the top set by the company’s CEO. A CEO who explicitly values ethics and honesty and emphasizes not only results,

but also the just means used to reach those results can foster ethical choices, whereas a CEO who is perceived as unethical or

even ethically neutral can foster an environment in which fraud is more easily rationalized (Treviño, Hartman, and Brown

2000).

By examining fraud risk factors using the three legs of the fraud triangle, auditors may develop more accurate fraud risk

assessments and become better prepared to alter the nature, timing, and extent of their audit procedures to respond to these

identified risks.

Part I Case Requirements: Identifying Fraud Risk Factors

You should work individually to complete responses to each of the assigned case requirement questions using the

information on Tesla Motors provided above and, where noted, in the case supplements, available for download in Appendix B.

Your responses should be completed before proceeding to Part II.

1. Fraud risks related to Tesla’s culture, leadership, and governance structure.

a. How would you describe the ‘‘tone at the top’’ set by Tesla’s leader, Elon Musk? How do Mr. Musk’s leadership style and his ‘‘tone at the top’’ contribute to possible fraud risk at Tesla Motors?

b. How would you describe the company’s culture? How might this culture create pressures and rationalizations for

fraud?

c. Review Tesla’s Code of Business Conduct and Ethics (see Appendix B for the link to ‘‘Tesla’s Code of Business Conduct and Ethics’’). How might any potential weaknesses in this code contribute to fraud risk at this company?

d. Describe some possible concerns regarding Tesla’s board of directors. How might these concerns create

opportunities and rationalizations for fraud?

2. Fraud risks related to Tesla’s incentive structures and stock performance.

a. To what extent are executives and employees incentivized with shares and stock options (see Appendix B for the

link to ‘‘Tesla’s 2015 Annual Report,’’ Item 7 Management’s Discussion and Analysis (MD&A) and Item 8 Financial Statements and Supplementary Data section, Note 10)? How do these pay structures create pressures/

incentives for fraud?

b. Review Tesla’s stock performance over the last two years (refer to Exhibit 3). What fraud pressures are created by

this stock performance?

3. Fraud risks related to revenue recognition at Tesla.

a. What does Tesla sell and how does the company account for revenue, accounts receivable, and COGS (see ‘‘Tesla’s

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2015 Annual Report,’’ Item 1 Business, Item 7 MD&A, and Item 8 Financial Statements and Supplementary Data, Note 2)?

b. How might these revenue-recognition practices create opportunities, incentives, and/or rationalizations for fraud?

4. Fraud risks related to Tesla’s business and operating conditions.

a. Review the business risks disclosed by the company (see Tesla’s 2015 Annual Report, Item 1A Risk Factors and

Item 8 Financial Statements and Supplementary Data, Note 2 and Note 13). How might some of these business risks

from the external environment also create fraud risks within Tesla?

b. What fraud risks are posed by Tesla’s expansion plans and the company’s ability to operate as a going concern (see

‘‘Tesla’s 2015 Annual Report,’’ refer to Item 1A)? c. What related-party transactions support Tesla’s financial performance (see ‘‘Tesla’s 2015 Annual Report,’’ Item 1

Manufacturing)? How might these transactions create opportunities for fraud?

5. Fraud risks indicated by the results of preliminary analytical procedures.

a. What fraud risks may be indicated by the year-to-year comparisons of Tesla’s financial statements (refer to Exhibits

1 and 2)?

b. How does the company perform relative to its peers (refer to Exhibit 4)? Do these ratios and trends seem

reasonable?

PART II

Fraud Brainstorming Session Best Practices

Brainstorming refers to an idea-generation process in which multiple participants share and explore their thoughts on a

particular topic. The brainstorming approach is advantageous in that the process can help participants identify and synergize

multiple ideas and perspectives in a relatively short amount of time. However, the process is not always effective;

brainstorming sessions may fail to deliver quality results for a number of reasons. Participants may consciously or

unconsciously engage in ‘‘social loafing’’ and hesitate to share their ideas because they think their efforts are either less important or less identifiable (Latané, Williams, and Harkins 1979). Research shows that inexperienced auditors may be

especially prone to social loafing when working in a group setting, which may cause them to produce significantly fewer and

less well-developed mental simulations of possible fraud schemes (Chen, Trotman, and Zhou 2015). Fraud brainstorming

sessions may also suffer process losses from ‘‘production blocking,’’ a phenomenon whereby participants lose an idea while waiting their turn and listening to others (Diehl and Stroebe 1987). Brainstorming sessions can also deteriorate due to

‘‘groupthink,’’ a phenomenon whereby a group coalesces on a single perspective rather than considering multiple ideas or points of view (Beasley and Jenkins 2003).

To minimize these obstacles to effective fraud risk brainstorming, groups should use content facilitation techniques, such

as prompts, to stimulate idea generation (Lynch, Murthy, and Engle 2009). The case requirements you completed in Part I of

this case are examples of the types of prompts used by auditors in actual fraud risk brainstorming sessions. To minimize the

risks of groupthink and production blocking, auditors commonly work individually to develop a list of fraud risks prior to joining the brainstorming session, and spend an average of five hours on preparing for each session (Dennis and Johnstone

2016). Brainstorming sessions can also be enhanced by following best practices (see Brazel, Carpenter, and Jenkins [2010] for

a recent field study of fraud risk brainstorming activities in audit firms). These best practices include a brainstorming session

that:

a. is led by a partner or forensic specialist;

b. includes an IT audit specialist;

c. is held early in the audit process (pre-planning or audit-planning stage);

d. includes extensive discussion about how management might perpetrate fraud;

e. includes extensive discussion about audit responses to fraud risk;

f. includes significant contributions from managers on the audit team; and

g. includes significant contributions from the audit partner.

Responding to Assessed Fraud Risks

In addition to using the concept of the fraud triangle as a tool to identify fraud risks, auditors may work in their fraud risk

brainstorming sessions to create a fraud risk matrix to help them better identify and respond to assessed fraud risks. A fraud risk

matrix is a tool that helps auditors connect identified fraud risk factors with possible fraud schemes and the account balances

that may be affected. The fraud risk matrix allows auditors to make a preliminary assessment of the likelihood and significance

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of such a scheme occurring within their client’s company. This then allows them to adapt the nature, timing, and extent of their

planned audit procedures to respond to the more likely and/or more significant identified fraud risks. Exhibit 5 provides an

example of a fraud risk matrix.

Auditing standards note that determining the nature, timing, and extent of planned audit procedures is a matter of

professional judgment. When the likelihood and/or significance of material misstatement due to fraud or error is high, the

auditor should respond by planning audit procedures that will increase both the quality—that is, the reliability and relevance—

and the quantity of the evidence collected (AICPA 2006). For example, when the likelihood of a particular fraud scheme is low

and the significance is low (e.g., employees being paid for unworked overtime when little to no overtime was reported in the

year), the audit team may decide that inquiries of associated personnel are sufficient to determine whether evidence of a

material misstatement exists for the account balances affected by such a scheme. When the likelihood of a particular fraud

scheme is high, but the significance is low (e.g., employees submitting false travel expense reimbursement claims for amounts

not requiring a receipt), the audit team may respond with additional procedures beyond inquiries of personnel to include both

tests of controls and analytical procedures, and determine whether additional substantive procedures are needed as this evidence

is evaluated. However, when the potential significance of a fraud scheme is high even when the likelihood may be low (e.g.,

members of management colluding to overstate revenue), auditors should plan for more substantive testing. Substantive testing

can include observing and/or re-performing significant transactions, recalculating balances, obtaining third-party confirmations,

and making physical inspections of assets and records. In response to increased risks of fraud, the timing of testing may also be

adjusted to perform more testing near the end of a period rather than at an interim date.

Once the fraud risk brainstorming session is complete, a member of the team is designated to document the results of the

session, which include: the identified fraud risks, the potential fraud schemes and the balances that would be affected, the

group’s assessment of the likelihood and significance of such schemes occurring, and the plan for adapting the nature, timing,

EXHIBIT 5 Sample Fraud Risk Matrix

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and/or extent of audit procedures to respond to this fraud risk assessment. This documentation may take the form of a

memorandum that is added to the audit file.

Part II Case Requirements: Conducting a Fraud Brainstorming Session

In Part II of this case, you will work in a group to simulate an audit team that is conducting a fraud risk brainstorming

session for Tesla Motors. Your instructor will provide you with further instructions regarding the composition of your audit

team and the timing of this brainstorming session. The following case requirements will help guide your activities in this

simulated brainstorming session.

1. Conducting the fraud brainstorming session.

a. Share and discuss your individual responses to each of the case requirement questions from Part I.

b. Work together to develop a fraud risk matrix (see Exhibit 5 for an example) that identifies the three fraud risk factors that your team believes present the greatest concern to the audit based on your team’s assessment of their likelihood

and significance. Focus on those fraud risk areas that pose the greatest potential threat for a material misstatement in

the financials.

c. Determine how the nature, timing, and extent of the audit procedures should be altered to respond to these identified

risks.

2. Documenting the results of the fraud brainstorming session.

Document your conclusions from this brainstorming session in a memorandum for the audit file. A template for your

reference is included in Appendix A. Your documentation should include:

a. The date, the attendees, and the purpose of the session, as well as how long the session lasted.

b. The three most concerning fraud risks at Tesla, the potential fraud schemes and account balances that would be affected, and the group’s assessment of the likelihood and significance of such schemes occurring in a fraud risk matrix

(from 1b above).

c. The team’s consensus (or lack thereof, if applicable) regarding the overall risk of fraud at Tesla Motors.

d. The team’s plan for adapting the nature, timing, and/or extent of audit procedures to respond to this fraud risk

assessment.

REFERENCES

American Institute of Certified Public Accountants (AICPA). 2006. Consideration of Fraud in a Financial Statement Audit. AU. Section 316. New York, NY: AICPA.

Arens, I. R. J., M. S. Beasley III, and A. Alvin. 2010. Auditing and Assurance Services: An Integrated Approach-13/E. Englewood Cliffs, NJ: Pearson Prentice Hall.

Association of Certified Fraud Examiners (ACFE). 2016. Report to the Nations on Occupational Fraud and Abuse. Available at: http:// www.acfe.com/rttn2016/docs/2016-report-to-the-nations.pdf

Beasley, M. S., and J. G. Jenkins. 2003. A primer for brainstorming fraud risks. Journal of Accountancy 196 (6): 32. Brazel, J. F., T. D. Carpenter, and J. G. Jenkins. 2010. Auditors’ use of brainstorming in the consideration of fraud: Reports from the field.

The Accounting Review 85 (4): 1273–1301. https://doi.org/10.2308/accr.2010.85.4.1273 Carpenter, T. D. 2007. Audit team brainstorming, fraud risk identification, and fraud risk assessment: Implications of SAS No. 99. The

Accounting Review 82 (5): 1119–1140. https://doi.org/10.2308/accr.2007.82.5.1119 Center for Audit Quality (CAQ). 2010. Report on Deterring and Detecting Financial Reporting Fraud: A Plan for Action. Available at:

http://www.thecaq.org/deterring-and-detecting-financial-reporting-fraud

Chen, C. X., K. T. Trotman, and F. Zhou. 2015. Nominal versus interacting electronic fraud brainstorming in hierarchical audit teams. The Accounting Review 90 (1): 175–198. https://doi.org/10.2308/accr-50855

Cressey, D. R. 1953. Other People’s Money; A Study of the Social Psychology of Embezzlement. Ann Arbor, MI: Free Press: University of Michigan.

Dennis, S. A., and K. M. Johnstone. 2016. A field survey of contemporary brainstorming practices. Accounting Horizons 30 (4): 449–472. https://doi.org/10.2308/acch-51503

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28 Hess and Andiola

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https://doi.org/10.2308/accr.2010.85.4.1273
https://doi.org/10.2308/accr.2007.82.5.1119
http://www.thecaq.org/deterring-and-detecting-financial-reporting-fraud
https://doi.org/10.2308/accr-50855
https://doi.org/10.2308/acch-51503
https://doi.org/10.1037/0022-3514.53.3.497
http://fortune.com/2015/08/21/teslas-startup-culture-musk/
http://fortune.com/2015/08/21/teslas-startup-culture-musk/
https://doi.org/10.1016/j.jacceco.2010.09.005
Fields, T. D., T. Z. Lys, and L. Vincent. 2001. Empirical research on accounting choice. Journal of Accounting and Economics 31 (1-3): 255–307. https://doi.org/10.1016/S0165-4101(01)00028-3

Harris, J., and P. Bromiley. 2007. Incentives to cheat: The influence of executive compensation and firm performance on financial

misrepresentation. Organization Science 18 (3): 350–367. https://doi.org/10.1287/orsc.1060.0241 Healy, P. M., and J. M. Wahlen. 1999. A review of the earnings management literature and its implications for standard setting.

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Statements. IAS 240. Available at: http://www.ifac.org/system/files/downloads/a012-2010-iaasb-handbook-isa-240.pdf KPMG. 2013. Integrity Survey 2013. Available at: http://www.kpmg-institutes.com/institutes/advisory-institute/articles/2013/07/integrity-

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brainstorming technique and facilitation. The Accounting Review 84 (4): 1209–1232. https://doi.org/10.2308/accr.2009.84.4.1209 MacLean, T. L. 2008. Framing and organizational misconduct: A symbolic interactionist study. Journal of Business Ethics 78 (1–2): 3–

16. https://doi.org/10.1007/s10551-006-9324-x

Mishina, Y., B. J. Dykes, E. S. Block, and T. G. Pollock. 2010. Why ‘‘good’’ firms do bad things: The effects of high aspirations, high expectations, and prominence on the incidence of corporate illegality. Academy of Management Journal 53 (4): 701–722. https:// doi.org/10.5465/AMJ.2010.52814578

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Public Company Accounting Oversight Board (PCAOB). 2016b. Related Parties. AS 2410. Washington, DC: PCAOB. Public Company Accounting Oversight Board (PCAOB). 2016c. Auditing Accounting Estimates. AS 2501. Washington, DC: PCAOB. Public Company Accounting Oversight Board (PCAOB). 2016d. Auditing Fair Value Measurements and Disclosures. AS 2502.

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Smith, A. 2014. Who is Elon Musk? Tech Billionaire, SpaceX Cowboy, Tesla Pioneer—and Real Life Iron Man. The Telegraph (January 4). Available at: http://www.telegraph.co.uk/technology/news/10544247/Meet-tech-billionaire-and-real-life-Iron-Man-Elon-Musk.

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governance-document.cfm?DocumentID¼14836 Telsa Motors. 2016b. Tesla Motors Inc 2015 Annual Report. Palo Alto, CA: Tesla Motors. Available at: http://files.shareholder.com/

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incentive misalignment. Academy of Management Journal 51 (2): 241–258. https://doi.org/10.5465/AMJ.2008.31767230

APPENDIX A Memo Template to Document the Results of a Fraud Brainstorming Session

Date: [DATE OF SESSION] Participants: [NAME OF ALL SESSION PARTICIPANTS] Length of Session: [TIME IN HOURS_MINUTES] Purpose of the Session: [FILL IN]

Fraud Risk Brainstorming at Tesla Motors 29

Issues in Accounting Education Volume 33, Number 2, 2018

https://doi.org/10.1016/S0165-4101(01)00028-3
https://doi.org/10.1287/orsc.1060.0241
https://doi.org/10.2308/acch.1999.13.4.365
http://www.ifac.org/system/files/downloads/a012-2010-iaasb-handbook-isa-240.pdf
http://www.kpmg-institutes.com/institutes/advisory-institute/articles/2013/07/integrity-survey-2013.html
http://www.kpmg-institutes.com/institutes/advisory-institute/articles/2013/07/integrity-survey-2013.html
https://doi.org/10.1037/0022-3514.37.6.822
https://doi.org/10.2308/accr.2009.84.4.1209
https://doi.org/10.1007/s10551-006-9324-x
https://doi.org/10.5465/AMJ.2010.52814578
https://doi.org/10.5465/AMJ.2010.52814578
https://www.pwc.com/us/en/faculty-resource/assets/pwc-data-driven-paper-feb2015.pdf
http://www.reuters.com/article/us-solarcity-m-a-tesla-idUSKCN0ZE2ZL
http://www.reuters.com/article/us-solarcity-m-a-tesla-idUSKCN0ZE2ZL
http://www.telegraph.co.uk/technology/news/10544247/Meet-tech-billionaire-and-real-life-Iron-Man-Elon-Musk.html
http://www.telegraph.co.uk/technology/news/10544247/Meet-tech-billionaire-and-real-life-Iron-Man-Elon-Musk.html
http://fortune.com/2013/06/12/9-questions-for-teslas-elon-musk/
http://fortune.com/2013/06/12/9-questions-for-teslas-elon-musk/
https://www.teslamotors.com/about
http://ir.tesla.com/corporate-governance-document.cfm?DocumentID=14836
http://ir.tesla.com/corporate-governance-document.cfm?DocumentID=14836
http://ir.tesla.com/corporate-governance-document.cfm?DocumentID=14836
http://files.shareholder.com/downloads/ABEA-4CW8X0/1651466307x0xS1564590-16-13195/1318605/filing.pdf
http://files.shareholder.com/downloads/ABEA-4CW8X0/1651466307x0xS1564590-16-13195/1318605/filing.pdf
https://doi.org/10.1037/0021-9010.75.4.378
https://doi.org/10.2307/41166057
https://doi.org/10.5465/AMJ.2008.31767230
Part A—Assessment of Fraud Risks

[INSERT FRAUD MATRIX HERE]

Part B—Overall Fraud Risk Assessment

As a group, how would you rate the overall potential of a risk of material misstatement due to fraud at this client (e.g., low

risk, moderate risk, or high risk)? Provide justification for your assessment and note any dissension about this assessment

among the team members, if applicable.

Part C—Planning the Nature, Timing, and Extent of Procedures

Based on the identified fraud risk factors and the level of assessed fraud at this client, how would your group modify the

nature, timing, and/or extent of the planned audit procedures? Discuss at least three audit procedures that should be performed

on this audit in response to the fraud risk factors identified above. Your group should try to be as specific as possible (i.e., the

account(s) that you would focus on, the procedure(s) you may perform, and when you would perform the procedure).

1. [FILL IN]

2. [FILL IN]

3. [FILL IN]

APPENDIX B

iace-51973_ Tesla’s Code of Business Conduct and Ethics: http://dx.doi.org/10.2308/iace-51973.s01

iace-51973_ Tesla’s 2015 Annual Report: http://dx.doi.org/10.2308/iace-51973.s02

30 Hess and Andiola

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http://dx.doi.org/10.2308/iace-51973.s01
http://dx.doi.org/10.2308/iace-51973.s02
CASE LEARNING OBJECTIVES AND IMPLEMENTATION GUIDANCE

This instructional case involves identifying fraud risk factors at a public company and conducting a fraud risk

brainstorming session, consistent with the guidance under AS 2401, Consideration of Fraud in a Financial Statement Audit. We see the instructional value of this case as two-fold. Not only does the case incorporate important auditing and forensic

concepts like assessing fraud risk and applying the fraud triangle, but also the case gives students first-hand experience with

conducting a fraud risk brainstorming session in a team environment and documenting this process. While there are a number

of cases published in the last 15 years that focus on the issue of identifying fraud risk factors and responding to fraud risks (e.g.,

Agoglia, Brown, and Hanno 2003; Ballou and Mueller 2005; Owhoso and Weickgenannt 2010; Gifford and Howe 2011; Rufus

and Hahn 2011; Dickins and Reisch 2012; Dee, Durtschi, and Mindak 2014), we are not aware of any instructional cases that

combine fraud risk assessment with guidance on how to conduct and document a fraud risk brainstorming session. Students

also indicated that they found this case to be realistic and enjoyed learning about these concepts in the context of this popular

company.

Learning Objectives

There are five learning objectives for this case:

1. To recognize the factors that contribute to financial statement fraud risk (Part I).

2. To identify and evaluate the likelihood and severity of fraud risks for a particular organization (Part I).

3. To analyze the ways that fraud risks can lead to material misstatements in the financial statements (Parts I and II).

4. To understand the purpose of and how to conduct a fraud brainstorming session as a team (Part II).

5. To develop audit procedures that respond to assessed fraud risks (Part II).

Implementation Guidance

This case is designed for use in either undergraduate- or graduate-level courses that feature an emphasis on fraud risk

assessments or assurance (e.g., auditing, fraud, forensic accounting). This case offers students the opportunity to explore the

fraud risk assessment process and to participate in a simulated fraud brainstorming session. To be most effective and more

closely simulate an actual fraud brainstorming session, we recommend that Part I of the case be completed by students

individually as a take-home assignment. Instructors will need to provide students with the case document in order for them to

complete Part I. Students should turn in Part I as an individual assignment (Deliverable 1), and then use their responses from

Part I as inputs for the brainstorming session in Part II. Students report spending approximately 3.5 hours to complete all of the

case requirement questions in Part I. To minimize the time required, instructors may choose to divide the case requirements

among the students (e.g., half of the students complete case Requirements 1 and 2 (six questions) and the other half complete

case Requirements 3 through 5 (seven questions). Before moving to Part II, we encourage instructors to dedicate some class

time (10–15 minutes) to review student responses to Part I and explain the tasks and deliverables associated with Part II. More

guidance on discussing the key concepts of this case is provided in the Teaching Notes.

For Part II of the case, instructors will need to group students into small audit teams (‘‘investigation teams’’ if using in a

forensic accounting class) to hold a fraud risk brainstorming session. The instructor will also need to provide students with

guidance on when they should hold their brainstorming session and how long they should spend brainstorming. We

recommend that students dedicate no more than one hour to the brainstorming session and reserve one to two hours for

documenting their results (Deliverable 2). We suggest that Part II be completed as a take-home group assignment, but

instructors also could complete Part II of the case as an in-class activity.

Following the completion and documentation of the team brainstorming sessions, we recommend that instructors lead a

class discussion of the key learning objectives from the case (about 30 minutes). Guidance on these topics and solutions are

available in the Teaching Notes. This discussion should highlight some of the challenges of (1) assessing fraud risk factors, (2)

conducting effective brainstorming sessions, and (3) linking risk factors to appropriate audit responses. Through this

discussion, instructors can elicit observations from the students on the effectiveness of their brainstorming session, as well as

specific examples of the fraud risk factors documented in their fraud risk matrices and the suggested audit procedures to reduce

these risks.

Customizing the Case

The usage of this case can vary somewhat depending on the specific student audience. The instructor can tailor the

difficulty of the case and the focus of the case depending on the knowledge and skill level of the students, as well as the focus

Fraud Risk Brainstorming at Tesla Motors 31

Issues in Accounting Education Volume 33, Number 2, 2018

of the class (i.e., auditing versus fraud). To increase the difficulty of the case, instructors can implement one or more of the following ideas:

� Assign additional readings from the academic literature related to financial statement fraud risks (e.g., MacLean 2008; Mishina, Dykes, Block, and Pollock 2010) or fraud brainstorming (e.g., Brazel, Carpenter, and Jenkins 2010; Dennis

and Johnstone 2016). As part of the class discussion of the key learning objectives, the instructor can facilitate a

dialogue on the findings taken from the academic research literature. � Assign additional analytical procedures for Part I, such as the calculation of Beneish’s (1997) ‘‘M-Score’’ for Tesla.

Instructors may find Wells’ (2001) article ‘‘Irrational Ratios’’ helpful in guiding students’ efforts to calculate and interpret Beneish’s M-Score.

� Increase the number of fraud risks documented in the fraud risk matrix and the number of audit procedures described in the memorandum of the fraud brainstorming session.

To simplify the case, instructors can implement one or more of the following ideas:

� Allow students to work in groups of two to complete Part I. � Remove the case requirement in Part II that requires students to identify the nature, timing, and extent of audit

procedures. � Conduct Part II as a class activity with the entire class participating in the session as one team.

Evidence of Efficacy

To assess the effectiveness of the case, we tested it in five undergraduate audit classes (185 students) and two graduate

fraud classes (39 students) at three public and two private universities (four independent instructors and one author). Pre- and

post-test surveys were Institutional Review Board (IRB) approved, were formatted similarly to those in Worrell (2010) and

Dow, Watson, and Shea (2013), and were administered using comparable procedures to avoid any potential demand effects.

The pre-test survey was administered a few days prior to assigning the case. Students were informed that the survey was to

assess their knowledge and comfort level with specific course-related topics, that it was entirely voluntary, and that all

responses would remain anonymous. The post-test survey was administered on the submission date of the completed

Deliverable 2.

The questions used in the survey, the pre-test and post-test means, and significance levels are presented in Table 1, Panel

A. In addition, Table 1, Panel B presents the results of several additional questions asked after completion of the case. To assess

the case’s impact on students’ knowledge, we asked students six questions before and after case completion that dealt with their

understanding of the key learning objectives of the case.1 Table 1, Panel A shows that the case significantly increased students’

knowledge of fraud risk factors and fraud brainstorming sessions (p , 0.001, two-tailed in both). In addition, the case made students more comfortable with applying the fraud triangle, creating a fraud risk matrix, adapting audit procedures, and

conducting a fraud brainstorming session (p , 0.001, two-tailed for all). In addition, Table 1, Panel B indicates that students perceived the case to be a realistic scenario (77.0 percent agree or

strongly agree), that was interesting (75.8 percent agree or strongly agree), and provided a positive learning experience (78.2

percent agree or strongly agree). In addition, students felt that the case required them to think critically (80.6 percent agree or

strongly agree) and apply their professional skepticism (78.2 percent agree or strongly agree). We also asked students to

provide verbal feedback about the case. An overwhelming number of responses indicated that students liked that the case used a

real, recognizable, and current company, with real data and information. For example, one student commented that ‘‘the issues Tesla faces are realistic issues that auditors have to be able to analyze and assess for any company.’’ In addition, several students pointed out that they liked conducting the actual brainstorming session to be able to pool their ideas and better

understand how the session would work in practice. Thus, the case appears to provide a realistic learning environment to help

students prepare for procedures they will be asked to do in audit practice.

TEACHING NOTES

Teaching Notes are available only to non-student-member subscribers to Issues in Accounting Education through the American Accounting Association’s electronic publications system at http://aaapubs.org/. Non-student-member subscribers

should use their usernames and passwords for entry into the system where the Teaching Notes can be reviewed and printed.

Please do not make the Teaching Notes available to students or post them on websites.

1 We investigated whether the responses differed by level (i.e., undergraduate, graduate), but results were quantitatively similar. Therefore, the combined results are presented in Table 1.

32 Hess and Andiola

Issues in Accounting Education Volume 33, Number 2, 2018

http://aaapubs.org/
If you are a non-student-member of AAA with a subscription to Issues in Accounting Education and have any trouble

accessing this material, then please contact the AAA headquarters office at info@aaahq.org or (941) 921-7747.

REFERENCES

Agoglia, C. P., K. F. Brown, and D. M. Hanno. 2003. Dickinson Technologies, Inc.: Assessing control environment and fraud risk. Issues

in Accounting Education 18 (1): 71–78. https://doi.org/10.2308/iace.2003.18.1.71

Ballou, B., and J. M. Mueller. 2005. Helecom communications: Considering fraud risk on an engagement before and after analyzing a key

business process. Issues in Accounting Education 20 (1): 99–118. https://doi.org/10.2308/iace.2005.20.1.99

TABLE 1

Student Learning Perceptions

Panel A: Questions Asked Before and After Case Completion

Survey Item

Pre-Case Mean (SD)

Post-Case Mean (SD) t-statistic

1. Rate your level of knowledge of identifying fraud risk factors of an organization. 3.34 4.70 10.7***

(1.26) (1.11)

2. Rate how comfortable you feel applying the fraud triangle to identify fraud risk factors. 3.66 4.98 10.0***

(1.35) (1.09)

3. Rate your level of knowledge of the purpose of fraud brainstorming sessions. 3.34 5.10 12.8***

(1.38) (1.16)

4. Rate how comfortable you feel creating a fraud risk matrix. 2.64 4.52 14.8***

(1.20) (1.17)

5. Rate how comfortable you feel adapting audit procedures to respond to assessed fraud risks. 3.23 4.41 9.3***

(1.24) (1.13)

6. Rate how comfortable you feel conducting a fraud brainstorming session. 3.08 4.91 14.0***

(1.32) (1.09)

Panel B: Questions Asked After Case Completion

Survey Item

Strongly Disagree

1 Disagree

2

Somewhat Disagree

3 Neutral

4

Somewhat Agree

5 Agree

6

Strongly Agree

7 Mean (SD)

This case represents a realistic scenario. 0.0% 0.0% 1.2% 4.8% 17.0% 39.4% 37.6% 6.07

(0) (0) (2) (8) (28) (65) (62) (0.92)

The case encouraged me to think critically

about the factors that contribute to fraud

risk.

0.0% 0.6% 0.6% 4.3% 13.9% 49.1% 31.5% 6.04

(0) (1) (1) (7) (23) (81) (52) (0.91)

The case encouraged me to apply

professional skepticism.

0.0% 0.0% 0.0% 4.8% 17.0% 46.7% 31.5% 6.05

(0) (0) (0) (8) (28) (77) (52) (0.83)

I found the case interesting. 0.0% 0.0% 4.8% 3.6% 15.8% 46.7% 29.1% 5.92

(0) (0) (8) (6) (26) (77) (48) (1.02)

The case was a positive learning experience. 0.0% 0.6% 2.4% 6.7% 12.1% 45.5% 32.7% 5.98

(0) (1) (4) (11) (20) (75) (54) (1.02)

***Signifies p , 0.001. Panel A presents results of a pre-case and post-case comparison of a set of six questions. Responses were provided on a series of seven-point scales with 1 labeled ‘‘low knowledge’’ and ‘‘highly uncomfortable’’ and 7 labeled ‘‘high knowledge’’ and ‘‘highly comfortable’’ (for questions 1 and 3, and 2, 4–6, respectively). The pre-case data includes 185 (146 undergraduate and 39 graduate) students and the post-case data includes 165 (132 undergraduate and 33 graduate) students. Panel B presents results of five additional post-case questions. Responses were provided on a series of seven-point scales with 1 labeled ‘‘strongly disagree’’ and 7 labeled ‘‘strongly agree.’’

Fraud Risk Brainstorming at Tesla Motors 33

Issues in Accounting Education Volume 33, Number 2, 2018

mailto:info@aaahq.org
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The Accounting Review 85 (4): 1273–1301. https://doi.org/10.2308/accr.2010.85.4.1273 Dee, C., C. Durtschi, and M. P. Mindak. 2014. Grand Teton Candy Company: Connecting the dots in a fraud investigation. Issues in

Accounting Education 29 (3): 443–458. https://doi.org/10.2308/iace-50763 Dennis, S. A., and K. M. Johnstone. 2016. A field survey of contemporary brainstorming practices. Accounting Horizons 30 (4): 449–472.

https://doi.org/10.2308/acch-51503

Dickins, D., and J. T. Reisch. 2012. Enhancing auditors’ ability to identify opportunities to commit fraud: Instructional resource cases.

Issues in Accounting Education 27 (4): 1153–1169. https://doi.org/10.2308/iace-50178 Dow, K. E., M. W. Watson, and V. J. Shea. 2013. Understanding the links between audit risks and audit steps: The case of procurement

cards. Issues in Accounting Education 28 (4): 913–921. https://doi.org/10.2308/iace-50508 Gifford, R. H., and H. Howe. 2011. Relating operational and financial factors to assess risk and identify fraud in an operational setting.

Issues in Accounting Education 26 (2): 361–376. https://doi.org/10.2308/iace-10021 MacLean, T. L. 2008. Framing and organizational misconduct: A symbolic interactionist study. Journal of Business Ethics 78 (1–2): 3–

16. https://doi.org/10.1007/s10551-006-9324-x

Mishina, Y., B. J. Dykes, E. S. Block, and T. G. Pollock. 2010. Why ‘‘good’’ firms do bad things: The effects of high aspirations, high expectations, and prominence on the incidence of corporate illegality. Academy of Management Journal 53 (4): 701–722. https:// doi.org/10.5465/AMJ.2010.52814578

Owhoso, V., and A. Weickgenannt. 2010. Vinand Petroleum, Inc.: Initial audit engagement and fraud risk case for a specialized industry.

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doi.org/10.2308/iace.2010.25.3.527

34 Hess and Andiola

Issues in Accounting Education Volume 33, Number 2, 2018

https://doi.org/10.1016/S0278-4254(97)00023-9
https://doi.org/10.2308/accr.2010.85.4.1273
https://doi.org/10.2308/iace-50763
https://doi.org/10.2308/acch-51503
https://doi.org/10.2308/iace-50178
https://doi.org/10.2308/iace-50508
https://doi.org/10.2308/iace-10021
https://doi.org/10.1007/s10551-006-9324-x
https://doi.org/10.5465/AMJ.2010.52814578
https://doi.org/10.5465/AMJ.2010.52814578
https://doi.org/10.2308/iace.2010.25.2.331
https://doi.org/10.2308/iace.2011.26.1.201
https://doi.org/10.2308/iace.2010.25.3.527
https://doi.org/10.2308/iace.2010.25.3.527