Amsterdam Business School

Auditor Mindsets and Fraud Judgment

Master thesis

Name: Thomas Laarman

Student number: 10267166

Thesis supervisor: Prof. dr. V. Maas

Date: August 15, 2016

Word count: 18.244

MSc Accountancy & Control, specialization [Accountancy]

Faculty of Economics and Business, University of Amsterdam

2

Statement of Originality

This document is written by student Thomas Laarman who declares to take full responsibility

for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources

other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion

of the work, not for the contents.

3

Abstract

The effectiveness of tools that auditors use for assessing fraud risk varies significantly, and this

variation impacts their fraud judgments. This is an alarming observation since it is expected that

in the future the importance of fraud in financial statements will increase relative to error.

Therefore, this thesis investigates whether the effectiveness of tools used by auditors to assess

fraud risk can be improved using mindset theory. Using an experiment, this thesis tests whether

it is beneficial for auditors to change from the current mindset they use when assessing fraud risk

(an implemental mindset) to a potential desirable mindset (a deliberative mindset). The advantage

of the deliberative mindset is that it fosters a broader focus of attention than the implemental

mindset. Furthermore, it promotes the impartial processing of information. Hence, this thesis

expects that a deliberative mindset improves auditors’ fraud judgments. Since the results of this

study provide no support for this expectation, it is suggested that mindset theory is not effective

in improving auditors’ fraud judgments.

Key words: auditors’ mindsets, fraud judgment, fraud risk assessment, SAS No. 99, fraud

checklists.

4

Acknowledgements

First of all, I would like to thank prof. dr. V. Maas for the support and feedback on my thesis. I

would also like to thank dr. ir. S. van Triest for providing additional feedback. Lastly, I would

like to thank my family for their mental support.

5

Contents

1 Introduction ...................................................................................................................... 7

2 Theoretical background and hypothesis development ................................................... 11

2.1 Fraud.......................................................................................................................... 11

2.1.1 Characteristics of fraud .......................................................................................................... 11

2.1.2 Types of fraud ......................................................................................................................... 12

2.1.3 Fraud triangle .......................................................................................................................... 12

2.1.3.1 Attitude .................................................................................................................................. 14

2.1.3.2 Incentive .................................................................................................................................. 16

2.1.3.3 Opportunity .............................................................................................................................. 18

2.1.4 Summary .................................................................................................................................. 20

2.2 SAS No. 99: Consideration of fraud in a financial statement audit .......................... 21

2.2.1 The role of the auditor .......................................................................................................... 21

2.2.2 Fraud risk assessment tools .................................................................................................. 22

2.2.2.1 Inquiries .................................................................................................................................. 23

2.2.2.2 Analytical procedures .................................................................................................................. 23

2.2.2.3 Fraud checklists ......................................................................................................................... 24

2.2.2.4 Brainstorming ........................................................................................................................... 25

2.2.3 Summary .................................................................................................................................. 26

2.3 Mindsets ................................................................................................................... 27

2.3.1 Characteristics ......................................................................................................................... 27

2.3.2 Implemental mindset, deliberative mindset and hypothesis ............................................ 28

3 Research Methodology ................................................................................................... 30

3.1 Experimental design ................................................................................................ 30

3.2 Sample and procedures ............................................................................................ 30

3.3 Case materials and measures ................................................................................... 32

3.4 Manipulation and variables ...................................................................................... 32

4 Results ............................................................................................................................. 34

4.1 Preliminary analyses ................................................................................................. 34

4.1.1 Variables .................................................................................................................................. 34

4.1.2 Descriptive statistics............................................................................................................... 35

4.1.3 Manipulation evaluation ........................................................................................................ 37

4.2 Hypothesis testing ................................................................................................... 39

4.2.1 Auditor’s mindsets ................................................................................................................. 39

4.3 Additional analyses .................................................................................................. 40

6

4.3.1 Regression analysis with interactions................................................................................... 40

4.3.2 Reduced sample test ............................................................................................................... 40

5 Conclusion ...................................................................................................................... 42

References.......................................................................................................................... 44

Appendix 1: Questionnaire Deliberative mindset ............................................................. 48

Appendix 2: Questionnaire Implemental mindset ............................................................ 53

7

1 Introduction

From the past, the audit profession has learned how disastrous fraud can be with the collapse of

Arthur Andersen, a firm which once constituted the then Big Five audit firms. In October 2001,

fraud was discovered at a client of Arthur Andersen, namely Enron, a large American energy,

natural resources, and services company. Two months later in December 2001, Enron

succumbed to the effects of the scandal and went bankrupt. Immediately after discovery of the

Enron scandal, Arthur Andersen was investigated for its performance regarding Enron’s

financial statements as well as its suspected role in the scandal. As a result, the audit firm was

convicted in June 2002 of obstruction of justice for destroying Enron related documents in

shredders. This conviction led to the downfall of Arthur Andersen in mid-2002; this downfall

was also brought about by the impact of the scandal and proof of felonious complicity of two

managers of the audit firm, namely Nancy Temple and David Duncan who initiated the

destruction of Enron related documents. In May 2005, the Supreme Court of the United States

decided to reverse the conviction of Arthur Andersen of obstruction of justice, but this came too

late for the audit firm.

The fraud at Enron is only one of the many scandals that have been uncovered in the

early 21st century. All these scandals point to an observation that current accounting and audit

laws and regulations are inadequate. In order to prevent future scandals from occurring, the

aforementioned laws and regulations needed to be rigorously altered. In an attempt to achieve

this objective, the Sarbanes-Oxley Act of 2002 was introduced; this act is an American law that

renews or extends current laws and regulations for all American listed company boards,

management and the audit firms auditing the financial statements of these companies. Also, the

American Institute of Certified Public Accountants (AICPA) introduced the Statement on

Auditing Standards number 99 (SAS No. 99) entitled Consideration of Fraud in a Financial

Statement Audit, and it has been effective from October 2002. The SAS No. 99 and other

standards relating to fraud should be taken very seriously by auditors because fraud detection

and deterrence is a crucial part of an audit (Elliot, 2002; Griffith et al., 2015; Wilks &

Zimbelman, 2004). Moreover, annual reports can now be prepared more reliably due to

innovations in information technology; as a result, the importance of fraud detection in an audit

will increase relative to error detection (Elliot, 2002). On the whole, it can be seen that fraud in

financial statements is a highly important issue that may become even more important in the

foreseeable future. However, the current literature provides mixed results about the effectiveness

of mandatory tools auditors currently use to assess fraud risk.

8

In response to this alarming observation, this study aims to expand the current body of

research literature by investigating whether the effectiveness of current tools used for fraud risk

assessments—which are incorporated in SAS No. 99—can be enhanced using mindset theory. A

recent study by Griffith et al. (2015) showed that mindset theory does indeed play an important

role in audits. Their study discovered evidence that a change in mindset can improve auditors’

evaluation of complex estimates (Griffith et al., 2015). Therefore, this thesis uses mindset theory

to determine whether this could also be beneficial in another part of the audit—assessing fraud

risk.

A mindset can be defined as a set of mental processes that establish a general

preparedness to react in a certain way (Freitas et al., 2004; Gollwitzer, 1990). There are two key

characteristics of a mindset: (a) it fosters orientations that are not related to a specific task and

(b) it stays active once it is activated, even after the completion of the original task (Hamilton et

al., 2011). The consequence of the second characteristic is that a mindset affects subsequent and

also separate tasks (Hamilton et al., 2011).

In this thesis, two mindsets—a deliberative mindset and an implemental mindset—are tested to

examine whether a change in mindset leads to a significantly different fraud risk judgment. A

deliberative mindset can be interpreted as mental procedures concerning how a person selects

one goal over other goal alternatives that are available to that person (Gollwitzer et al., 1990). By

contrast, an implemental mindset can be viewed as the steps a person has to take to achieve a

selected goal (Gollwitzer et al., 1990). In other words, a deliberative mindset consists of

procedures focused on analysing and weighing advantages and disadvantages, and an

implemental mindset consists of procedures focused on the timing and sequence of steps that

need to be taken (Gollwitzer et al., 1990). Currently, it is most likely that auditors will adopt a

mindset close to the implemental mindset because assessing fraud risk involves performing the

steps required by the Auditing Standards. However, a deliberative mindset might be more

beneficial to auditors because assessing fraud risk is a unique process in which it is not only

crucial to follow the steps required by the Auditing Standards but also to remain open to

information beyond the steps. A deliberative mindset enlarges the openness of a person’s mind

to incidentally provided information (Gollwitzer & Bayer, 1999; Fujita et al., 2007), and adopting

this mindset could result in the value of the information being evaluated in a better way

(Beckman & Gollwitzer, 1987). Hence, the hypothesis of this thesis is that auditors adopting a

deliberative mindset will judge fraud to be more likely than auditors adopting an implemental

mindset.

9

To test this hypothesis, a case-based experiment was carried out in this study. A total of 36

auditors participated in the experiment; they are from one of the Big Four audit firms that

operate in the Netherlands. All participants completed a questionnaire where they are asked to

read a case of a fictitious audit client and a related fraud risk factor checklist completed by a

senior. Subsequently, the participants are asked to provide their judgment about the risk of

material misstatement in the financial statements due to fraud. Before reading this information

and providing a judgment, the participants were first asked to read a different case about a

potential client, a listed construction company that is obliged under Dutch law to choose a new

audit firm for their statutory audit for next year. The participants are asked to imagine that they

work for a Big Four audit firm as an auditor, and that their firm is considering writing a proposal

to win the construction company. After reading the case, one half of the participants are asked to

list three advantages and disadvantages in winning the construction company, and the other half

are asked to list six steps they would take in their attempt to win the construction company. This

was the variable that was manipulated in the experiment; the pros and cons question is used for

activating a deliberative mindset, while the required steps question is used for activating an

implemental mindset.

The results of the experiment provide no support for the expectation of this thesis.

Using a deliberative mindset instead of an implemental mindset does not result in higher fraud

judgments. This implies that mindset theory is not effective in enhancing the effectiveness of

fraud checklists. The findings of this thesis extend the literature in two ways and may be

interesting to both researchers and standard setters. First, the findings suggest that the use of

mindset theory is not effective in enhancing the effectiveness of mandatory tools to assess fraud

risk incorporated in SAS No. 99. Second, the findings of this thesis are inconsistent with the

findings of Griffith et al. (2015). Whereas they do find evidence in their study that suggests

mindset theory is useful in audits, this study finds no evidence. This shows that the usefulness of

mindset theory depends on the task performed in the audit. Therefore, standard setters who are

considering to implement new mindset regulations in specific auditing standards should be

careful when implementing such regulations.

This thesis is subject to several limitations, which could potentially affect the

contributions of the findings. First, the auditors who participated in the experiment all work for

the same Big Four audit firm at one location. These factors may have affected the answers

provided by the participants. Consequently, the generalization of the results is limited. Second,

the use of an already completed fraud checklist in the experiment may also have influenced the

results. Third, the participant’s total time for completing the experiment was not measured.

10

Therefore, it remains unclear whether participants in one mindset sample spent significantly

more time on the experiment than participants in the other mindset sample.

This thesis is structured as follows. Chapter 2 provides theoretical background by reviewing

relevant literature about fraud and mindsets, followed by a development of the hypothesis.

Chapter 3 elaborates on the research methodology used in this thesis, while Chapter 4 describes

the results from the case-based experiment. Lastly, Chapter 5 includes a discussion of the

conclusion and the limitations of the study; the chapter also provides directions for future

research.

11

2 Theoretical background and hypothesis development

2.1 Fraud

This section explains the concept of fraud using SAS No. 99 and relevant literature. In particular,

this section sheds light on the characteristics of fraud, the types of fraud and the occurrence of

fraud using the fraud triangle.

2.1.1 Characteristics of fraud

Each year companies are required to issue an annual report, which is a report regarding the

company’s activities and position. Usually, this report consists of four financial statements,

including a balance sheet, an income statement, a statement of changes in equity and a cash flow

statement. In addition to these financial statements, the annual report contains a management

discussion and analysis. To minimize the risk of having deviation in the report, companies are

obliged by law to hire an audit firm to audit their annual report. In the event that a company’s

financial statements contain a deviation, this can be due to error or fraud. The basic principle for

evaluating whether a deviation is the result of error or fraud depends on whether the action

which causes a deviation is unintentional or intentional (AICPA, 2002, p. 1721). The AICPA

(2002, p. 1721) states that “fraud is an intentional act that results in a material misstatement in

financial statements that are subject of an audit”. Alternatively, the Dutch institute for auditors

defines fraud as an intentional act or negligence to act involving deception in order to obtain an

advantage, and of which the extent is of such a magnitude that the decisions made based on the

financial statements can be influenced by this deception (NBA, 2010, p. 386). Fraud can be

committed by one or multiple members of management, those charged with governance,

employees or third parties (NBA, 2016).

Although the definition of fraud by the two institutes differs in terms of precision, the

core of both definitions is quite similar. Based on both definitions, this study defines fraud to be

an intentional act by one or multiple individuals involving deception and this act results in a

material misstatement in financial statements that are subject to audit. In this definition, a

material misstatement refers to a misstatement that can influence the decisions made based on

the financial statements, and fraud risk refers to the risk that the financial statements are

materially misstated due to fraud.

12

2.1.2 Types of fraud

Two types of misstatements due to fraud are of interest to an auditor when conducting an audit.

Both misstatements result in financial statements that are not presented in all material respects,

in accordance with generally accepted accounting principles (GAAP) (AICPA, 2002, p. 1722).

The first type of misstatement is a material deviation arising from fraudulent financial reporting

(NBA, 2010, p. 391). This type of fraud consists of intentional inaccuracies, deletion of

amounts, or disclosures in the financial statements (AICPA, 2002, p. 1722). According to the

AICPA, this can be achieved using one of the following three methods. The first method

consists of exercising influence on accounting records or accompanying documents from which

the financial statements are compiled (AICPA, 2002, p. 1722). The second method entails

representing information incorrectly in the financial statements or keeping information out of

the financial statements on purpose (AICPA, 2002, p. 1722). The last method involves the

misapplication of GAAP, and this results in inaccuracy with amounts, classification, presentation

or disclosure (AICPA, 2002, p. 1722). The methods for accomplishing fraudulent financial

reporting make it likely that upper management is directly involved in the fraud or is complicit

(Coram et al., 2008, p. 545). Also, public disclosure of a misstatement arising from fraudulent

financial reporting means significant deficiencies in either internal controls, corporate

governance structures, or both (Coram et al., 2008, p. 545).

The second type of misstatement to consider is a deviation arising from misappropriation

of assets (NBA, 2010, p. 391). Examples of misappropriation of assets at the expense of the

company include embezzlement of receipts or theft of assets that belong to the company or

letting a company pay for undelivered goods or services (AICPA, 2002, p. 1722). Furthermore,

misappropriation of assets may also be done in order to deliver benefits to the company, such as

improperly obtaining subsidies (NBA, 2010, p. 391). To cover up misappropriation of assets, the

method of producing incorrect or deceptive records or documents is often used (NBA, 2010, p.

392). Although both types of misstatements are of interest to auditors, auditors considering fraud

during an audit of financial statements seem to pay more attention to the first type of

misstatement (Chadwick, 2000).

2.1.3 Fraud triangle

Multiple studies about fraud risk have used the interaction of three elements to explain why a

person may decide to commit fraud; these elements include attitude, incentive and opportunity

(Cressey, 1973; Albrecht et al., 1984; Loebbecke et al., 1989). These three together are referred to

as the fraud triangle. The first element attitude means that individuals need to have a certain

13

attitude that rationalizes their behaviour to commit fraud (Wilks & Zimbelman, 2004, p. 725).

The next element—incentive—is sometimes referred to as the motivation element, and it entails

that a person has an incentive or is motivated to commit fraud because of a perceived pressure

(Wilks & Zimbelman, 2004, p. 724). Lastly, the opportunity element consists of conditions or

situations that create an opportunity for a person to engage in fraudulent activities (Wilks &

Zimbelman, 2004, p. 724).

When all three elements exist in a certain setting, it is likely that fraud can be committed

or has already been committed (Loebbecke et al., 1989, p. 4). Bell and Carcello (2000) found

evidence that is consistent with this assertion. In their study, they developed and tested a logistic

regression model that estimates the probability of fraud, and they have found that a number of

fraud risk factors are associated with fraud. These factors associated with fraud cover all three

elements of the fraud triangle. They include weak internal controls, rapid growth, management

mainly focused on meeting analysts’ expectations, management lying to the auditor or

management not being available often on purpose, ownership status, and a connection between

weak internal controls and management’s aggressive attitude with regard to financial reporting

(Bell & Carcello, 2000, pp. 177-178). A later study by Rezaee provided additional evidence for

the earlier mentioned assertion (2005). He analysed five alleged fraud firms and found evidence

that the fraud triangle elements are present in all these firms (Rezaee, 2005).

By contrast, if one of the elements does not exist, the probability that fraud has occurred

is low, as well as the probability of it happening in the future (Loebbecke et al., 1989, p. 4).

Keeping this in mind, the authors argue that auditors need to examine to what extent the

attitude, incentive and opportunity elements are present. Subsequently, the results of the analysis

are summarized in an overall conclusion (Loebbecke et al., 1989, p. 4). According to the authors,

when one of the elements is absent, the overall conclusion would be that the risk of fraud is

equal to zero. However, the authors also claim that this approach of assessing the likelihood of

fraud has one issue, namely having incomplete information reduces the likelihood of fraud. It

can be the case that incomplete information is available to the auditor, the auditor obtains

incomplete information, or both (Loebbecke et al., 1989, p. 4). Loebbecke et al. (1989, p. 4)

explained this through an example about a firm in which the fraud triangle elements are present

but one of the elements is not recognized by the auditor as present. Normally, this would result

in an overall conclusion that the risk of fraud is equal to zero. To prevent this from happening,

additional work has to be done; this work consists of assessing the robustness and reliability of

the auditor’s performed procedures (Loebbecke et al., 1989, p. 4).

14

Wilks and Zimbelman (2004) tested the approach of decomposing the fraud triangle

elements in order to assess the likelihood of fraud, and they then compared it with a holistic

approach. They carried out their study in response to concerns raised by the audit profession

that auditors were too much focused on finding attitude cues that imply a low fraud risk; as a

consequence, both incentive and opportunity cues that imply a high fraud risk were not

sufficiently taken into consideration (Wilks & Zimbelman, 2004, pp. 739-740). They found that

auditors assessing the likelihood of fraud using the approach that decomposes fraud assessments

in situations of low fraud risk are significantly more attentive to incentive and opportunity cues

than auditors using the holistic approach (Wilks & Zimbelman, 2004, p. 740). However, auditors

using the approach that decomposes fraud assessments in situations of high fraud risk are equally

attentive to incentive and opportunity cues as auditors using the holistic approach (Wilks &

Zimbelman, 2004, p. 740).

2.1.3.1 Attitude

In these next three sub-sections, the elements of the fraud triangle are discussed in more detail.

This sub-section concerns the attitude element, which Loebbecke et al. described as a

characteristic found in individuals that allows them to knowingly commit a crime (1989, p. 4).

According to the AICPA, multiple risk factors can lead to an attitude that rationalizes

committing fraud, including

low ethical values or standards;

non-financial management interferes excessively with selecting accounting principles

and determining estimates;

history of violations, allegations and claims;

excessive interest in stock price or earnings by management;

management committing itself to third parties to meet aggressive or unrealistic

expectations;

management not being able to quickly resolve known bugs or weaknesses in internal

controls;

management’s interest in employing unlawful methods to reduce reported earnings for

tax reasons;

number of attempts by management to approve accounting due to immateriality; and

the highly tense relation between the current or predecessor auditor and management

(AICPA, 2002, pp. 1751-1752).

15

Furthermore, the AICPA (2002, p. 1753) stated that attitude risk factors related to the

misappropriation of assets are usually not observed by the auditors. However, in the case where

auditors are informed or discover information regarding these attitude risk factors, they should

consider this information when assessing fraud risk due to the misappropriation of assets

(AICPA, 2002, p. 1753).

Multiple studies have looked into this element and investigated factors that may explain

or may affect an attitude that rationalizes criminal behaviour. The first study on this topic

examined the earnings management decisions of managers and auditors (Nelson et al., 2002).

Nelson et al. (2002) investigated whether a difference in precision of accounting standards

affects managers’ attitude to engage in earnings management, and their results indicated that this

is indeed the case. First, they found evidence that managers are more likely to engage in earnings

management with structured transactions when accounting standards are precise; when

accounting standards are imprecise, unstructured transactions are used instead (Nelson et al.,

2002, p. 192). Second, they discovered that auditors are less likely to demand adjustment of

earnings management attempts that are structured when accounting standards are precise; when

accounting standards are imprecise, auditors are less likely to demand adjustment of earnings

management attempts that are not structured (Nelson et al., 2002, p. 192). In addition, managers

were more likely to make earnings-decreasing attempts with unstructured transactions and

imprecise accounting standards (Nelson et al., 2002, p. 193). Moreover, the majority of managers’

earnings management attempts are earnings-increasing (Nelson et al., 2002, p. 193). However,

auditors are more likely to demand adjustment of those attempts, especially if material (Nelson et

al., 2002, pp. 194-195).

Hernandez and Groot (2007) also studied the attitude that managements have towards

committing fraud. However, they approached this topic from a different perspective than

Nelson et al. (2002). Using a large sample of over 5,000 client acceptance and audit continuance

assessments at a Big Four audit firm operating in the Netherlands, they investigated the nature

and degree to which the attitude of management affects fraud risk judgment of audit partners

(Hernandez & Groot, 2007). The findings of the study highlighted that attitude of management

significantly affects auditors’ fraud risk judgment. The ethical conduct of senior management is

considered to be the most important attitude factor for auditors assessing fraud risk of the

attitude factors investigated; this conduct is most strongly associated with higher auditor fraud

risk judgment (Hernandez & Groot, 2007, p. 21). Furthermore, Hernandez and Groot found

that use of aggressive accounting methods, as measured by assessments of revenue recognition

and accounting estimates, also lead to higher auditor fraud risk judgments (2007, p. 33). Lastly,

16

they investigated the effects of both auditor-management relationships and senior management

experience and skill on auditor fraud risk judgment. The results showed these factors to be

important in that they affect the overall fraud risk, but these results are only significant for

situations of lower fraud risk levels (Hernandez & Groot, 2007, pp. 33-34).

In contrast to the first two studies mentioned, Gillett and Uddin (2005) specifically

investigate the attitude of one type of manager, the Chief Financial Officer (CFO). The authors

obtained data from 139 CFOs via a survey, and they found that a firm’s size affects a CFO’s

intention to commit financial reporting fraud (Gillett & Uddin, 2005, p. 73). According to the

authors, CFOs of large companies tend to be more likely to commit financial statement fraud

(Gillett & Uddin, 2005, p. 73).

2.1.3.2 Incentive

As mentioned earlier, the incentive element entails that a person has an incentive or is motivated

to commit fraud because of a perceived pressure (Wilks & Zimbelman, 2004, p. 724). The

AICPA listed four incentive risk factors for financial reporting fraud and two for the

misappropriation of assets. The incentive risk factors for financial reporting fraud include the

following conditions: (a) the financial stability or profitability of the company is threatened, (b)

the management is under high pressure to meet expectations of third parties, (c) information is

available that the personal financial position of management or persons charged with governance

is threatened by the company’s performance, and (d) management is under high pressure to meet

targets (AICPA, 2002, pp. 1749-1750). The incentive risk factors for misappropriation of assets

are employees who have personal financial obligations or a negative relation with the company,

and who are able to misappropriate company assets (AICPA, 2002, p. 1752). The current

literature focused on incentive risk factors for financial reporting fraud, and it identified four

perceived pressures which can provide an incentive for a person to commit financial reporting

fraud by illegally managing earnings. These perceived pressures include the need for external

financing, prevention of debt covenant restrictions, compensation scheme and poor business

results.

Using a sample of companies subject to actions by the Securities and Exchange

Commission (SEC) for violating GAAP, Dechow et al. (1996) examined motives for earnings

management. Their results suggested two important motives for earnings management: the

desire to raise external capital at a low cost and the prevention of debt covenant limitations

(Dechow et al., 1996, p. 30).

17

Research literature have provided mixed results regarding compensation as a motivation

for engaging in fraudulent financial reporting, but the majority of the studies find a relation

between the two (Beneish, 1999a; Burns & Kedia, 2006; Efendi et al., 2007). The study by

Erickson et al. is an example of a study that contradicts the majority of the research on

compensation and financial reporting fraud (2006). Their study investigated the equity incentives

of executives and financial reporting fraud, and they found no consistent empirical evidence to

suggest that financial reporting fraud is more likely to occur as the total equity incentives of

executives become more sensitive to fluctuations in stock prices (Erickson et al., 2006, p. 140).

Furthermore, the study provided evidence that managements’ sales of stocks and exercises of

stock options are not significantly higher for fraudulent firms compared to non-fraudulent firms

(Erickson et al., 2006, p. 140).

Apart from this study, multiple studies have found a relation between compensation and

fraudulent financial reporting, such as the study by Efendi et al. (2007). Using a sample of firms

that corrected their annual report, they discovered that the probability of a misstated annual

report increases when the Chief Executive Officer (CEO) has a significant amount of stock

options in-the-money (Efendi et al., 2007, p. 703). The term in-the-money means that the current

share price of the share connected to the stock option is below the strike price of the stock

option. This provides the holder of the stock option a possibility to sell the share above its

current share price. Furthermore, the results suggested that irregularities in financial statements

are more likely to occur for companies limited by an interest coverage debt covenant or raising

new external capital (Efendi et al., 2007, p. 703). This finding is consistent with the findings of

the aforementioned study by Dechow et al. (1996). The study by Burns and Kedia showed

similar results with regard to stock options and probability of financial statement fraud (2006).

Specifically, they found that CEO compensation schemes have an impact on the use of

aggressive accounting methods that lead to a restatement of the financial statements (Burns &

Kedia, 2006, p. 63). In particularly, CEOs who have stock option packages which are more

sensitive to share prices are more inclined to engage in financial statement fraud (Burns & Kedia,

2006, p. 63). An earlier study by Beneish examined incentives and sanctions related to earnings

management, and the findings of this study further strengthens the claim that compensation is

related to financial statement fraud (1999a). Their results showed that managers in companies

that opportunistically increase their earnings are more likely to sell their shares and stock options

before public disclosure of the irregularity than managers in control companies (Beneish, 1999a,

p. 454). These findings have suggested that a motivation for managers to overstate earnings is

selling shares and stock options at higher prices (Beneish, 1999a, p. 454). Additional evidence for

18

this view has been provided by Denis et al. (2006). They found a significant positive relation

between the probability of fraud and executive stock option incentives (Denis et al., 2006). Their

results have corroborated the view that executive stock option packages lead to an increased

likelihood that executives commit fraud (Denis et al., 2006).

Lastly, Rosner (2003) focused on opportunistic earnings manipulation in poor

performing companies. She examined whether poor performing firms before bankruptcy are

more inclined to engage in earnings manipulation. Her results showed that poor performing

companies have significantly lower cash flows, which is reflected by earnings-increasing

manipulation in non-going-concern years and subsequent reversal in going-concern years

(Rosner, 2003, p. 401).

2.1.3.3 Opportunity

According to Wilks and Zimbelman, the opportunity element consists of conditions or situations

that create an opportunity for a person to engage in fraudulent activities (2004, p. 724). In

section 85 of SAS no. 99, the AICPA listed multiple risk factors that can increase the

opportunity to commit fraud (2002, pp. 1750-1751). The AICPA provided the following as risk

factors that can create an opportunity to commit financial reporting fraud: (a) the nature of the

industry or the company’s operations, (b) insufficient monitoring of management, (c) complex or

unstable organizational structure, and (d) inadequate internal control components (2002, pp.

1750-1751). The literature provided a number of studies that have investigated whether these risk

factors in practice create an opportunity to engage in financial reporting fraud. These studies

have mainly focused on insufficient monitoring of management and inadequate internal control

components as opportunity risk factors.

One of the first studies that focused on these risk factors is the study by Loebbecke et al.

(1989). This study analysed auditors’ experience with material misstatements. In particular, the

authors examined audit partners’ experience with material misstatements of a then Big Eight

audit firm using a survey. The results of the survey indicated that two situations clearly expand

the opportunity to commit fraud: dominated decisions by management and a weak internal

control environment (Loebbecke et al., 1989, p. 20). Using data from 64 Australian firms

obtained through a survey, Rae and Subramaniam have studied the second finding in more depth

(2008). Their results indicated that the probability of fraud occurring is higher in situations

characterized by low Internal Control Procedures (ICP) quality and poor employee perceptions

of organizational justice (Rae & Subramaniam, 2008, p. 119). In other words, a strategy that sets

19

high ethical values within the company and leads to high ICP quality reduces opportunity to

commit fraud (Rae & Subramaniam, 2008, p. 120).

Beasley (1996) specifically investigated whether board composition affects the likelihood

of financial statement fraud and how this occurs. He found that there are fewer outside directors

on boards of fraudulent firms than non-fraudulent firms (Beasley, 1996, p. 463). In fact, adding

outside members to the board leads to more adequate monitoring of management which in turn

reduces the opportunity to commit financial statement fraud (Beasley, 1996, p. 463). This finding

has proven to be consistent with the results of the study by Farber, which has used a control

sample to compare 87 companies classified by the SEC as fraudulent firms—fraudulent because

they were illegally manipulating their financial statements (2005, p. 560). His results also showed

that fraudulent firms have fewer outside members on the board of directors (Farber, 2005, p.

560). Furthermore, he found significant evidence that suggests fraudulent firms have fewer

financial experts on the audit committee and fewer audit committee meetings (Farber, 2005, p.

560). Also, they are less often audited by Big Four audit firms, and they more often have a CEO

who is also the chairman of the board of directors (Farber, 2005, p. 560).

Finally, a couple of studies have paid specific attention to audit committees and financial

statement fraud. Abbott et al. (2004) analysed whether multiple audit committee characteristics

affect the probability of financial statement fraud and how this occurs. Using two samples

consisting of 44 companies alleged of fraud and 44 control companies, the authors found that

audit committee expertise and independence are negatively associated with the likelihood of

fraud (Abbott et al., 2004, pp. 80-83). Further studies that have investigated audit committee

characteristics and the likelihood of financial statement fraud showed that the presence of

financial experts on the audit committee is negatively associated with the likelihood of financial

statement fraud (McDaniel et al., 2002; Bédard et al., 2004).

The AICPA also formulated opportunity risk factors that can increase the likelihood of

misappropriation of assets. This can be a particular characteristic or condition, such as (a) a

process involving a lot of cash; (b) an inventory consisting of small, valuable or highly demanded

items; (c) assets that can easily be converted or the possession of small, marketable fixed assets;

or (d) fixed assets of which identification of ownership is difficult (AICPA, 2002, pp. 1752-

1753). Furthermore, the AICPA mentioned insufficient internal control over a company’s assets

as an opportunity risk factor (AICPA, 2002, pp. 1753). The literature included multiple studies

which examine the relation between internal control over a company’s assets and the likelihood

of misappropriation of assets.

20

The first important study to mention in this respect is the one by Coram et al. (2008).

They focused on the second opportunity risk factor provided by the AICPA—which is

insufficient monitoring of assets—and they measured this factor using the presence of an

internal auditor department (Coram et al., 2008). Many companies have an internal auditor

department to ensure that prior to the audit of the financial statements, there is a low probability

of the second type of misstatement, which is the misappropriation of assets. The authors

examined whether such a department indeed leads to a lower probability of the second type of

misstatement. The results of their study highlighted that companies with an internal auditor

department are better able to detect and self-publish the second type of misstatement than

companies that do not have such a department (Coram et al., 2008, p. 557). In other words, an

internal auditor department is effective in reducing the probability of the second type of

misstatement in the financial statements. This point suggested that the presence of an internal

auditor department can give an auditor an useful indication of a company’s internal control over

assets.

Second, the study by Mustafa and Youssef extended the aforementioned research on

audit committees and financial reporting fraud by looking at whether the financial expertise and

the independence of members in an audit committee affect the probability of misappropriation

of assets (2010, p. 221). They found that an increase in financial expert members and

independent members in an audit committee leads to a decrease in the probability of

misappropriation of assets (Mustafa & Youssef, 2010, p. 221). An important point to note is that

the additional tests showed how independent financial expert members are significantly

negatively associated with the likelihood of misappropriation of assets, but independent

members without financial expertise are not significantly negatively associated with

misappropriation of assets (Mustafa & Youssef, 2010, p. 221). This finding indicated that an

independent member of an audit committee can only reduce the likelihood of misappropriation

of assets if this member has financial expertise (Mustafa & Youssef, 2010, p. 221).

2.1.4 Summary

In summary, fraud can defined as an intentional act by one or multiple individuals involving

deception that results in a material misstatement in financial statements which are subject to

audit. As mentioned, a material misstatement is referred to as a misstatement that can influence

the decisions made based on the financial statements, and fraud risk can be explained as the risk

that the financial statements are materially misstated due to fraud. Two types of material

misstatements due to fraud are of interest to an auditor considering fraud in an audit—the first

21

type is a material deviation arising from financial reporting fraud, and the second is a material

deviation arising from misappropriation of assets. In the literature, the occurrence of these two

material misstatements due to fraud are explained by the interaction of the three elements in the

fraud triangle. These elements are attitude (rationalizes fraudulent activity), incentive (provides

motivation to commit fraud) and opportunity (creates possibility to carry out fraudulent activity).

When all three elements are present in a situation, it is likely that fraud is committed or will be

committed in the future. Many studies have investigated the elements of the fraud triangle; for

each element, these studies have provided a lot of risk factors that are associated with the

likelihood of a material misstatement due to fraud. Many of these risk factors are included in

SAS No. 99. As a result, the risk factors formulated in SAS No. 99 should provide adequate

support to an auditor in assessing the degree to which the elements of the fraud triangle are

present in the company under audit.

2.2 SAS No. 99: Consideration of fraud in a financial statement audit

In elaborating on the concept of fraud, this section explains the role of the auditor with regard to

the consideration of fraud in an audit. Subsequently, the section explores literature that has

investigated the effectiveness of tools which are incorporated into the fraud related standard of

SAS No. 99. This standard has provided guidance on how auditors should assess fraud risk, and

it introduced several tools to support auditors in carrying out a fraud risk assessment.

2.2.1 The role of the auditor

According to International Standard on Auditing (ISA) 200, the role of an auditor consists of

two parts (2009, p. 74). The auditor’s two-part role is “to obtain reasonable assurance about

whether the financial statements as a whole are free from material misstatement, whether due to

fraud or error, and to report on the financial statements, and communicate as required by the

ISAs, in accordance with the auditor’s findings” (ISA, 2009, p. 74). This definition has also been

incorporated into national legislation (NBA, 2010, p. 208; AICPA, 2012, p. 79). Furthermore,

ISA 200 also described that the term reasonable assurance must be interpreted as a high but not

absolute level of assurance since performing an audit has limitations; these limitations lead to the

majority of the audit evidence of the auditor as being compelling but not conclusive (2009, p.

73). This point was confirmed by Ruhnke and Lubitzsch, who found that there is a boundary to

the maximum level of assurance that can be provided based on the audit evidence of the audited

subject matter (2010). The precise meaning of this term has been ambiguous over a long period

22

of time until a definition was finally introduced by the AICPA in 2004 (Roberts & Dwyer, 1998,

p. 572; Christensen et al., 2012, p. 137).

To fulfil the auditors’ role with regard to fraud in a financial statement, an auditor starts

with a fraud risk assessment of the company under audit. The auditor then responds to the

results of the assessment by exercising professional scepticism in collecting and evaluating audit

evidence (AICPA, 2002, p. 1732). Professional scepticism entails that an auditor (a) has a

questioning mind and (b) critically assesses the competency and sufficiency of audit evidence

(AICPA, 2002, p. 1724). The auditor can respond in a number of ways (AICPA, 2002, p. 1732).

For example, the auditor can decide to design additional or other audit procedures for collecting

additional reliable audit evidence substantiating the financial statements or to collect further

confirmation on managements’ explanations and statements on material matters (AICPA, 2002,

p. 1732). Finally, auditors evaluate the audit evidence and report on the financial statements in

accordance with the auditor’s findings. In the case where auditors finds misstatements that are or

may be the result of fraud, they are required to investigate the implications (AICPA, 2002, p.

1745). SAS No. 99 states the follow-up steps that auditors need to take in response to the

outcomes of the investigation (AICPA, 2002, pp. 1745-1748).

2.2.2 Fraud risk assessment tools

According to SAS No. 99, three steps are essential for carrying out an effective fraud risk

assessment (AICPA, 2002, pp. 1725-1732). The first step entails collecting the information

needed for identifying the risks of material misstatement due to fraud (AICPA, 2002, p. 1725).

This essential information about the risk of fraud is collected through inquiry of management

and others persons within the company about the risk of fraud (AICPA, 2002, p. 1726).

Furthermore, several items need to be considered in this step, including (a) the outcomes of the

analytical procedures performed in the planning phase, (b) the fraud risk factors, and (c) other

possible useful information such as the outcomes of brainstorming sessions (AICPA, 2002, pp.

1728-1729). The second step involves processing the collected information and identifying fraud

risks that may lead to a material misstatement (AICPA, 2002, p. 1729). The third and final step

consists of assessing the identified fraud risks; an evaluation of the company’s programs and

controls that tackle the fraud risks also need to be kept in mind (AICPA, 2002, p. 1731).

A number of studies have examined fraud risk assessments. In particular, these studies

have investigated the aforementioned tools in SAS No. 99 that are used for collecting the

required information. The most important studies in this respect are discussed in the next

subsections.

23

2.2.2.1 Inquiries

According to Hirst and Koonce, inquiry of client personnel is a frequently used tool by auditors

for developing explanations for unexpected differences in the planning stage of the audit (1996,

p. 463). However, multiple studies have suggested that audit quality could be impaired when this

audit evidence is collected and used by the auditor (Bedard & Biggs, 1991, p. 88; Glover et al.,

2000, p. 42). In response to these findings, Krishnamoorthy and Wright specifically investigated

the value of management inquiry (1999). They provided a framework for auditors that enables

them to assess the value of the evidence collected from management inquiry (Krishnamoorthy &

Wright, 1999, p. 5). The study used three factors which seem to be important in assessing the

value of management inquiry (Krishnamoorthy & Wright, 1999, p. 16). These factors are

management objectivity, management competence and risk of misstatement (Krishnamoorthy &

Wright, 1999, p. 16). First, Krishnamoorthy and Wright found that audit evidence collected

from management inquiry is of high explanatory value only when the audit client is both

objective and competent (1999, p. 16). Second, the possible value of explanations from

management is greatest when the risk of misstatement is high (Krishnamoorthy & Wright, 1999,

p. 16). Third, in the case where financial reporting fraud is suspected and the objectivity of

management is questioned as a result, the value of explanations from management inquiry is low

(Krishnamoorthy & Wright, 1999, p. 16). Finally, when misappropriation of assets is suspected,

the value of explanations from management inquiry can be high, but only if management is

competent to assess the risk of fraud (Krishnamoorthy & Wright, 1999, p. 16). However, it

seems that auditors do not often evaluate managements’ competence in assessing the risk of

fraud (Krishnamoorthy & Wright, 1999, p. 16). Overall, this study suggests that management

inquiry can be a useful tool for collecting audit evidence, but auditors need to exercise much care

in using this audit evidence because the value varies significantly depending on the situation.

2.2.2.2 Analytical procedures

According to the AICPA, analytical procedures consists of comparisons of reported amounts—

or ratios calculated using those reported amounts—to auditors’ expectations (1989, p. 1889). The

difference in complexity of the various analytical procedures is rather great (Green & Choi, 1997,

p. 14). Beneish developed and tested a model in order to predict and detect financial statement

fraud (1999b). The variables of the model consists of reported amounts as well as financial ratios

(Beneish, 1999b, p.25). His results showed that some of the incorporated variables in the model

24

are useful in detecting companies that commit financial statement fraud (Beneish, 1999b, p. 33).

Furthermore, he found that some of the variables have predictive or discriminatory power

(Beneish, 1999b, pp. 33-34). Nevertheless, it should also be noted that the model has a large rate

of classification errors (Beneish, 1999b, p. 34). This is due to the fact that the model captures

both distortions that result from manipulation and distortions that are the result of another

cause, such as material acquisition, a change in the company’s strategy, or a change in the

company’s external environment (Beneish, 1999b, p. 34).

Kaminksi et al. focused specifically on the efficacy of analytical procedures that use

financial ratios to identify fraud risk (2004, p. 26). They compared 21 financial ratios of 79

matched fraudulent and non-fraudulent companies over multiple years (Kaminski et al., 2004, p.

17). They discovered that some of the financial ratios differed significantly between fraudulent

and non-fraudulent companies (Kaminski et al., 2004, p. 26). However, these financial ratios

were not significant across the investigated period of time (Kaminski et al., 2004, p. 26).

Therefore, Kaminski et al. concluded that the efficacy of analytical procedures that use financial

ratios to identify fraud risk is limited (2004, p. 26). Overall, it seems that analytical procedures are

not ineffective, but their contribution is modest.

2.2.2.3 Fraud checklists

In general, auditors make use of standard fraud checklists that are situated around the three

elements of the fraud triangle in order to collect information on the fraud risks factors in the

company under audit (Shelton et al., 2001, p. 25; Mock & Turner, 2005, p. 62). Although such a

checklist is intended to support the fraud risk assessment, the studies are not convinced that

such a checklist is actually beneficial. Early research was conducted by Pincus, who used a field

experiment to investigate the effectiveness of a red flags checklist for assessing fraud risk (1989).

The results of the study showed that the use of a fraud checklist does not significantly affect the

fraud risk assessment in a no-fraud setting (Pincus, 1989, p. 161). Even more importantly, the

use of such a checklist in a fraud setting significantly affects the fraud risk assessment negatively

(Pincus, 1989, p. 161). In the fraud setting, the fraud risk assessments of the participants who did

not use a fraud checklist were about one-third higher than the participants who used a fraud

checklist (Pincus, 1989, p. 161). According to Asare and Wright, it is difficult to generalize these

findings for two reasons (2004, p. 330). First, the study was carried out in a period of time when

auditors were not obliged to take responsibility for assessing fraud risk and detecting fraud

(Asare & Wright, 2004, p. 330). Second, the fraud checklist used in the study was merely one

long list of fraud risk factors; it contained no categorizations of fraud risk factors (Asare &

25

Wright, 2004, p. 330). A related study by Mock and Turner focused specifically on fraud

checklists and fraud risk factors (2005). They found that auditors using a fraud checklist do not

often identify fraud risk factors in addition to the fraud risk factors listed in the fraud checklist;

auditors also tend to tick off more fraud risk factors when the length of the checklist increases

(Mock & Turner, 2005, p. 74). Furthermore, the authors showed that auditors who did not use a

checklist identified more fraud risk factors than auditors who did use a checklist (Mock &

Turner, 2005, p. 74). However, the impact of the last finding on the fraud risk assessment

remains unknown since the authors did not investigate this area in their study.

The study by Asare and Wright extended the scope of research literature by investigating

whether the use of fraud checklists affects the fraud risk assessment while taking into account

the limitations of earlier research (2004). As mentioned in section 2.2.1, auditors currently do

have the responsibility to report that the financial statements are not materially misstated due to

fraud. Furthermore, an updated fraud checklist which categorizes the fraud risk factors is used

(Asare & Wright, 2004, p. 335). The results of the study showed that auditors who do not use a

fraud checklist provide a more accurate fraud risk assessment than auditors who do use a fraud

checklist (Asare & Wright, 2004, p. 341). This point is consistent with the findings of Pincus

(1989). Overall, the research literature has criticized the effectiveness of fraud checklists in

assessing fraud risk rather than confirmed the effectiveness.

2.2.2.4 Brainstorming

SAS No. 99 introduced a new tool for improving auditors’ fraud judgments, brainstorming,

which is mandatory for every financial statement audit (AICPA, 2002, p. 1724). According to the

AICPA, a brainstorming session should consist of an exchange of ideas among the audit team

regarding (a) the susceptibility of the company’s financial statements to material misstatement

due to fraud, (b) managements’ ability to commit and conceal financial reporting fraud, and (c)

the ways in which assets belonging to the company could be misappropriated (AICPA, 2002, p.

1724). Furthermore, a brainstorming session should emphasize the importance in maintaining a

questioning mind and exercising professional scepticism during the audit (AICPA, 2002, pp.

1724-1725).

Carpenter investigated the effectiveness of fraud brainstorming audit teams using an

experiment in which forty audit teams performed brainstorming sessions; each team consisted of

a staff auditor, a senior and a manager (2007, pp. 1125-1126). First, the results suggested that

fraud brainstorming audit teams come up with more quality fraud ideas than individual auditors

even though the teams may have a fewer number of fraud ideas (Carpenter, 2007, p. 1136).

26

Second, fraud brainstorming audit teams come up with new quality fraud ideas that were not

previously considered by the members of the audit team (Carpenter, 2007, p. 1136). Third, prior

to a fraud brainstorming session, the fraud risk assessments made by audit team members are

significantly lower than their assessments after a brainstorming session, particularly when fraud is

present (Carpenter, 2007, p. 1136). In summary, these findings have suggested that the

effectiveness of financial statement audits can improve when a fraud brainstorming session is

mandatory for performing a financial statement audit.

Brazel et al. found similar results with regard to the effectiveness of audit teams that

performed a fraud brainstorming session (2010). Using data obtained from 179 real audit

engagements, they developed and tested a measure of brainstorming quality (Brazel et al., 2010,

p. 1297). The results of their study showed that fraud risk factors are positively associated with

fraud risk assessments, and the results provided some support that brainstorming quality

moderates these associations (Brazel et al., 2010, p. 1297). Furthermore, in the case where

brainstorming quality is perceived to be higher, fraud risk assessments are more positively

associated with measures of audit procedures; these measures include the nature, timing, and

extent of audit procedures and staff who performs them (Brazel et al., 2010, p. 1297). Overall,

the findings of Brazel et al. suggested that high brainstorming quality seems to improve the audit

team’s consideration of fraud in a financial statement audit by creating a wider set of responses

for the identified fraud risks (2010, pp. 1297-1298). By contrast, a low brainstorming quality

could harm the effectiveness of the financial statement audit because this can result in

insufficient auditing (Brazel et al., 2010, p. 1298). Overall, the studies suggested that a

brainstorming session is an effective tool for auditors assessing fraud risk.

2.2.3 Summary

In summary, the auditors’ role with regard to fraud is to obtain reasonable assurance on whether

the financial statements under audit are free from material misstatement due to fraud. Auditors

cannot obtain absolute assurance because performing an audit has limitations which lead to the

majority of the audit evidence being compelling but not conclusive. To fulfil the auditors’ role,

auditors start with a fraud risk assessment of the company under audit. Typically, a fraud risk

assessment consists of three steps. In the first step, the necessary information is collected to

identify the risks of material misstatement due to fraud. The next step consists of processing the

information and identifying fraud risks that may lead to a material misstatement due to fraud.

The final step involves assessing the identified fraud risks. SAS No. 99 introduced multiple

mandatory tools for carrying out the first step of the fraud risk assessment, including inquiries,

27

analytical procedures, fraud checklists and brainstorming. The studies have provided mixed

results about the effectiveness of these tools. Management inquiry is only effective under certain

conditions, such as when the audit client is both objective and competent (Krishnamoorthy &

Wright, 1999). The effectiveness of analytical procedures is limited but not ineffective (Beneish,

1999b; Kaminski et al., 2004). The studies have criticized the effectiveness of fraud checklists in

assessing fraud risk (Pincus, 1989; Asare & Wright, 2004). Lastly, the literature has shown how

the most recently introduced tool of fraud brainstorming sessions is considered to be promising

(Carpenter, 2007; Brazel et al., 2010).

2.3 Mindsets

The previous section highlights mixed results for the effectiveness of the tools provided in SAS

No. 99. In response, this section discusses the potential of mindset theory in increasing the

effectiveness of these tools. First, the characteristics of mindsets are discussed. Second, two

mindsets are introduced, namely a mindset which reflects the current auditors’ mindset and a

potential desirable mindset. Finally, the hypothesis of this thesis is defined.

2.3.1 Characteristics

A mindset can be defined as a set of mental processes which establish a general preparedness to

react in a certain way (Freitas et al., 2004; Gollwitzer, 1990). Mindsets have been first studied in

the beginning of the 20th century in early experimental studies in psychology (Gollwitzer, 1990,

p. 63). These studies show that carrying out particular tasks activates a set of cognitive operations

(Hamilton et al., 2011, p. 14). Key characteristics of a mindset are that (a) it fosters orientations

that are not related to a specific task, and (b) it remains active when activated, even after

completion of the original task (Hamilton et al., 2011, p. 14). The implication of the first

characteristic is that mindsets impact all phases of decision-making (Griffith et al., 2015, p. 55).

These include the analysis of the problem cues in the task (Gollwitzer, 1993, p. 141), the

information sought (Heckhausen & Gollwitzer, 1987, p. 101; Henderson et al., 2008, p. 408) and

the way in which information is processed and evaluated (Gollwitzer et al., 1990, p. 1119; Taylor

& Gollwitzer, 1995, p. 213). The consequence of the second characteristic is that a mindset also

affects subsequent and separate tasks (Hamilton et al., 2011, p. 14; Freitas et al., 2004, p. 740;

Wyer & Xu, 2010, p. 121).

Mindset theory assumes that situational conditions (e.g. requirements of a certain task)

can switch a person from using one mindset to using a different mindset (Hamilton et al., 2011,

28

p. 14). One point to note is that different mindsets which consist of different sets of cognitive

processes would approach tasks in different ways; in considering this fact, it is difficult for a

person to use more than one mindset at any given time (Hamilton et al., 2011, p. 14). Hamilton

et al. compared this with individuals trying to focus their eyes on a close object and a faraway

object at the same time (2011, p. 14). As a consequence, activating a different mindset than the

current active mindset entails switching away from the current active mindset rather than using a

second mindset (Hamilton et al., 2011, p. 14).

2.3.2 Implemental mindset, deliberative mindset, and hypothesis

In this thesis, the Rubicon model of action phases is used for putting mindsets into perspective.

This model assumes that an action consists of four sequential phases (Heckhausen, 1986). The

pre-decisional phase is the first phase; in this phase, a person’s task is to deliberate and choose

between potential action goals (Gollwitzer, 1990, p. 62). In the second phase, the post-decisional

phase, a person is concerned with the initiation of actions that imply moving towards the

accomplishment of the chosen goal (Gollwitzer, 1990, p. 62). The third is the actional phase

where a person should execute the actions in an efficient way (Gollwitzer, 1990, p. 62). In the

last phase, the post-actional phase, a person evaluates the outcomes of the actions, specifically

whether the chosen goal is accomplished (Gollwitzer, 1990, p. 62). According to Gollwitzer,

carrying out these tasks activates a phase-typical mindset; a set of procedures that support task

accomplishment (1990, p. 62). To analyse mindset effects on auditors fraud risk assessment, this

thesis uses the mindset of the pre-decisional phase (deliberative mindset) and the post-decisional

phase (implemental mindset) because these are most likely to impact auditors’ inferences

(Gollwitzer & Kinney, 1989; Griffith et al., 2015). Furthermore, these mindsets are tested in an

experiment using fraud checklists, which is the most problematic tool of SAS No. 99, as

presented in section 2.2.2.3.

A deliberative mindset consists of procedures focused on analysing and weighing

advantages and disadvantages of goal alternatives, while an implemental mindset consists of

procedures focused on the timing and sequence of steps that need to be taken for accomplishing

the chosen goal (Gollwitzer, et al., 1990, p. 1120). A feature of the deliberative mindset is that it

fosters a broad focus of attention which expands beyond task relevant information (Gollwitzer

& Bayer, 1999; Heckhausen & Gollwitzer, 1987). Fujita et al. investigated this feature, and they

found that using a deliberative mindset results in the mind being more open to processing

incidental information compared to the implemental mindset (2007). Furthermore, Taylor and

Gollwitzer discovered that individuals using a deliberative mindset show fewer positive illusions

29

(i.e. they are more impartial) when processing information than individuals adopting an

implemental mindset (1995). Individuals using an implemental mindset are more biased when

processing information because this mindset stimulates a narrow focus of attention, namely a

focus on directly-related information and selective information processing in support of the

chosen goal (Gollwitzer & Bayer, 1999, p. 406; Heckhausen & Gollwitzer, 1987, p. 116).

Auditors using fraud checklists obtain separate audit evidence for each listed fraud risk

factor. Based on this evidence, they then verify whether the fraud risk factor is present or not. In

the end, they provide an overall fraud judgment based on their findings. This task resembles a

verification task because there needs to be a verification made on whether or not fraud risk

factors exist. Therefore, it is expected that auditors would use a mindset closely linked to an

implemental mindset for this task. As mentioned, this mindset supports individuals in efficiently

completing a task. This implicates that the usage of this mindset when completing fraud risk

checklists leads to auditors focusing on information that is relevant for the risk factors in the

fraud checklist. However, it is likely that this narrow focus limits auditors in considering

information that is not directly relevant to the fraud checklist but might constitute another fraud

risk factor. Mock and Turner found evidence consistent with this assertion (2005). They

discovered that auditors using a fraud checklist do not often identify other potential fraud risk

factors in addition to the fraud risk factors listed in the fraud checklist (2005). This may provide

an explanation for the finding of auditors using a fraud checklist provide significantly fewer

accurate fraud judgments than auditors who do not use a fraud checklist (Pincus, 1989; Asare &

Wright, 2004).

In response, this thesis hypothesizes that switching from an implemental mindset to a

deliberative mindset improves the effectiveness of fraud checklists in assessing fraud risk. Based

on the abovementioned procedures in the deliberative mindset, this thesis expects that auditors

using a deliberative mindset would look beyond the information that is relevant for the fraud

checklist and would process information in a more impartial manner. In this way, auditors

should be able to develop an improved overview of the existing fraud risk factors in the

company under audit. In other words, auditors should be able to provide more accurate fraud

judgments. This point leads to the following hypothesis:

H1: auditors adopting a deliberative mindset will judge fraud to be more likely than

auditors adopting an implemental mindset.

30

3 Research Methodology

3.1 Experimental design

In order to the test the hypothesis, a case-based experiment is conducted. The experiment has a

two by one factorial design; in the experiment, the dependent variable is the participants’

assessment of the fraud risk in a company that is presented in a case scenario. The case provides

information on a fictitious client of the Big Four audit firm which the participant works for. The

information provided consists of (a) the background of the company, its industry, competition,

and its management and (b) a fraud risk factor checklist completed by an audit senior. Based on

the provided information, the participants were asked to give their judgment of the risk material

misstatement due to fraud. Before the participants read the information and gave their judgment,

they were all asked to read a different case about a potential client, a listed construction company

that is obliged by Dutch law to choose a new audit firm for carrying out their statutory audit for

next year. The participants were asked to imagine that they work for a Big Four audit firm as an

auditor and that their firm is considering writing a proposal to win the construction company.

The task given right after presenting this case was used for manipulating the mindset of the

participant in the experiment. One half of the participants were asked to list three advantages

and disadvantages of winning the construction company, while the other half of the participants

were asked to list six steps they would take in their attempt to win the construction company.

3.2 Sample and procedures

In total, 36 auditors from a Big Four audit firm operating in the Netherlands participated in the

experiment. The deliberative mindset condition of the experiment was completed by 18 auditors

and the implemental mindset condition by 18 auditors. At the end of the experiment, the

participants were asked to answer a couple of questions regarding their demographics, namely

their age, gender, function, and years of experience as an auditor. The demographics of the

participants in the experiment are summarized in Table 1. Regarding the profiles of the

participants, a vast majority of them were males. The function of the participants ranged from

Junior Staff to Director, and most of them had multiple years of experience as an auditor.

The experiment was carried out using a questionnaire that was given to the participants.

This questionnaire was available in hard-copy and in an electronic version; most of the

participants completed the electronic version, and only three participants completed the paper

version. Prior to completing the questionnaire, the participants were told that the questionnaire

31

consists of three parts. The first part contains a case of an audit firm rotation with one question,

the second part contains a fraud risk assessment case with one question, and the third part

contains four questions about the demographics of the participant. Furthermore, the participants

were told to keep in mind that this experiment is not a test, and there are no correct or incorrect

answers. Besides these instructions, a consent form was included on the front page, and it

informed the participants about the study, including the purpose, procedures, risks and benefits

of the experiment, the confidentiality of the participants, the contact person, and voluntary

participation in and withdrawal from the experiment.

Table 1

Demographic data of the participants Number of participants (#) Percentage of participants (%)

Participants

Deliberative mindset 18 50

Implemental mindset 18 50

Total participants 36 100

Age

20-25 9 25

26-30 17 47

31-35 6 17

36-40 4 11

Gender

Male 28 78

Female 8 22

Year(s) of experience

as an auditor

0-3 15 42

4-6 8 22

7-9 5 14

10-12 4 11

13-15 3 8

16-18 0 0

19-21 0 0

22-24 1 3

Function

Junior Staff 1 3

Staff 12 33

Senior Staff 5 14

Junior Manager 7 19

Manager 4 11

Senior Manager 5 14

Director 2 6

Partner 0 0

32

3.3 Case materials and measures

In Appendices 1 and 2, the deliberative and implemental mindset condition questionnaires for

the experiment are disclosed. As mentioned earlier, the questionnaire contains two cases in total.

The first case—in combination with a question—is used for activing a deliberative mindset or an

implemental mindset. This case is developed by myself, and it concerns a listed construction

company named Total Sustainable Homes N.V. (TSH N.V.); general information is also

provided about the company’s background, turnover, net income, market position, employees,

contracts and goal for the coming five years. This case is followed by a question about

advantages and disadvantages of winning the construction company or a question about steps to

be taken to win the construction company.

After the first case, the participants were asked to read another case and a fraud risk

factor checklist completed by an audit senior. This case was originally used by Wilks and

Zimbelman (2004). In their study, they used the case together with the checklist to investigate

whether a fraud triangle decomposition of fraud risk assessments (before commenting on the

total the risk of fraud) leads to an increase in auditors’ sensitivity to indications of incentive and

opportunity risks when attitude risks of management suggest that the fraud risk is low (Wilks &

Zimbelman, 2004). To obtain both access to the case and the permission to use it for this thesis,

I contacted the authors by e-mail; Wilks replied my e-mail and sent me the case along with one

cell of their experiment. This cell was a fraud risk factor checklist indicating a low fraud risk; in

this checklist, six of the 40 fraud risk factors were present. These included four incentive risks

and two opportunity risks. This checklist was transformed into a fraud risk factor checklist

indicating a high fraud risk; this was possible using their paper. Three more incentive risks and

four more opportunity risks were marked as present in the case. This present thesis is specifically

interested in situations in which attitude risk is perceived to be low. Therefore, risks that might

have a significant impact on attitude risk are not used for creating a high fraud risk in the case.

Based on the provided information (the case and the completed fraud risk factor checklist), the

participants were asked to assess the risk of material misstatement in the financial statements due

to fraud and provide their judgment.

3.4 Manipulation and variables

The questionnaire contains one independent variable—the auditor’s mindset—which is

manipulated. The manipulation consist of a question that tries to trigger a certain mindset, which

is either a deliberative or an implemental mindset. The manipulation in the experiment, is similar

33

to the one used by Griffith et al. (2015). All participants were asked to read the same case, but

the stated question differed at the end of the case. For the participants who were asked to list

three advantages and disadvantages, a deliberative mindset was activated as the participants were

forced to analyse and weigh pros and cons. For the other participants who were asked to list six

steps, an implemental mindset was activated as they were forced to come up with the steps and

decide on the timing and sequence of the steps.

Subsequently, all the participants were asked to assess the fraud risk after reading another

case and a fraud risk factor checklist completed by an audit senior. A difference between the

fraud risk provided by the participants adopting a deliberative mindset and those adopting an

implemental mindset could suggest that an auditor’s fraud risk judgment is influenced by the

mindset he or she adopts. Moreover, if the participants adopting a deliberative mindset provide a

higher fraud risk than the participants adopting an implemental mindset, this could suggest that

auditors adopting a deliberative mindset judge fraud to be more likely.

The questionnaire consists of one dependent variable: the participants’ assessment of the

fraud risk in a company. The participants were asked to assess the fraud risk in this company on

a rating scale from 1 (indicating a low fraud risk) to 10 (indicating a high fraud risk).

34

4 Results

4.1 Preliminary analyses

In this section, the results of the preliminary analyses, which were performed on the data

obtained from the experiment, are discussed to provide a more complete picture of the data used

in this thesis.

4.1.1 Variables

To test the hypothesis of this thesis, multiple variables were used in both the questionnaire of

the experiment and the statistical analyses. For example, other variables were used aside from a

mindset and a fraud risk judgment variable; some of these other variables include gender and

audit experience. An overview of all variables used is provided in Table 2, which presents a

description and measurement for each variable.

Table 2

Variables: description and measurement

Variable Description Measurement

Mindset The first case contained a

question to activate a

deliberative mindset or a

question to activate an

implemental mindset

0 = Implemental mindset

question in the case

1 = Deliberative mindset

question in the case

Age The age of the participant Ratio

Gender The gender of the participant 0 = Male

1 = Female

Function Function of the participant

within the audit firm

0 = Junior Staff

1 = Staff

2 = Senior Staff

3 = Junior Manager

4 = Manager

5 = Senior Manager

6 = Director

7 = Partner

Experience Year(s) of experience as an

auditor

Ratio

Assessed Fraud Risk The participants’ assessment

of the fraud risk in the second

case

Rating scale from 1

(indicating a low fraud risk)

to 10 (indicating a high

fraud risk)

35

4.1.2 Descriptive statistics

In Table 3, the descriptive statistics of the variables are presented. This table lists the descriptive

statistics for the deliberative and the implemental mindset sample as well as the total sample. The

average age of the participants in the experiment is 29.11 years. Furthermore, 22% of the

participants are female (Mean = 0.22, SD = 0.422). In other words, the vast majority of the

participants are male. Also, the table shows two audit related variables: Function and Experience.

The results show that the function of the majority of the participants varies between Junior Staff,

which is the lowest function, and Manager, which is the fourth highest function (Mean = 2.67,

SD = 1.690). Lastly, the most important variable is Assessed Fraud Risk. As mentioned in Table

2, this variable measures the participants’ fraud risk assessment. The results indicate that the

participants in the deliberative mindset sample provided on average a fraud risk judgment of 7.72

(Mean = 7.72, SD = 1.074). In contrast, the participants in the implemental mindset sample

provided on average a fraud risk judgment of 7.67 (Mean = 7.67, SD = 1.237).

Table 4 presents the Pearson and non-parametric Spearman correlations for the variables

used. According to the Pearson correlation, the switch to a deliberative mindset is insignificantly

correlated with AFR (Pearson r = 0.025, p > 0.05). Furthermore, the non-parametric Spearman

correlation shows that the switch to a deliberative mindset is insignificantly correlated with AFR

(Spearman ρ = -0.074, p > 0.05).

36

Table 3

Descriptive statistics

N Minimum Maximum Mean Median SD

Age Total 36 24 40 29.11 28 4.857

Del. mindset 18 24 40 29.39 28 4.972

Imp. mindset 18 24 40 28.83 27.50 4.866

Gender Total 36 0 1 0.22 0 0.422

Del. mindset 18 0 1 0.33 0 0.485

Imp. mindset 18 0 1 0.11 0 0.323

Function Total 36 0 6 2.67 2.50 1.690

Del. mindset 18 1 6 2.67 2 1.815

Imp. mindset 18 0 6 2.67 3 1.609

Experience Total 36 1 22 6 5 4.980

Del. mindset 18 1 15 6.28 5.50 4.599

Imp. mindset 18 1 22 5.72 5 5.454

AFR Total 36 4 10 7.69 8 1.142

Del. mindset 18 6 10 7.72 8 1.074

Imp. mindset 18 4 9 7.67 8 1.237

Valid N total sample = 36, deliberative mindset sample = 18 and implemental mindset sample = 18

Table 4

Correlations

Mindset Age Gender Function Experience AFR

Mindset

- 0.081

(0.640)

0.267

(0.115)

-0.027

(0.874)

0.113

(0.512)

-0.074

(0.667)

Age

0.058

(0.737)

- -0.485**

(0.003)

0.821**

(0.000)

0.766**

(0.000)

0.191

(0.265)

Gender

0.267

(0.115)

-0.403*

(0.015)

- -0.568**

(0.000)

-0.446**

(0.006)

-0.247

(0.146)

Function

0.000

(1)

0.871**

(0.000)

-0.535**

(0.001)

- 0.907**

(0.000)

0.387*

(0.020)

Experience

0.057

(0.743)

0.848**

(0.000)

-0.367*

(0.028)

0.882**

(0.000)

- 0.388*

(0.019)

AFR

0.025

(0.886)

0.166

(0.333)

-0.211

(0.217)

0.375*

(0.024)

0.306

(0.069)

-

The Pearson correlations are presented below the diagonal.

The non-parametric Spearman correlations are presented above the diagonal.

P-values are presented between brackets (-).

* = Correlation is significant at the 0.05 level (two-tailed).

** = Correlation is significant at the 0.01 level (two-tailed).

37

4.1.3 Manipulation evaluation

In the first part of the questionnaire, the participants were asked a question after reading a case;

this is done in order activate an implemental mindset or a deliberative mindset. In the

implemental mindset sample, only one of the eighteen participants gave three instead of six

steps. By contrast, all eighteen participants in the deliberative mindset sample gave three

advantages and three disadvantages.

To evaluate the responses to the implemental mindset question, the client acceptance

procedures of Hayes et al. are used (2005). In assisting auditors in obtaining new audit clients,

these procedures include the following steps: (a) evaluating a client’s background and reasons for

the audit, (b) checking whether an auditor is able to meet ethical and competence requirements

for the client, (c) determining the need for other professionals, (d) contacting the predecessor

auditor, (e) preparing a client proposal, (f) selecting staff for the audit, and (g) obtaining an

engagement letter (Hayes et al., 2005, pp. 164-185). Table 5 lists the results of the evaluation. An

important point to note is that the results only include procedures that were directly mentioned

by the participants. The results showed that the responses of the participants account for an

average of 44% of client acceptance procedures. This suggests that the participants in the

implemental mindset sample read and answered the question quite critically.

For the evaluation of the responses to the deliberative mindset question, four distinct

categories are used. These categories are financial performance (measured by the words profit and

revenue), reputation (measured by the word reputation), knowledge (measured by the words

knowledge, resources, and experience) and workforce (measured by the words staff and employees). The

reason for choosing these categories is rather straightforward. In order to win and serve clients,

an audit firm needs a number of features, including a good reputation, sufficient knowledge and

qualified employees. Furthermore, financial performance is not only the result of these elements;

it is also a signal to potential clients of an audit firms’ audit quality. An important point to note

here is that in the case where a word is mentioned more than once in an advantage or a

disadvantage, it counts as one word. Furthermore, an advantage or a disadvantage that contains

words from multiple categories can only be used once (e.g. an advantage or a disadvantage that

contains a key word for performance cannot subsequently be used for recording a key word for

another category). The results of the evaluation are shown in Table 6. A distinction is made

between words positively and negatively mentioned. The results show that 39% of the responses of

the participants in the deliberative mindset sample fall in one of the four categories. This also

suggests that the participants in the deliberative mindset sample read and answered the question

quite critically.

38

Table 5

Evaluation responses implemental mindset sample

Procedures Number of times directly mentioned

1. Evaluate clients’ background and reasons

for the audit

16

2. Check whether auditor is able to meet

ethical and competence requirements for the

client

5

3. Determine need for other professionals 3

4. Contact predecessor auditor 3

5. Prepare client proposal 16

6. Select staff for audit 3

7. Obtain engagement letter 1

Total procedures directly mentioned 47

Total steps (18 participants x 6 steps = 108) 108

Total procedures directly mentioned as a

percentage of total steps 44%

Table 6

Evaluation responses deliberative mindset sample

Category Advantage (+) Disadvantage (-)

Performance

- Revenue 7 0

- Profit 1 4

Reputation

- Reputation 5 2

- Name 2 4

Knowledge

- Knowledge 1 0

- Resources 0 4

- Experience 2 0

Workforce

- Staff 2 4

- Employees 3 1

Words mentioned as

advantage or disadvantage 23 19

- Total words mentioned = 23 + 19 = 42

- Total advantages and disadvantages = (3 advantages x 18 participants) + (3 disadvantages x

18 participants) = 108

- Total mentioned words as a percentage of total advantages and disadvantages = (42 / 108) x

100 % = 39%

39

4.2 Hypothesis testing

This following section discusses the results of the test for the hypothesis of this thesis. The

dependent variable AFR is used for testing whether the hypothesis should be rejected or

accepted. The variable AFR provides the results of the participants’ assessment of the fraud risk

in the second case. Furthermore, three independent variables are used, namely mindset, gender

and experience. The latter two variables are included as control variables since they may have an

impact on the dependent variable AFR.

4.2.1 Auditor’s mindsets

According to section 2.3.2, the hypothesis states that auditors adopting a deliberative mindset

will judge fraud to be more likely than auditors adopting an implemental mindset. To test this

hypothesis, a regression analysis was carried out. The results of this regression analysis showed

that there was one outlier (Mahalanobis distance = 12.946, larger than the critical value of 7.81).

This outlier was later removed, and the regression analysis was performed again (n = 36 - 1 =

35). Table 7 presents the results of this regression analysis. The adjusted R-squared shows that

3.6% of the AFR variance is explained by the model. However, the AFR variance explained by

the model is not significant (F = 1.423, p = > 0.05). The table shows that the mindset beta is not

significant (t = 0.011, p > 0.05). Furthermore, both the gender and experience are also not

significant (t = -0.680, p > 0.05; t = 1.408, p > 0.05). Therefore, the hypothesis should be

rejected. Multicollinearity has not affected the analysis since the tolerance of all independent

variables is greater than 0.2 and the VIF is lower than 10.

Table 7

Regression analysis

Model

Unstandardized

Coefficients

Standardized

Coefficients

Collinearity

Statistics

B Standard

error

Beta t-value Significance

level

Tolerance VIF

Intercept 7.283 0.396 18.385 0.000

Mindset 0.005 0.419 0.002 0.011 0.991 0.842 1.187

Gender -0.254 0.530 -0.093 -0.478 0.636 0.744 1.344

Experience 0.083 0.053 0.301 1.570 0.127 0.770 1.299

Adjusted R square: 0.036

F-value: 1.423, significance level: 0.255

Dependent variable: AFR

Independent variables: Mindset, Gender and Experience

40

4.3 Additional analyses

This section provides two additional analyses to check whether the results are robust.

4.3.1 Regression analysis with interactions

The hypothesis is further tested by including two interaction variables as independent variables

to the model. These are mindset times gender and mindset times experience. The results of this

regression analysis are shown in Table 8. The adjusted R-squared shows that -2.4% of the AFR

variance is explained by the model, which means that the model does not fit the data. In other

words, the statistical power is too low to use these results.

Table 7

Regression analysis

Model

Unstandardized

Coefficients

Standardized

Coefficients

Collinearity

Statistics

B Standard

error

Beta t-value Significance

level

Tolerance VIF

Intercept 7.158 0.537 13.327 0.000

Mindset 0.255 0.843 0.112 0.303 0.764 0.220 4.537

Gender -0.267 0.952 -0.098 -0.281 0.781 0.245 4.079

Experience 0.109 0.084 0.398 1.295 0.205 0.319 3.134

Mindset

times

gender

-0.016 1.166 -0.005 -0.014 0.989 0.203 4.926

Mindset

times

experience

-0.045 0.110 -0.177 -0.408 0.686 0.160 6.234

Adjusted R square: -0.024

F-value: 0.844, significance level: 0.530

Dependent variable: AFR

Independent variables: Mindset, Gender and Experience

4.3.2 Reduced sample test

The regression test in section 4.2.1 is performed again, excluding participants who have less than

two years of experience as an auditor. A legitimate reason for this change is that auditors with

less than two years of experience have probably only carried out one fraud risk assessment per

client they serve. Furthermore, it is not likely that they have conducted a complete fraud risk

assessment but rather only an element of it. Lastly, the sample consists of a significant portion of

41

participants with less than two years of experience. Taken together, this may have an impact on

the results in section 4.2.1. For the reduced sample test, seven scores were removed compared to

the original regression analysis (n = 35 - 7 = 28); the results of the reduced sample test are

presented in Table 9. The adjusted R-squared shows that -9.2% of the AFR variance is explained

by the model, which means that the model does not fit the data. In other words, the statistical

power is too low to use these results.

Table 9

Regression analysis

Model

Unstandardized

Coefficients

Standardized

Coefficients

Collinearity

Statistics

B Standard

error

Beta t-value Significance

level

Tolerance VIF

Intercept 7.906 0.418 18.921 0.000

Mindset -0.209 0.400 -0.114 -0.522 0.607 0.842 1.187

Gender -0.066 0.584 -0.026 -0.113 0.911 0.744 1.344

Experience 0.028 0.049 0.121 0.570 0.574 0.770 1.299

Adjusted R square: -0.092

F-value: 0.245, significance level: 0.864

Dependent variable: AFR

Independent variables: Mindset, Gender and Experience

42

5 Conclusion

As mentioned, the numerous fraud scandals in the beginning of the 21st century showed how

accounting and audit laws and regulations were inadequate. In an attempt to prevent future

scandals from happening, the Sarbanes-Oxley Act of 2002 was introduced, and the AICPA also

introduced SAS No. 99 which has been effective from October 2002. However, the current

literature questions the effectiveness of multiple mandatory tools that are incorporated in SAS

No. 99 in assessing fraud risk. Furthermore, multiple studies emphasize the importance of fraud

detection and deterrence in an audit, and it is expected that this area will become even more

important in the future. Therefore, this thesis investigates whether the effectiveness of

mandatory tools incorporated in SAS No. 99 to assess fraud risk can be enhanced using mindset

theory.

According to multiple studies, a mindset can be referred to as a set of mental processes

that establish a general preparedness to react in a certain way. Key characteristics of a mindset

include fostering orientations that are not related to a specific task and remaining active after

completion of the original task. Two mindsets—a deliberative and an implemental mindset—are

tested in an experiment to examine whether a change in mindset leads to a significantly more

accurate fraud risk judgment. The tool used for this experiment is a fraud risk checklist, which

according to the literature is the worst performing tool of SAS No. 99. As mentioned, a fraud

checklist resembles a verification task, and therefore it is expected that auditors will use a

mindset closely linked to an implemental mindset. Usage of this mindset leads to auditors

focusing on information that is relevant for the risk factors in the fraud checklist. However, it is

likely that this narrow focus limits auditors in considering information that may constitute

another fraud risk factor. By contrast, usage of a deliberative mindset fosters a broad focus of

attention that expands beyond task relevant information. Furthermore, auditors using a

deliberative mindset are more impartial in processing information than auditors adopting an

implemental mindset. Therefore, this thesis expects that usage of a deliberative mindset will

improve the effectiveness of fraud checklists. In this thesis, a higher fraud risk assessment is

considered to represent an improved effectiveness of fraud checklists.

The results of the experiment provide no support for the expectation of this thesis.

Using a deliberative mindset instead of an implemental mindset does not result in higher fraud

judgments. This implies that mindset theory is not effective in enhancing the effectiveness of

fraud checklists.

43

The findings of this thesis extend the literature in two ways. Furthermore, these findings

may be interesting to both researchers and standard setters. First, the findings suggest that the

use of mindset theory is not effective in enhancing the effectiveness of mandatory tools

incorporated in SAS No. 99 for assessing fraud risk. This means that mindset theory does not

result in auditors providing more accurate fraud judgments. Second, the findings of this thesis

are inconsistent with the findings of Griffith et al. (2015). Whereas they do find evidence in their

study that suggests mindset theory is useful in audits, this study finds no evidence. This shows

that the usefulness of mindset theory depends on the task performed in the audit. Therefore,

standard setters considering to implement new mindset regulations in specific auditing standards

should be careful when implementing such regulations.

This thesis is subject to several limitations, which could potentially affect the

contributions of the findings. First, the auditors who participated in the experiment all work for

the same Big Four audit firm, and they all work at the same office location. These factors may

have affected the answers provided by the participants. As a consequence, the generalization of

the results is limited. Second, the use of an already completed fraud checklist in the experiment

may also have influenced the results. By contrast, if auditors had been asked to fill out a fraud

checklist themselves and then provide a fraud judgment, the results could be different. Third, the

participant’s total time to complete the experiment was not measured. Therefore, it remains

unclear whether participants in one mindset sample spent significantly more time on the

experiment than participants in the other mindset sample.

This thesis is the second study that addresses the effectiveness of mindset theory in

audits, and the first one that investigates mindsets and fraud judgements. Therefore, further

research is of great importance. First, this thesis is subject to several limitations that harm the

generalizability of the findings. Therefore, future research is needed for investigating a larger

sample consisting of participants from multiple audit firms, and the time participants spend on

their task to provide a fraud judgment needs to be recorded. Second, it is desirable to have future

research on mindsets and the other three tools to assess fraud risk incorporated in SAS No. 99.

These include inquiries, analytical procedures and brainstorming. Third, since it is currently

unclear how long a mindset persists, it is desirable to investigate this in future research. Finally,

future research is needed for investigating the usefulness of mindset theory in performing other

tasks which are part of a financial statement audit.

44

References

Abbott, L. J., Parker, S., & Peters, G. F. (2004). Audit Committee Characteristics and Restatements. Auditing: A Journal of Practice & Theory, 23(1), pp. 69-87.

AICPA (1989, January 1). AU Section 329: Analytical procedures. Retrieved from: http://www.aicpa.org/Research/Standards/AuditAttest/DownloadableDocuments/AU -00329.pdf

AICPA (2002, December 15). SAS No. 99: Consideration of Fraud in a Financial Statement Audit. Retrieved from: https://www.aicpa.org/Research/Standards/AuditAttest/ DownloadableDocuments/AU-00316.pdf

AICPA (2012, December 15). AU-C Section 200: Overall Objectives of the Independent Auditor and the Conduct of an Audit in Accordance With Generally Accepted Auditing Standards. Retrieved from: http://www.aicpa.org/research/standards/auditattest/downloadabledocuments/au-c- 00200.pdf

Albrecht, W. S., Howe, K., & Romney, M. (1984). Deterring fraud: The internal auditor’s perspective. Altamonte Springs, Florida: The Institute of Internal Auditors Research Foundation.

Asare, S. K., & Wright, A. M. (2004). The Effectiveness of Alternative Risk Assessment and Program Planning Tools in a Fraud Setting. Contemporary Accounting Research, 21(2), pp. 325-352.

Beasley, M. S. (1996). An Empirical Analysis of the Relation between the Board of Director Composition and Financial Statement Fraud. The Accounting Review, 71(4), pp. 443-46 465.

Beckman, J., & Gollwitzer P. (1987). Deliberative vs. Implemental States of Mind: The Issue of Impartiality in Pre-and Postdecisional Information Processing. Social Cognition, 5, pp. 259-279.

Bedard, J. C., & Biggs, S. F. (1991). The Effect of Domain-Specific Experience on Evaluation of Management Representations in Analytical Procedures. Auditing: A Journal of Practice & Theory, 10, pp. 77-90.

Bédard, J., Chtourou, S. M., & Courteau, L. (2004). The Effect of Audit Committee Expertise, Independence, and Activity on Aggressive Earnings Management. Auditing: A Journal of Practice & Theory, 23(2), pp. 13-35.

Bell, T. B., & Carcello, J. V. (2000). A Decision Aid for Assessing the Likelihood of Fraudulent Financial Reporting. Auditing: A Journal of Practice & Theory, 19(1), pp. 169-184.

Beneish, M. D. (1999a). Incentives and Penalties Related to Earnings Overstatements that Violate GAAP. The Accounting Review, 1999, 74(4), pp. 425-457.

Beneish, M. D. (1999b). The Detection of Earnings Manipulation. Financial Analysts Journal, 55(5), pp. 24-36.

Brazel, J. F., Carpenter, T. D., & Jenkins, J. G. (2010). Auditors’ Use of Brainstorming in the Consideration of Fraud: Reports from the Field. The Accounting Review, 85(4), pp. 1273-1301.

Burns, N., & Kedia, S. (2006). The impact of performance-based compensation on misreporting. Journal of Financial Economics, 79(1), pp. 35-67.

Carpenter, T. D. (2007). Audit Team Brainstorming, Fraud Risk Identification, and Fraud Risk Assessment: Implications of SAS No. 99. The Accounting Review, 82(5), pp. 1119-1140.

45

Chadwick, W. E. (2000). Keeping Internal Auditing In-house. Internal Auditor, 57(3), p. 88.

Christensen, B. E., Glover, S. M., & Wood, D. A. (2012). Extreme Estimation Uncertainty in Fair Value Estimates: Implications for Audit Assurance. Auditing: A Journal of Practice & Theory, 31(1), pp. 127-146.

Coram, P., Ferguson, C., & Moroney, R. (2008). Internal audit, alternative internal audit structures and the level of misappropriation of assets fraud. Accounting & Finance, 48(4), pp. 543-559.

Cressey, D. R. (1973). Other people’s money. Montclair, NJ: Patterson Smith.

Dechow, P. M., Sloan, R. G., & Sweeney, A. P. (1996). Cause and Consequences of Earnings Manipulation: An Analysis of Firms Subject to Enforcement Actions by the SEC. Contemporary Accounting Research, 13(1), pp. 1-36.

Denis, D. J., Hanouna, P., & Sarin, A. (2006). Is there a dark side to incentive compensation? Journal of Corporate Finance, 12(3), pp. 467-488.

Efendi, J., Srivastava, A., & Swanson, E. P. (2007). Why do corporate managers misstate financial statements? The role of option compensation and other factors. Journal of Financial Economics, 85(3), pp. 667-708.

Elliot, R. (2002). Twenty-first century assurance. Auditing: A Journal of Practice & Theory, 21(1),pp. 139-146.

Erickson, M., Hanlon, M., & Maydew, E. L. (2006). Is There a Link between Executive Equity Incentives and Accounting fraud. Journal of Accounting Research, 2006, 44(1), pp. 113- 143.

Farber, D. B. (2005). Restoring Trust after Fraud: Does Corporate Governance Matter? The Accounting Review, 80(2), pp. 539-561.

Freitas, A. L., Gollwitzer, P., & Trope, Y. (2004). The influence of abstract and concrete mindsets on anticipating and guiding others’ self-regulatory efforts. Journal of Experimental Social Psychology, 40(6), pp. 739-752.

Fujita, K., Gollwitzer, P. M., & Oettingen, G. (2007). Mindsets and pre-conscious open- mindedness to incidental information. Journal of Experimental Social Psychology, 43(1), pp. 48-61.

Gillett, P. R., & Uddin, N. (2005). CFO Intentions of Fraudulent Financial Reporting. Auditing: A Journal of Practice & Theory, 24(1), pp. 55-75.

Glover, S. M., Jiambalvo, J., & Kennedy, J. (2000). Analytical Procedures and Audit-Planning Decisions. Auditing: A Journal of Practice & Theory, 19(2), pp. 27-45.

Gollwitzer, P. (1990). Action phases and mind-sets, E. T. Higgings and R. M. Sorrentino (Eds.). Handbook of motivation and cognition, 2, pp. 53-92. New York: Guilford Press.

Gollwitzer, P. (1993). Goal Achievement: The Role of Intentions. European Review of Social Psychology, 4(1), pp. 141-185.

Gollwitzer, P. M., & Bayer, U. (1999). Deliberative versus Implemental Mindsets in the Control of Action, S. Chaiken and Y. Trope (Eds.). Dual-process theories in social psychology, pp. 403- 422. New York: Guilford.

Gollwitzer, P. M., & Kinney, R. F. (1989). Effects of Deliberative and Implemental Mind-Sets on Illusion of Control. Journal of Personality and Social Psychology, 56(4), pp. 531-542.

46

Gollwitzer, P. M., Heckhausen, H., & Steller, B. (1990). Deliberative and Implemental Mind- Sets: Cognitive Tuning Toward Congruous Thoughts and Information. Journal of Personality and Social Psychology, 59(6), pp. 1119-1127.

Green, B. P., & Choi, J. H. (1997). Assessing the Risk of Management Fraud Through Neural Network Technology. Auditing: A Journal of Practice & Theory, 16(1), pp. 14-28.

Griffith, E. E., Hammersley, J. S., Kadous, K., & Young, D. (2015). Auditor Mindsets and Audits of Complex Estimates. Journal of Accounting Research, 53(1), pp. 49-77.

Hamilton, R., Vohs, K. D., Sellier, A., & Meyvis, T. (2011). Being of two minds: Switching mindsets exhausts self-regulatory resources. Organizational Behavior and Human Decision Processes, 115(1), pp. 13-24.

Hayes, R., Dassen, R., Schilder, A., & Wallage, P. (2005). Principles of Auditing: An Introduction to International Standards on Auditing (second edition). Harlow, England: Pearson Education Limited.

Heckhausen, H. (1986). Why some time out might benefit achievement motivation research, J. H. L. van den Bercken, T. C. M. Bergen and E. E. J. De Bruyn (Eds.). Achievement and task motivation, pp. 7-39. Lisse, The Netherlands: Swets and Zeitlinger.

Heckhausen, H., & Gollwitzer, P. (1987). Thought Contents and Cognitive Functioning in Motivational versus Volitional States of Mind. Motivation and Emotion, 11(2), pp. 101- 120.

Henderson, M. D., Liver, Y. D., & Gollwitzer, P. M. (2008). The Effects of an Implemental Mind-Set on Attitude Strength. Journal of Personality and Social Psychology, 94(3), pp. 396 -411.

Hernandez, J. R., & T. Groot (2007). How Trust Underpins Auditor Fraud Risk Assessments. Working paper, Free University of Amsterdam.

Hirst, D. E., & Koonce, L. (1996). Audit Analytical Procedures: A Field Investigation. Contemporary Accounting Research, 13(2), pp. 457-486.

ISA (2009, December 15). International Standard on Auditing 200. Retrieved from: http://www.ifac.org/system/files/downloads/a008-2010-iaasb-handbook-isa-200.pdf

Kaminksi, K. A., Wetzel, T. S., & Guan, L. (2004). Can financial ratios detect fraudulent financial reporting? Managerial Auditing Journal, 19(1), pp. 15-28.

Krishnamoorthy, G., & Wright, A. (1999). A Framework for Assessing the Value of Management Inquiry. International Journal of Auditing, 3(1), pp. 5-20.

Loebbecke, J. K., Eining, M. M., & Willingham, J. J. (1989). Auditors’ experience with material irregularities: Frequency, nature, and detectability. Auditing: A Journal of Practice & Theory, 8(2), pp. 1-28.

McDaniel, L., Martin, R. D., & Maines, L. A. (2002). Evaluating Financial Reporting Quality: The Effects of Financial Expertise vs. Financial Literacy. The Accounting Review, 77, pp. 139-167.

Mock, T. J., & Turner, J. L. (2005). Auditor Identification of Fraud Risk Factors and their Impact on Audit Programs. International Journal of Auditing, 9(1), pp. 59-77.

Mustafa, S. T., & Youssef, N. B. (2010). Audit committee financial expertise and misappropriation of assets. Managerial Auditing Journal, 25(3), pp. 208-225.

47

NBA (2010, May 10). Handleiding Regelgeving Accountancy: Toelichting regelgeving. Retrieved from: https://www.nba.nl/Documents/Wet-%20en%20Regelgeving/HRA-II%20druk_10mei 2010.PDF

NBA (2016). 240 Verantwoordelijkheden accountant voor fraude ikv controle. Retrieved from: https://www.nba.nl/HRAweb/HRA1/201405/970.html

Nelson, M. W., Elliott, J. A., & Tarpley, R. L. (2002). Evidence from auditors about managers’ and auditors’ earnings management decisions. The Accounting Review, 77, pp. 175-202.

Pincus, K. V. (1989). The efficacy of a red flags questionnaire for assessing the possibility of fraud. Accounting, Organizations and Society, 14(1), pp. 153-163.

Rae, K., & Subramaniam, N. (2008). Quality of internal control procedures: Antecedents and moderating effect on organisational justice and employee fraud. Managerial Auditing Journal, 23(2), pp. 104-124.

Rezaee, Z. (2005). Causes, consequences, and deterrence of financial statement fraud. Critical Perspectives on Accounting, 16(3), pp. 277-298.

Roberts, R., & Dwyer, P. (1998). An Analysis of Materiality and Reasonable Assurance: Professional Mystification and Paternalism in Auditing. Journal of Business Ethics, 17(5),pp. 569-578.

Rosner, R. L. (2003). Earnings Manipulation in Failing Firms. Contemporary Accounting Research, 20(2), pp. 361-408.

Ruhnke, K., & Lubtizsch, K. (2010). Determinants of the Maximum Level of Assurance for Various Assurance Services. International Journal of Auditing, 14(3), pp. 233-255.

Shelton, S. W., Whittington, O. R., & Landsittel, D. (2001). Auditing Firms’ Fraud Risk Assessment Practices. Accounting Horizons, 15(1), pp. 19-33.

Taylor, S. E., & Gollwitzer, P. M. (1995). Effects of Mindset on Positive Illusions. Journal of Personality and Social Psychology, 69(2), pp. 213-226.

Wilks, T. J., & Zimbelman, M. F. (2004). Decomposition of Fraud-Risk Assessments and Auditors’ Sensitivity to Fraud Cues. Contemporary Accounting Research, 21(3), pp. 719-745.

Wyer, R. S., & Xu, A. J. (2010). The role of behavioral mind-sets in goal-directed activity: Conceptual underpinnings and empirical evidence. Journal of Consumer Psychology, 20(2), pp. 107-125.

48

Appendix 1: Questionnaire Deliberative mindset

Part A: Audit firm rotation

According to Dutch law, companies classified as Organisaties van Openbaar Belang (in

English: public-interest organisations) are obliged to switch auditors after a certain number of

years.

Due to this law on the mandatory rotation of audit firms a listed construction company named

TSH N.V. (Total Sustainable Homes N.V.) – classified as a public-interest organisation – has

to choose a new audit firm to carry out their statutory audit for next year.

TSH N.V. was founded in 1992 by two engineering students. In 2014, TSH N.V’s turnover

was 8.5 billion euro and net income 730 million euro. TSH N.V. is a leader in multiple

segments of the European construction industry including private homes, commercial

buildings and educational buildings. TSH N.V. has multiple offices throughout Europe and

operates globally in more than 37 countries. It currently employs 9,000 people that carry out

about 1,800 building contracts every year. TSH N.V.’s goal for the coming five years is

enhancing their position in current markets and entering new markets.

Imagine that you are working for a Big 4 audit firm as an auditor. Your Big 4 audit firm

considers writing a proposal to win the construction company.

As a consequence, you - as an auditor - are asked to list three advantages and disadvantages

of winning the construction company. Write the three advantages and disadvantages in one

or a few sentences in the table below.

Advantages:

1.

2.

3.

Disadvantages:

1.

2.

49

3.

Part B: Fraud risk assessment case: Oltrak, Inc.

In this part you as an auditor are asked to assess the fraud risk for a client of your audit firm.

First, please read and review the information below. The information consists of (1) company

information and (2) a fraud risk factor checklist completed by an audit senior during the

planning stage. Second, write your judgment in the answer form which is provided at the end

of the text.

Company Background

Oltrak, Inc. (a publicly traded company) is one of the leading global electronic security

companies in the world. Oltrak designs, manufactures, markets, sells and services innovative

electronic products and systems for security and surveillance, industrial video and

professional audio markets worldwide. These products and systems include video monitors,

switchers, quad processors, digital and analog recorders, multiplexers, video transmission

systems, cameras, lenses, observation systems, audio equipment and accessories. Customers

range from single location mom-and-pop businesses to universities and government facilities.

Sales to the professional security markets are through the Company’s channel partners. The

Company has increased sales from $1.8 million in 1987 to $210 million in 2000.

The following financial data have been derived from the consolidated financial statements of

the Company and its subsidiaries (in thousand $).

Year 1996 1997 1998 1999 2000

Net sales 148,977 177,837 196,998 208,200 209,998

Net income

(loss)

1,599 2,401 3,555 3,865 2,972

Total assets 172,510 185,256 196,626 200,350 193,497

Industry/Competition

The Company faces substantial competition in each of its markets. Significant competitive

factors in the Company’s markets include price, quality and product performance, breadth of

product line and customer service and support. Some of the company’s existing and potential

competitors have substantially greater financial, manufacturing, marketing and other

resources than the Company. To compete successfully, the Company must continue to make

substantial investments in its engineering and development, marketing, sales, customer

service and support activities. The Company considers its major competitors to be the CCTV

and access control operations of Sensormatic Electronics Corporation, Burle (part of Philips

Communication & Security Systems, Inc.), Panasonic, Pelco, Lenel, and Interlogics.

Management Background

The management team of Oltrak is made up of the following key individuals:

- President and CEO, George Schultz

- Vice President of Sales and Marketing, Tammy Miller

- Vice President of Operations, Chris Streeter

- Chief Financial Officer, Theo Smith

50

- Controller Fred Beck

Most of the management team has been with Oltrak since Deloitte began auditing the

company five years ago. Over the years, the management team has been very easy to work

with and shown a high level of competence. Furthermore, several sources of information

indicate that the character of the management team is of a high quality, For example, the

partner in charge of this audit has told you that the integrity of upper management is

impeccable. He also commented to you that the CEO is one of the most honourable

businessmen in the community and that he admires his leadership in local community service

organizations such as the United Way. Most people in the business community characterize

Oltrak as begin very supportive of community values and high ideals. This characterization

stems largely from the high ideals of the management team.

Fraud Risk Factor Checklist

Fraud Risk Factor: Present: Yes/No

1. Domineering management behaviour in dealing with the auditor,

especially involving attempts to influence the scope of the auditor's work.

No

2. Significant bank accounts or subsidiary or branch operations in tax-

haven jurisdictions for which there appears to be no clear business

justification.

Yes

3. Unusual rapid growth or profitability, especially compared with that of

other companies in the same industry.

No

4. Excessive interest by management in maintaining or increasing the

entity's stock price or earnings trend.

No

5. An interest by management in pursuing inappropriate means to minimize

reported earnings for tax-motivated reasons.

No

6. Frequent disputes with the current or predecessor auditor on accounting,

auditing, or reporting matters.

No

7. Lack of monitoring of controls, including automated controls and

controls over interim financial reporting (where external reporting is

required).

No

8. Difficulty in determining the organization or individual(s) that control(s)

the entity.

No

9. Known history of violations of securities laws or other laws and

regulations, or claims against the entity, its senior management, or board

members alleging fraud or violations of laws and regulations.

No

10. Formal or informal restrictions on the auditor that inappropriately limit

access to people or information or the ability to communicate effectively

with the board of directors or audit committee.

No

11. Significant related party transactions not in the ordinary course of

business or with related entities not audited or audited by another firm. Yes

12. Perceived adverse consequences on significant pending transactions,

such as business combinations or contract awards, from reporting poor

financial results.

No

13. Nonfinancial management's excessive participation in, or

preoccupation with, the selection of accounting principles or the

determination of significant estimates.

No

51

14. High degree of competition or market saturation, accompanied by

declining margins. Yes

15. A practice by management of committing to analysts, creditors, and

other third parties to achieve aggressive or unrealistic forecasts.

No

16. An ineffective means of communication and support of the entity's

values or ethical standards by management or the communication of

inappropriate values or ethical standards

No

17. Excessive pressure on management or operating personnel to meet

financial targets set up by the board of directors or management, including

sales or profitability incentive goals.

Yes

18. Management's personal guarantee of significant debts of the entity. Yes

19. Ineffective board of director or audit committee oversight over the

financial reporting process and internal control. Ineffective board of

director or audit committee oversight over the financial reporting process

and internal control.

No

20. Operating losses making the threat of bankruptcy, foreclosure, or

hostile takeover imminent.

No

21. Significant, unusual, or highly complex transactions, especially those

close to year end that pose difficult "substance over form" questions. Yes

22. Recurring negative cash flows from operations or an inability to

generate cash flows from operations while reporting earnings and earnings

growth.

No

23. Management failing to correct known reportable conditions on a timely

basis.

No

24. Marginal ability to meet debt repayment or other debt covenant

requirements. Yes

25. Unreasonable demands on the auditor such as unreasonable time

constraints regarding the completion of the audit or the issuance of the

auditor's reports.

No

26. High vulnerability to rapid changes, such as changes in technology,

product obsolescence, or interest rates. Yes

27. Domination of management by a single person or small group (in a

non-owner managed business) without compensating controls.

No

28. Recurring attempts by management to justify marginal or inappropriate

accounting on the basis of materiality.

No

29. Overly complex organizational structure involving unusual legal

entities or managerial lines of authority.

No

30. Significant declines in customer demand and increasing business

failures in either the industry or overall economy. Yes

31. Significant operations located or conducted across international borders

where differing business environments and cultures exist. Yes

32. High turnover rates or employment of ineffective accounting, internal

audit, or information technology staff.

No

33. Significant portions of management's compensation (e.g., bonuses,

stock options) being contingent upon achieving aggressive targets for stock

price, operating results, financial position, or cash flow.

Yes

34. Assets, liabilities, revenues, or expenses based on significant estimates

that involve subjective judgments or uncertainties that are difficult to Yes

52

corroborate.

35. New accounting, statutory, or regulatory requirements that threaten

financial stability or profitability.

No

36. Ineffective accounting and information systems including situations

involving reportable conditions.

No

37. Management has heavy concentration of personal net worth in the

entity.

No

38. Need to obtain additional debt or equity financing to stay competitive-

including financing of major research and development or capital

expenditures.

Yes

39. High turnover of senior management, counsel, or board members. No

40. Profitability or trend level expectations of investment analysts,

institutional investors, significant creditors, or other external parties

(particularly expectations that are unduly aggressive or unrealistic)

including expectations of these external parties created by management in,

for example, overly optimistic press releases or annual report messages.

No

Based on the provided information (case and completed fraud risk factors checklist) what is

the risk of material misstatement in the financial statements due to fraud?

Give your answer on a scale of 1 (low fraud risk) to 10 (high fraud risk). Mark one box

below.

□ □ □ □ □ □ □ □ □ □

Low 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. High

Part C: Information participant

Please enter your demographics in the following fields:

Age:

Gender (Male/Female):

Function:

Year(s) of experience as an auditor:

53

Appendix 2: Questionnaire Implemental mindset

The only difference with Appendix 1 is that in the implemental mindset Part A: Audit firm

rotation contains a different question, which you can see below.

Part A: Audit firm rotation

According to Dutch law, companies classified as Organisaties van Openbaar Belang (in

English: public-interest organisations) are obliged to switch auditors after a certain number of

years.

Due to this law on the mandatory rotation of audit firms a listed construction company named

TSH N.V. (Total Sustainable Homes N.V.) – classified as a public-interest organisation – has

to choose a new audit firm to carry out their statutory audit for next year.

TSH N.V. was founded in 1992 by two engineering students. In 2014, TSH N.V’s turnover

was 8.5 billion euro and net income 730 million euro. TSH N.V. is a leader in multiple

segments of the European construction industry including private homes, commercial

buildings and educational buildings. TSH N.V. has multiple offices throughout Europe and

operates globally in more than 37 countries. It currently employs 9,000 people that carry out

about 1,800 building contracts every year. TSH N.V.’s goal for the coming five years is

enhancing their position in current markets and entering new markets.

Imagine that you are working for a Big 4 audit firm as an auditor. Your Big 4 audit firm

considers writing a proposal to win the construction company.

As a consequence, you - as an auditor - are asked to list six steps you would take in your

attempt to win the construction company. Write the six steps in one or a few sentences in the

table below.

Steps:

1.

2.

3.

4.

54

5.

6.