What are the consequences of high leverage on the number and topic of the Key Audit Matters?

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University of Groningen

The influences of

leverage on the Key

Audit Matters in the

Audit Report.

What are the consequences of high leverage on the number and topic of the Key Audit Matters?

Mark van den Hof

6-29-2017

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Abstract:

This paper analyses the effect of leverage on the number and topic of the key audit matters in the audit report. Since the introduction of the extended auditors report, no research has been done on the influence of a company's financial structure on the key audit matters named by the auditor. This paper presents a first look at this. Results from 762 annual reports of 310 firms in 2 countries indicate that the number of key audit matters is significantly higher for firms with a high leverage ratio. On top of that, firms with a high leverage name more liabilities key audit matters and less asset key audit matters. These results are in line with the pressure to reduce the information asymmetry between manager and stakeholder.

Keywords: key audit matters; leverage; audit report; expectation gap.

Master thesis Accountancy (EBM869B20)

Groningen, June 2017

Name: Mark van den Hof

Studentnumber: 2374854

E-mail: m.van.den.hof.1@student.rug.nl

Adres: Paterswoldseweg 59A, 9727 BA Groningen

Telephone number: +31 6 29357396

Word count: 7203

Supervisor: Prof. Dr. D.A. de Waard RA

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1. Introduction

The auditor’s report is more extensive since 2013. The “old” audit report, which major purpose was to communicate the conclusion, was over 70 years old, yet served an important purpose (Christensen, Glover and Wolfe 2014). The opinion of de auditor was communicated through the annual audit report in which the auditor only approved the audit, with no further information (Brouwer, Eimers, and Langendijk 2016). There has been much criticism on the former audit report, mainly about its content and value to stakeholders (Carson, Fargher, Geiger, Lennox, Raghunandan, Willekens 2013; Cohen Commission 1978; Smieliauskas, Craig, and Amernic 2008; Geiger 1993; Mock, Bedard, Coram, Davis, Espahbodi and Warne 2013; Church, Davis and McCracken 2008). According to Doty (2013) both users and standard setters expected more from the audit report. Stakeholders wanted more insight about the view of the auditors on the appropriateness of the management estimates (FRC, 2015). In addition, auditors also saw the added value of the extended audit report in order to reduce the information gap (Dobjia, Cieslak and Iwuc 2013).

1.1 Key Audit Matters

In the past years almost all accountants from Public Interest Companies (PIEs) in the United Kingdom (UK) and the Netherlands (NL) switched over to the extended audit report. The NBA (October 2014) appointed six major changes to the new auditors report. First, the opinion of the audit at the beginning. Second, the auditors have to appoint the Key Audit Matters (KAMs) of the audit. Third, the topic of continuity has to be addressed. Fourth, auditors have to clarify the used materiality. Fifth, in case of a group audit, explanation on how the group audit is performed is needed. And lastly, the auditors have to pay attention to the readability of the audit report. The KAMs are points of discussion in the media. Are the key audit matters valuable information? Does naming the key matters satisfy the stakeholders need for information? Does the auditor describe how he/she has dealt with the essentials? All these questions can lead to intense discussions. In this research KAMs are further explored. There are differences in the amounts and themes of the KAMs in the audit reports. The average number of KAMs in auditors reports 2015 in The Netherlands was 4,2. All PIE’s in The Netherlands have between 2 and 6 KAMs. There was a bigger difference in the different themes from the KAMs. All kinds of different subjects can be seen in the KAMs, from account balance risks to internal control risks and from acquisition risks to fraud risks.

1.2 Stakeholders

The auditor makes the audit report for the intended users (ISA 701). After all, the stakeholders are the parties who actually should read the audit report. For the auditor it is crucial to communicate the results of the audit in the audit report (Coram, Mock, Turner and Gray 2011). Beside the shareholders, debtholders are an important stakeholder of PIEs.

There is a link placed by Bharath, Pasquariello and Wu (2009) and Gao and Zhu (2015) between a high level of leverage and information asymmetry. Gao and Zhu (2015) concluded that companies with a high degree of information asymmetry use more debt as financing. The new auditor's report provides an information effect between stakeholder and the firm according to Christensen et al. (2014).

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1.3 Relevance

This study attempts to establish a link between the leverage of a company and the KAMs in the auditor's report. Leverage is the ratio of book value of debt in relation to the book value of total assets (Danso and Adomako, 2014; Fosu, 2013; Opler and Titman, 1994).

The main question in this research is: Does the firm’s financial structure influence the KAMs in the Audit Report?

In this research I will elaborate on the extended audit report. How does the leverage influence the Key Audit Matters? This research will also check if a high leverage has an effect on certain topics of KAMs. For example, auditors at firms with a high leverage may appoint more liability KAMs than firms with a low leverage. There has been little research on the new auditor's report, and not a single study on the relationship between the financial structure of a company and the auditor's report. This study will give a first indication on this topic. If the new auditor's report is really informative and has the effect of reducing the information asymmetry, a connection will be distinguished.

Furthermore, in chapter 2 the theory used will be discussed. At the end of the Theoretical Framework two hypotheses will be formulated. After that, the research design is reported in chapter 3. In chapter 4 the results are reported and in chapter 5 the conclusion and discussion will be handled. Finally, in chapter 6, the references are named.

2. Theoretical Framework

In this chapter the Theoretical Framework will be discussed. Firstly, in section 2.1 a brief summary about the facts and figures is given, secondly in section 2.2 the expectations gap will be discussed, next in section 2.3 the information asymmetry is on the order. In section 2.4 the leverage is treated. At lastly, in section 2.5 the hypotheses will be formulated.

2.1 Facts

Dow (2014) discusses in his article the different aspects of the KAMs. Here he focuses on specific concerns raised by the proposed standard. The audit firms all compose the KAMs in their own way. The Financial Reporting Council (2016) analysed how many words the auditor’s organizations use in the auditor's report risk section. They analysed 350 English public listed companies. Deloitte uses an average of only 893 words to describe the KAMs, while PwC uses 1557 words. EY and KPMG both use around 1000 words for the KAM section. The Financial Reporting Council (FRC) also looked at the number of listed KAMs by the various audit firms. This showed that in the 2nd year almost all auditors’ organizations noted fewer KAMs than in the first year. The exception is Deloitte, they went from 4.0 KAMs in the first year to 4.1 KAMs in the second year.

2.2 Expectation gap

There is little published on this relatively new topic; the extended audit report. Although the topic appears frequently in the media and lectures, there are few scientific papers published on the subject. The extended auditor's report is launched from the idea to reduce the expectation gap between society and the auditor. This theory was introduced by Porter (1993) and then further investigated by many researchers. Litjens, Van Buuren and Vergoossen (2015)

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Page | 5 investigated the influence of information in the auditor's report on the audit expectation gap through an experiment. They set out a survey in which auditors, bankers and managers gave their opinion about the auditor’s expectations gap and how to reduce it. The conclusion of the research was that auditors try to minimize their risks, managers are reluctant to let the auditors publish sensitive information and bankers require additional information. Gold, Gronewold and Pott (2012) suggest in their research that the audit opinion alone may signal sufficient relevant information to users. They also find that explanations of the ISA 700 auditor’s report do not result in a smaller expectation gap.

2.3 Information asymmetry

The expectation gap cannot be separated from information asymmetry, of course, and thus the agency theory. The information asymmetry between principal and agent can be reduced by making private information public. Broye and Weill (2008) states that an audit generally helps to reduce the information asymmetry between debtholders and managers. By explaining the KAMs in the auditor’s report, it gives the principal (/debtholder) an additional insight into the company so that the principal obtains more information and this will result in a decrease in information asymmetry (Nwaobia, Luke, Theophilus 2016). Nwaobia et al. also concludes that the audit quality has improved by introducing the extended audit report. The problem of the information asymmetry from the principals’ perspective is well reflected in an article from Ross (1973), in which he clearly explains how the principal has to make decisions under uncertainty. In contrast, Boolaky and Quick (2016) found during an experiment no material impact of the KAM paragraph of the audit report on bank directors’ perspective. They argued that additional information might have a positive effect, but that the effect possibly is evened out because the reported facts in this case regarding risks were negative. Furthermore, in the case given, the client was a brewery so it doesn’t represent other industries.

After the insiders of a firm, auditors are the group of stakeholders with the most precise information about an enterprise (Varici, 2013). According to Varici, the auditor has the task to verify the information provided by the organization and to make sure the information is not misleading. Because of this, Varici states that “audit’s reports are of vital importance especially for the third parties because they allow reaching the exact information and enable disclosure of the information that must be revealed, but that has not been revealed yet” (p. 132).

2.4 Leverage

A company can be financed by creating equity, for example, by selling shares of a company. Another option is creating debt. These are interest-bearing loans, on which interest is paid annually. The interest paid on debt is generally lower than the cost of equity. The risk to debt holders, on the other hand, is also lower. They are given priority if a company is liquidated. Leverage is the ratio between debt and total assets. High leverage means that a company is financed with a larger portion of debt.

Many articles are written about a firm’s choice between equity and debt. The common conclusion of the literature is that firms that perform better, measured by profit, tend to use more equity and less debt. Donaldson’s (1961) “pecking order theory” describes how organizations make their financing decisions. According to this theory, managers of organizations would rather finance new investments with retained earnings than debt, resulting in lower leverage for high profitable organizations. Besides that, firms with high profits use these earnings to pay down debt which results in a lower leverage (Titman and Wessels 1988).

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Page | 6 Finally, stock prices rise if a firm becomes more profitable. Asquith and Mullins (1986) and Masulis and Korwar (1986) found that firms tend to issue equity when the stock prices increase, resulting in higher equity and thus lower leverage.

There are some pros and cons to attracting debt. Damodaran (1996) states that the interest rate on debts is deductible from the taxable income. In addition, high leverage results in interest rates rising and free cash flow for managers decreases in the company. This makes the managers more selective and accurate looking at investments. This helps discipline managers and thereby reduces agency costs (Jensen 1986).

There are also disadvantages to debt. High debt, and thus high leverage, increases the risk of financial distress (Parsons and Titman, 2008). Besides that, companies with high leverage face reduced flexibility in their financial position (Zingales, 1998). Flexibility is defined by Denis (2011) as the ability to respond to abrupt changes in cash flows or investment needs of the company. Finally, there is a danger that managers focus too much in the short term on cash flow because they have to meet interest payments (Peyer and Shivdasani, 2001). Malshe and Agarwal (2015) states that when firms take on more debt, they commit to pay a larger rate of the cash flow towards interest payments. Future cash inflows have an uncertain nature and the cash outflow of interest is very certain. This makes that Peyer and Shivdasani conclude that firms with higher leverage have an increased risk of bankruptcy.

If a loan is granted by a debtholder, the debtholder is faced with information asymmetry. The debtholder is not certain how the funds he granted are used by shareholders and mainly managers (Broye and Weill, 2008). In relation to the agency theory, Broye and Weill claim that agents may take actions that benefit themselves at the expense of creditors. The main risk in this is that managers make more risky investments than assumed by debtholders when the loan was granted (Galai and Masulis, 1976; Jensen and Meckling, 1976).

Debtholders would like the information asymmetry to decrease. The audit is one way of decreasing the information gap between debtholder and manager. In the KAM paragraph of the audit report, the auditor writes down the most important matters. The auditor writes the audit report for the intended users. Hereby, it is logical that the auditor writes down the topics which the users find most interesting. This research is exploring the influence of the leverage on the named KAMs. Particularly, I investigate if the leverage has influence on the number of liability and fraud risks in the audit report.

2.5 Hypotheses

This research aims to see whether the leverage influences the KAMs. High leverage may indicate a high information asymmetry. Bankers or other debtholders of firms with high leverage and high information asymmetry ask for more information from the auditor in the extended audit report. Besides that, high leverage firms have a higher risk to go bankrupt. To prevent that, stakeholders would like the firm to be transparent and the auditor to perform the audit with a high quality. It follows that:

Hypothesis 1: A high leverage is positively related to the number of Key Audit Matters in de audit report.

The KAMs named in the auditor's report may be different in nature. In this research I distinguish between ten topics of KAMs. From fraud to external topics, and from acquisitions to liabilities. For companies with a high leverage, debtholders are a more important stakeholder group than

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Page | 7 companies with a low leverage. A difference between debt holders and shareholders is that debtholders look more at the risks of a company, while shareholders look more at the opportunities of a company (Prowse, 1990). This research pays attention to the difference in topics of KAMs in relevance to the leverage ratio of firms. As stated above, debtholders encounter a level of information asymmetry towards the firm. Debtholders are especially interested in liability and fraud issues in the firm, relatively more than shareholders. This research argues that all others equal, a company with a high leverage should have more liability and fraud KAMs in the audit report.

Hypothesis 2: High leverage is positively related to the percentage of liability topics and fraud topics in the KAM section of the audit report.

3. Research Design

In this chapter the research design is being treated. In section 3.1 the sample and data is described. Next, in section 3.2 the variables will be discussed divided into the dependent, independent and control variables. Lastly, the research model will be discussed in section 3.3.

3.1 Sample and Data

This research tries to link the leverage of firms to the extended auditors report. I will look at the top 250 listed English firms in 2013, 2014 and 2015 and the top 75 Dutch firms over these three years. The Dutch representation in this study comes from the stock market funds of the AEX, AMX and AScX. For all these firms there is data collected from the annual reports from 2013, 2014 and 2015. The data collected comes from 327 companies for three years, so this increases the reliability of this research. For this dataset I selected the top 250 UK listed companies, based on their market value. These firms are all in the Financial Times Stock Exchange 100 Index (FTSE) or the FTSE 250. In total, the population is 981. Because two firms are on both the Dutch and the UK stock exchange, the top 75 and 250 becomes 76 and 251, respectively. The total population is 981 (76 + 76 + 76 + 251 + 251 + 251).

The entire population, however, is not completely suitable for this research. Not all auditors have made use of the option of bringing out an extended audit report and instead used the standard audit report. These annual reports are not relevant for this research and are therefore filtered out. In addition, there are also some other reasons why the final population becomes smaller. Reasons are because the firm is not yet Stock Exchange noted or the relevant variables are not present. From the 981 observations, 176 auditor’s reports didn’t report any KAMs. Of the remaining 805 observations, 43 had missing variables. This leaves the used dataset to be 762 observations. In the table following, the distribution between years and country is described.

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In total, the dataset consists of 762 annual reports from 310 different companies over the years 2013 to and including 2015.

The following is an explanation of the used variables of this research.

3.2 Variables

Two dependent variables and one independent variable are used in this study. The following is an explanation of these variables.

3.2.1 Dependent Variables

The amount of KAMs is one dependent variable in this study. This is measured by the amount of KAMs the auditor has recorded in his extended auditor’s report. Although it has been noticed that there is a lot of difference in the way of naming, this is not investigated further.

The amount of text which is used on the KAM paragraph in the extended auditor’s report runs far apart. In this research, however, the amount of KAMs is more important than the way in which the KAM is referred to by the auditor. Below is displayed, in Table 2, how often an x-number of KAMs are named.

Number of KAMs in de Audit Report Number of observations 1 KAM 23 2 KAMs 103 3 KAMs 185 4 KAMs 193 5 KAMs 143 6 KAMs 71 7 KAMs 30 8 KAMs 11 9 KAMs 3 Total: 762 Average KAMs 3,97 Table 2

Country – Year Number of firms Netherlands 2013 26 United Kingdom 2013 145 Netherlands 2014 60 United Kingdom 2014 234 Netherlands 2015 65 United Kingdom 2015 232 Total: 762 Table 1

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Page | 9 The second dependent variable in the research is the topic of the KAM. Not all the KAMs are about the same topic. Some KAMs are about the profit and loss statement, others about the balance. Some KAMs are about fraud, others about taxation issues. These are just examples of the wide range of different KAMs that auditor’s name in the extended auditors report. There are 10 major themes defined in which the KAMs are categorized. By hand the auditor reports are walked through to categorize in total 3022 KAMs. In Table 3 the categories are named, with the percentage of KAMs in the dataset.

These categories are valued by % of total KAMs per annual report. If, by example, an auditor’s report has 4 KAMs of which two are assets KAMs, one fraud KAM and one taxation KAM, the distribution is 50% assets, 25% fraud, 25% taxation and the other 7 categories are valued at 0%.

Category KAM % of total KAMs

Assets 34,86 % Liability 19,10 % Fraud 15,62 % Entity 09,53 % Acquisition 07,28 % Taxation 05,50 % Profit & Loss 04,44 % Valuation financial instruments 02,48 % External 00,66 % Other 00,53% Total: 100 % Table 3 3.2.2 Independent variables

The independent variable in this research is the firms’ leverage. Leverage is measured by a financial ratio. The equation used is Total Debt /Total Assets (Danso and Adomako, 2014; Fosu, 2013; Opler and Titman, 1994). The degree of leverage is strongly divergent. Some firms have less than 10% leverage (ratio of 0,10). Others, mainly financial services firms, have a ratio exceeding the 90%. There are even firms with negative equity, resulting in a leverage exceeding the 100%. To give an indication how leveraged the firms are, a distinction is made in Table 4 to categorize what ratio of leverage the firms have.

Ratio of Leverage Number of observations 0,00 – 0,20 57 0,20 – 0,40 124 0,40 – 0,60 227 0,60 – 0,80 204 0,80 – 1,00 139 < 1,00 11 Average: 57,83 % Table 4

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3.2.3 Control variables

The extended audit report is rather new, the introduction was in 2013. Because of this, the influences on why there is a difference in what the auditor writes down in the audit report is relatively uncertain. All the more reason to control the outcomes of this research for other variables. This research uses two main control variables: firm size and the auditor’s organization. Firm size is measured by the total assets, standardized to the Euro exchange rate at the first of January of the year after the audit. For the annual report of 2013, the exchange rate of 1-1-2014 is used to standardize the total assets. Because the total assets are very distinct, a logarithm of the total assets is made. Analyzing with a log of the total assets makes the outliners less influential, which increases the reliability of this research.

The auditor’s organization is categorized by firm. The Big-4 firms are mostly performing the audit of these firms, so this research uses 5 categories of Audit Organizations: Deloitte Touche Tohmatsu Limited (Deloitte), EY, PriceWaterhouseCoopers (PwC), KPMG and non-Big-4. To summarize these data, I refer to Table 5.

Accounting Firm Number of observations

Deloitte 174 EY 118 PwC 251 KPMG 206 Non Big-4 13 Total: 762 Table 5 3.3 Research Model

All these variables are put in the data software of SPSS. This research used the most up-to-date version available, which was version 24. The first step in data analysis is to understand what the data means. Firstly, the number of KAMs. This variable is one of the two dependent variables, the amount has is an integer number, there can’t be 3,5 KAMs named in the auditor’s report. This means that this variable falls under the category Interval. Secondly, the category of KAMs named in the auditor’s report. This is the second and last dependent variable. The category is expressed as a percentage of total KAMs per auditor’s report. This percentage is valued as a ratio, always between 0 and 1. Between 0 and 1, all kinds of ratios can occur, such as 0.25 or 0.175. Hereby, the variable is marked as Interval. Thirdly, the independent variable used is Leverage. Same as before, leverage is a ratio mostly between 0 and 1, except some firms have a leverage exceeding 1. Again, all ratio’s are possible. The leverage ratio can vary between 0,02 and 0,973 and between 0,142 and 1,15. Same as above, this variable is Interval.

Besides these two dependent and one independent variables, this research uses two control variables. First the firm size, standardized to euros. Also, this variable is interval. Finally, the audit firm as the last variable in this research. Because there is no qualification between one firm and the other, this variable is nominal. I distinguish five different auditors firms: Deloitte, EY, PwC, KPMG and non-big-4 auditors.

The goal of this research is to display a significant relationship between leverage and the number of KAMs on the one hand, and leverage and the category of KAMs on the other hand. Because all these variables are in the interval category, I perform several linear regressions.

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4. Results

In this chapter I will report the results of the analyzed data. In the methodology paragraph above, a couple of descriptive statistics are shown. The major topic in this research is the relationship between the degree of the leverage and the number of KAMs named by the auditor in the auditor’s report. In the figure on the right, the average leverage per number of KAMs is shown. Here is seen that the higher the leverage, the more KAMs are named by the auditor. Between every number of KAM there is an increase of leverage.

Next, in paragraph 4.1 a further

introduction in the results is given, by naming some more descriptive statistics, relevant for this research. In paragraph 4.2, hypothesis 1 is treated. To conclude, in paragraph 4.2 hypothesis 2 is treated.

4.1 Descriptive statistics

The data was distracted from annual reports of UK and NL firms between 2013 and 2015. Back in 2013, not all auditors published an extended auditor’s report. In this research, the total dataset is 762 observations large. The distribution between years is stated below.

Remarkable is that the difference between 2013 and 2014 is large, 123 observations more in 2014 than in 2013. The difference between 2014 and 2015 is only 3. Nowadays, in the UK and NL it is mandatory to publish an extended auditors report. This is quite logical based on the data on the left. Almost all auditors bring out an extended report, and the increase in voluntarily publishing the extended report stagnates. This makes that the timing to make the extended auditors report mandatory is logical. In total 762 annual reports, and thus auditor’s reports are used for this research. In these 762 extended auditor’s reports, 3022 KAMs are written down by the auditor. In figure 2 these 3022 are specified by category.

Year Number of observations 2013 171 2014 294 2015 297 Total 762 Table 6 0 0,2 0,4 0,6 0,8 1 1 2 3 4 5 6 7 8 9 R A TIO O F LE V ER A GE

NUMER OF KEY AUDIT MATTERS

Figure 1

Average Leverage

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Page | 12 Remarkable in these facts is the distribution between categories. Balance risks (assets + liability) are overrepresented in relation to the profit and loss statement risks, 1.631 over 134 respectively. Next to this, the fraud risks need to be stated. In every audit, fraud is a mandatory key matter, but 473 fraud matters are written down. Approximately 300 auditors didn’t write down a fraud KAM in their auditor’s report while it was a Key Matter in their audit.

4.2 Influence leverage on number of KAMs

At the beginning of this chapter, a figure was shown between the relation of leverage and number of KAMs. This indicates that there might be a relation between these two variables. To investigate whether the auditors firm is of influence on the number of KAMs, I performed a One-way ANOVA on Auditor and Number of KAMs. This One-way ANOVA was significant, F (4, 757) = 20,545, p < ,000. The auditor is of influence on the number of KAMs. To investigate if the other variables (Number of KAMs, Total Assets of a firm and the Leverage ratio) are related to one another, a bivariate correlation can be conducted. The results of this are shown in the table below.

#KAMs Total Assets Leverage

#KAMs Pearson Correlation 1 ,402*** ,306***

Sig. (2-tailed) ,000 ,000

Total Assets Pearson Correlation 1 ,410***

Sig. (2-tailed) ,000

Leverage Pearson Correlation 1

Sig. (2-tailed) Table 7

To analyze whether the leverage affects the amount of KAMs, I performed a linear regression of leverage on number of KAMs. This regression was significant R2=0,209, F (3,758) = 66,866, p = 0,000. The leverage has a positive influence on the number of KAMs, B = 1,033, p = 0,000

578 220 1053 288 20 134 166 15 473 75 0 200 400 600 800 1000 1200 N u mb e r o f to tal KA M Categories of KAM

Figure 2

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4.3 Influence leverage on topic of KAM

This research focuses on the topic liability and the topic fraud. Mainly, this is because previous literature on the effects of leverage on auditor’s decision making isn’t very extensive. Literature states that auditors might be more interested in liability and fraud risks if a firm is highly leveraged, and thus writes more KAMs about these topics.

The extended auditor’s report is relatively new, and not a single academic paper has linked the leverage of a firm to the extended auditor’s report. Because this research is so explorative, I have researched not only the liability and fraud KAMs, but all ten categories of KAMs. To investigate whether the auditor’s firm is of influence on the topic of the KAM, I performed a One-way ANOVA on auditor and the ten KAM topics. The results of this ANOVA are stated below.

Category of KAM F-value Sig.

Acquisition 0,888 ,471 Assets 11,695 ,000*** Entity 1,574 ,179 External 4,924 ,001*** Fraud 10,223 ,000*** Liability 5,883 ,000*** Other 2,203 ,067*

Profit and Loss statement 0,643 ,632

Taxation 3,072 ,016**

Valuation Financial Instruments 0,530 ,713

*, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively. Table 8

In this table is shown that the firm of the auditor is significant of influence in six topics, of which four are significant at 1% level. Liability and fraud are in the top-3 topics with the highest F-value’s, only the topic assets has a higher F-value.

To investigate if the other variables (topics of KAMs, total assets of a firm and the leverage ratio) are related to one another, a bivariate correlation can be conducted. The results of this are shown in the table 9.

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Category of KAM Total Assets Leverage

Acquisition Pearson Correlation -,044 -,011

Sig. (2-tailed) ,230 ,763

Assets Pearson Correlation -,165*** -,314***

Sig. (2-tailed) ,000 ,000

Entity Pearson Correlation ,054 ,074**

Sig. (2-tailed) ,134 ,041

External Pearson Correlation ,144*** ,019

Sig. (2-tailed) ,000 ,596

Fraud Pearson Correlation -,061* ,031

Sig. (2-tailed) ,093 ,400

Liability Pearson Correlation ,187*** ,281***

Sig. (2-tailed) ,000 ,000

Other Pearson Correlation -,002 -,029

Sig. (2-tailed) ,952 ,419

Profit and Loss statement Pearson Correlation -,101*** -,045

Sig. (2-tailed) ,005 ,217

Taxation Pearson Correlation ,020 -,021

Sig. (2-tailed) ,587 ,564

Valuation Financial Instruments

Pearson Correlation ,189*** ,138***

Sig. (2-tailed) ,000 ,000

*, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively. Table 9

There are four significant relations between the category of the KAM and the leverage. Interesting is that liabilities and leverage have a positive relation and assets and leverage have a negative relation. This indicates that the higher the leverage, the less assets related KAMs are named, but the more liability related KAMs are named.

To analyze whether the leverage affects the ratio of named liability KAMs, I performed a linear regression of leverage on ratio of liability KAMs. This regression was significant R2=0,102, F (3,759) = 28,646, p = 0,000. The leverage has a positive influence on the ratio of named liability KAMs, B = ,209, p = 0,000.

To analyze whether the leverage affects the ratio of named fraud KAMs, I performed a linear regression of leverage on ratio of fraud KAMs. This regression was not significant R2=0,010, F (3,759) = 2,556, p = 0,054. The leverage has no influence on the number of fraud KAMs, B = ,052, p = 0,092

As stated above, the leverage ratio has a significant relation towards: assets, entity, liability and valuation financial instruments. Besides that, this research goes further in depth in the fraud KAMs. Because of that, fraud will also be included into the next table. Here, I present the outcomes of different linear regression models.

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Table 10

Linear Regression Results

Variable (2) (3) (4) (5) (6) Liability ,209*** ,000 Fraud ,052* ,092 Assets -,298*** ,000

Valuation Financial Instruments ,026*

.063

Entity ,036

,117

R-square ,098 ,010 ,102 ,041 ,009

F-Value 28,646 ,2,556 28,648 10,670 2,308

Independent variable: Leverage. *, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively. As stated above, leverage has significant impact on different KAM topics. The obvious relations are between leverage and liabilities, and between leverage and assets. These are in all models significant at 1% significance level. Besides that, valuation financial instruments and fraud also are influenced by leverage in a significant way.

5. Conclusion and Discussion

In this chapter, I will conclude the research. First, I start with the conclusions of this research. Next, a brief discussion is placed over the conclusions. Lastly, some limitations and suggestions for further research will be handled.

5.1 Conclusion

In this study, I initiated the impact of a company's financing structure on the audit report. The auditor reports in the audit report which matters were most significant during the audit. When the leverage is high, other matters might sooner be significant. For this research I developed two hypotheses. First, I found that the higher the leverage, the more Key Audit Matters the auditor will write down. Next, I predicted that high leverage results in more Key Audit Matters with the topics liability and fraud. The results show a significant relation of 1% between leverage and liability topics, but not for fraud. Fraud actually is significant, but only at a 10% significance level. Besides that, leverage has a significant relation to two other Key Audit Matter topics. One of those two, valuation financial instruments, has a positive relation from leverage. Firms with high leverage tend to have more Key Audit Matters with this topic. A clear explanation for this phenomenon is difficult. Debtholders might put pressure towards the auditor to extra inspect the valuation of the financial instruments. Besides the positive relation, a negative significant relation has come from this research. Auditors of firms with high leverage, write down less asset related Key Audit Matters in the audit report. This is clearly explainable by the fact that debtholders are more likely to look at risks of firms. Shareholders tend to attach more value to opportunities of firms. Lower leverage ratios lead to more assets Key Audit Matters. Because assets are mostly meant to gain opportunities, it makes sense that shareholders are more interested in assets. Auditors of low leveraged firms are more likely to write down assets Key Audit Matters, because of the shareholder pressure.

5.2 Discussion

This research has a rather explorative character. This makes this research so interesting. Why do auditors write such different KAMs in their audit report? The results of this research show that leverage is partly the cause. Apparently, the auditor feels some pressure to adjust the audit

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Page | 16 report to the intended users. Debtholders are more interested in liability risks, and shareholders are more interested in asset risks. Auditors might be looking for ways to reduce the expectations gap between them and the stakeholders. If debtholders are a more important stakeholder, because the leverage ratio is high, auditors might publish an audit report which is more of interest by debtholders.

Another remarkable effect is the rise of the number of KAMs named in the audit report when the leverage is high. It seems that auditors find high leveraged firms more risky, and feel the need to disclose more audit information through the KAMs. It might feel as a safety precaution for the auditor. Firms with high leverage have a higher risk to go bankrupt. If the auditor names more specific KAMs on liabilities risks, it might feel that they warned the users of the Financial Statements that high leverage brings risks.

5.3 Limitations and suggestions

Explorative research always brings some limitations. Because earlier research can’t be consulted, it is hard to come up with testable hypotheses. In this case I chose to define a quite broad hypotheses and the quite narrow hypotheses. A major limitation in this research is the sample. Firms from the UK and the Netherlands are precursors in the field of the extended auditor’s report. This makes them interesting to research, but it is hard to generalize the results. Next, the industry in which the firm operates is not included in this research. As an example, many banks and other financial service firms have really large balance totals, and quite high leverage. This is not strange in these industries. I did not control for industry effects in this paper, but there might be a link between these factors. On top of that, there might be a problem with the deferred tax assets. When the deferred tax assets are significant, the possibility occurs that the auditor names that as a KAM. Moreover, in this research I only used one independent variable: leverage. Leverage is calculated by total assets divided by total debt. A suggestion for further research is to investigate other connections between financial structures. For example, the difference between short and long term debt.

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What are the consequences of high leverage on the number and topic of the Key Audit Matters?

The influences of

leverage on the Key

Audit Matters in the

Audit Report.

Mark van den Hof

6-29-2017

Abstract:

Table of Contents

1. Introduction

2. Theoretical Framework

3. Research Design

4. Results

Figure 1

Average Leverage

Figure 2

5. Conclusion and Discussion

6. References