The Board’s Influence On Operational Risk
Reporting
29 June 2015
P.J. Kuiper (S2557363) Rijksuniversiteit Groningen Faculteit Economie en Bedrijfskunde Master Accountancy and Controlling
Duisenberg Building
Jan Wiegerslaan 23, 9581 LR Musselkanaal Tel: +31 (0) 638596725
E-mail: p.j.kuiper.2@student.rug.nl
Abstract
To find out to what extent listed organizations in the Netherlands present information about the operational risks they are facing and the process of managing these risks an ORD-score is used. This research examines the relationship between characteristics of the Board of Directors and the degree of operational risk reporting. The tenure of board members and the gender of board members is supposed to have a positive influence on the degree of operational risk reporting in organizations. Unfortunately, the results of this research indicate that there is no relationship between the variables taken into account and the degree of operational risk reporting.
Content
1. Introduction ... 3 2. Theoretical framework ... 5 2.1 Board tenure ... 5 2.2 Board diversity ... 6 2.3 Big X auditor ... 7 3. Method section ... 9 3.1 Sampling procedure ... 9 3.2 Variables ... 9 3.3 Econometric model ... 12 4. Results ... 13 5. Discussion ... 16 5.1 Findings ... 16 5.2 Theoretical implications ... 16 5.3 Practical implications ... 175.4 Limitations and further research ... 17
6. Conclusion ... 18
1.
Introduction
“If you want to prevent fires, look for flammable substances. Don’t count fire extinguishers”1.
This statement tells us something about risk management and the importance of it. It is more important to identify the threats faced by the organization and the impact of these threats than rather put some controls in the system and hope you implemented the right controls. This statement tells us that it is crucial to look for the events that cause the threat and find ways to control these events, then only look for the solutions to control the threat.
According to Helbok & Wagner (2006) not assuring a proper risk management, might lead outsiders to overestimate the expected loss from and/or probability for the realization of an operational risk event and consequently result in investors demanding a higher return. Risk management is thus important to inform stakeholders about the risks faced by the organization and the way the organization handles these risks. In the perspective of the agency theory the connection between the organization and the stakeholders is seen as an agency relationship. Jensen & Meckling (1976) define an agency relationship as a contract under which one or more persons (the principal(s)) engage another (the agent) to perform some service on their behalf which involves delegating some decision making authority to the agent. The type of risk which is most emphasized by academics and scholars in the last decade besides strategic, financial and compliance risks is operational risk. The definition of operational risk being used in this study is from the Basel Committee of Banking Supervision (BCBS) and is defined as follows: “the
risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. This definition includes legal risk, but excludes strategic and reputational risk”. In its early
manifestations, operational risk was simply a residual category for ‘other risks’ not covered by market risk and credit risk (Power, 2005). But the times are changing and during the financial crisis in the last decade one of the major lessons is that financial institutions’ risk management and the disclosure of their on and off balance sheet risks must be improved (Vauhkonen, 2012). Nowadays the measurement and management of operational risks in financial institutions is ultimately mandated and supervised by the Basel Committee on Banking Supervision (BCBS). There are also other parties besides bank regulators which encourage improved risk management disclosure such as the accounting and corporate governance standard setters as well as rating agencies and auditors (Helbok & Wagner, 2006). That rules are important comes forward in the article of Brown, Goetzmann, Liang & Schwarz (2008) who stated that mandatory disclosure is an important regulatory tool intended to allow market participants to assess manager risks without unnecessarily constraining manager actions.
Within corporate governance the Board of directors plays an important role as a mechanism of control (Fama and Jensen, 1983). According to Wang & Hsu (2013) a board which is more effective in overseeing and advising senior management can help to reduce a firm’s chances of experiencing potentially damaging operational risk events because they can implement and maintain a better governance structure. Therefore, within the agency framework the board can be seen as an internal governance mechanism with the responsibility to mitigate agency problems between managers and shareholders (Carter, Simpson & Simkins, 2003; Wang & Hsu, 2013). This important role of the board in combination with the emerging role of operational risk management makes it an interesting subject for research. According to Ismail & Rahman (2011) an effective board of directors could provide a good monitoring
1 Viewed via: http://www.kmworld.com/Articles/Editorial/Features/Risk-management-Reputation-is-everything-102169.aspx on 9-3-2015.
function towards maximizing shareholders’ wealth in order to align the interest of the managers and the shareholders. In other words, the responsibility of the board to disclose operational risk in the annual report is in line with the interests of the shareholder.
Inside the board of directors there are various compositions which can be characterized. In this study we will focus on board tenure and the diversity of board members in the sense of the presence of male and female directors. Beside these two characteristics we also study the role of a Big X auditor and their influence on the quality of operational risk reporting. Based on the foregoing the following research question is formulated:
To what extent do board characteristics influence the quality of operational risk disclosure?
This study contributes to the existing literature by providing evidence about the quality of operational risk disclosure and the continuous changing of the risk appetite of companies during the past years. Despite the interest in financial institutions the sample in this research consists of more organizations in various sectors. The reason to take a broader sample is to facilitate this research. To my knowledge no study has yet investigated the quality of operational risk reporting and the role of board characteristics in listed companies in the Netherlands. To find out the impact of board characteristics in the Netherlands is interesting, because Magnan & Markarian (2011) found evidence that governance responses have been country specific. Other studies in the area of operational risk management and disclosure were focussed on listed companies in the UK (Linsley & Shrives, 2006), insurance companies (Gatzert & Kolb, 2013) and the financial sector (Helbok & Wagner, 2006; Vauhkonen, 2012; Wang & Hsu, 2013).
The remainder of this paper is as follows. In section two the theoretical framework will be highlighted and some detailed information about operational risk reporting and the characteristics of the board is provided. The third section comprises the method section where the research method used and the data collection are highlighted. In section four the results of this study will be presented and in section five these results are discussed. The last section comprises the conclusions of this study.
2.
Theoretical framework
The concept of operational risk is changing and it transforms internal control into risk management, with a focus on deeper ways of analysing and managing internally generated risks and external risks. (Power, 2004; Ciborra, 2006). Nowadays reporting on operational risks is mandatory in the financial sector and in the past years the importance of this type of reporting was also known due to the fact that Helbok & Wagner (2006) argued that reporting on operational risks is a tool for promoting transparency and market discipline. The recent financial crisis worked in my opinion as a stimulant in the process of change and further improvement of operational risk reporting.
In a lot of research throughout the past years board composition has been investigated and their impact on several aspects within companies. Several studies investigated aspects of the board such as board independence (Bhagat & Black, 2002; Chen, Dyball & Wright, 2009), outside directors (Beasley, 1996; Duchin, Matsusaka & Ozbas, 2011) and board size (Raheja, 2005; Kang, Cheng & Grey, 2007). Beside the characteristics mentioned before board gender is also widely discussed in the literature in relation to firms’ organizational structure, acquisition strategies and firm performance (Farrell & Hersch, 2005; Adams & Funk, 2012; Ahren & Dittmar, 2012; Levi, Li & Zhang, 2014). Despite this large literature, less attention has been paid to the effect of board gender, i.e. the presence of female directors in the board, and board tenure on the quality of operational risk reporting.
I propose that the fact that operational risk reporting is mandatory in financial institutions these days will stimulate other organizations in different sectors to keep up with these requirements in order to establish a high quality of risk reporting. To find out if it stimulates other organizations in different sectors, Dutch listed organizations are part of the sample as they represent different sectors. In the following subsections the theoretical foundation for this proposition and the development of the hypothesises is described to give a clear understanding of the existing literature and the way in which these hypothesis have come into being.
2.1 Board tenure
In corporate governance an important aspect of board composition to consider besides director’s knowledge, relevant expertise and availability, is length of tenure (Chen et al., 2009). Evidence shows that increased tenure of directors is associated with fewer misleading financial disclosures (Donoher, Reed & Storrud-Barnes, 2007). This suggests that more experienced directors are more driven in presenting financial statements and that they attach great value to the reliability of these financial disclosures. The link between board tenure and risk is mentioned by Bao, Fanshmidt, Nair & Vracheva (2014) who declare that tenure influences the level of risk that managers are willing to take. According to Kor (2006), managers with less tenure inside the organization may be more willing to take risks because they are compelled to produce results and prove themselves as competent managers. On the other hand, long-tenured managers have a more risk-averse approach because they feel less need to prove themselves.
To maintain a high quality of operational risk reporting, knowhow of the organization and the risks the organization is exposed to are important. Pfeffer & Salancik (1978) found that longer director tenure is to be regarded as a source of reputation and organizational knowledge, which can lead to the provision of better access to resources. In addition to this and a more recent finding comes from Chan, Liu & Sun (2013) who found that directors with a long tenure are more likely to acquire procedural knowledge as a result of their work experience and have higher monitoring effectiveness. This procedural knowledge
helps to better understand the processes and procedures in the organisation and increases the chance of recognizing risks in the organisation. Besides, the long tenured directors also have more opportunities to gain knowledge of the company’s internal control system and business operations over time, and establish working relationships with the management to acquire more useful information for their judgements on accounting issues. When reporting on operational risks, sufficient knowledge of the firm and industry is important to maintain a high quality of reporting due to the fact that without knowledge not all of the risks can be identified. Developping knowledge of a firms’ past commitment and unique resources and capabilities by directors can be assisted by a longer tenure (Kor & Sundaramurthy, 2009). Muller-Kahle & Lewellyn (2011) argue that boards with low tenure lack internal knowledge of firm and industry specific issues and thus, are not as effective in decision making compared to boards with greater tenure. Furthermore, they also state that boards with a low tenure may lack necessary skills and knowledge due to low levels of institutional memory. This indicates that directors with a longer tenure are more capable of assessing the relevant issues to consider and are able to recognise irrelevant issues and keep these out of consideration.
Hypothesis 1 (H1): There is a positive relationship between the board of directors’ tenure and the quality of operational risk reporting.
2.2 Board diversity
Board diversity in the sense of gender, racial, and cultural composition is seen as an important aspect of corporate governance. According to Carter et al. (2003) it is one of the most significant governance issues currently facing the manager, directors, and shareholders of the modern corporation. In his paper he also states that corporate diversity promotes a better understanding of the marketplace and that diversity increases creativity and innovation. Nowadays women accessing corporate boards are still the exception to the rule (Sheridan & Milgate, 2005). However there is also evidence that the number of women in boards is increasing, which could be due to the fact that boards respond to outside pressure to add women directors (Farrel & Hersch, 2005). In their paper they also state that the greater demand for diversity may be based on a firm having a higher public profile than other organizations. These firms with a public profile could attract negative attention when it becomes public that in the search of a new director only men can fulfil this function. This negative attention gives the organization a bad reputation which will probably lead to shareholders being concerned and a declining firm performance, whereas women in the board tend to have positive influence on firm performance (Carter et al., 2003).
There is also evidence that boards with more women were more likely to identify criteria for measuring strategy, monitor its implementation, follow conflict of interest guidelines, and adhere to an ethical code of conduct (Brown, Brown & Anastasopoulos, 2002). These competences that female directors bring with them suggest that the attention paid to proper risk reporting is more likely, and therefore the quality of risk reporting also increases. Furthermore, Brennan and McCafferty (1997) suggest two advantages of having women on board. First, women are not part of the “old boys” network, which allows them to be more independent. Second, they may have a better understanding of consumer behaviour, the needs of customers, and opportunities for companies in meeting those needs.
Adams & Ferreira (2009) found that the attendance records of female directors is better than the attendance of male directors and that a more gender-diverse board has fewer attendance problems. These results suggest that more attention is paid to monitoring, which in case could lead to a better risk management and a higher quality of operational risk reporting. The fact that female board members
are more risk averse (Croson & Gneezy, 2009) is also an indication that women pay more attention to risk management which leads to a higher quality of risk reporting. There is also counterevidence that women on the board need not necessarily lead to more risk-averse decision-making as female directors are slightly more risk-loving than male directors (Adams & Funk, 2012). I suggest that this could also lead to an increased quality of risk reporting due to the fact that the risks taken need to be accounted in the annual report.
Hypothesis 2 (H2): There is a positive relationship between the presence of female directors in the boards and the quality of operational risk reporting.
2.3 Big X auditor
To ensure a decent quality of risk reporting, organizations often choose an external auditor for an independent review of their reporting activities. A lot of these external auditors employed by organizations are Big X auditors. Big X is a collective noun for the following accounting firms: PwC, EY, KPMG and Deloitte. According to Owusu-Ansah & Ganguli (2010) the external audit function plays an important role in corporate governance by lending credibility to published financial statements. They argue that this is done by auditing the financial statements and providing reasonable assurance that they conform to the contractual relation between the investors and top management (which is a principal-agent relationship), and are free of material misstatement caused by errors and fraud. The presence of an external auditor has a positive influence on the quality of risk reporting. This is supported by Carson (2002) who suggests that auditor are highly interested in corporate governance-related issues of their clients because an improvement in governance could improve the quality of financial statements, and therefore, reduce litigation risk. Furthermore, Pridgen & Wang (2012) found that hospitals who employed Big X auditors were associated with better internal control quality. It is important for a Big X auditor to deliver high quality work due to the fact that their reputation is dependent from it. That reputation is an important facet is apparent from the fact that Big X auditors are more reticent in the sense that they do not want to be associated with organizations that do not work according “best practices” (Bryan-Low, 2003; Hindo & Sager, 2003). This suggests that Big X auditors have relatively more low-risk organizations as their clients (Contessotto & Moroney, 2014). Low-risk organizations mentioned before are the organizations that are less likely to discredit the Big X auditor with the risks they are exposed to, such as the consequences of illegal activities.
Based on the theoretical assumption explained above, the following hypothesis is developed:
Hypothesis 3 (H3): There is a positive relationship between the presence of a Big X auditor and the quality of operational risk reporting.
Due to the fact that Big X auditors deliver work of high quality it can be assumed that their work and services also stimulate the board to deliver high quality work, i.e. risk reporting, as well. This support in knowledge and expertise that a Big X auditor brings could help directors to do their job in a proper way. Furthermore, this could also avoid longer tenured directors from falling into routine behaviour and to keep them keen. This also entails the risk on “blind spots”, in other words: the risk that directors are not able to recognise risks timely because of their long tenure. Therefore I suggest that the presence of a Big X auditor strengthens the relationship between the board of directors tenure and the quality of operational risk reporting.
Based on this the following hypothesis is developed:
Hypothesis 4 (H4): The presence of a Big X auditor strengthens the relationship between board tenure and the quality of operational risk reporting.
Based on the research question, the theory discussed, and the hypothesis developed based on this theory a research model (figure 1) has been prepared. This model visualizes the relationships between the variables and indicates if there will be a positive or negative influence on the dependent variable.
3.
Method section
This section comprises the research method being used in this study. In the first paragraph the sampling procedure will be explained and a further explanation of the information being used during this study will be given. The measurement of the variables will be presented in the second paragraph of this section. The dependent and independent variables will be operationalized and also the control variables are discussed. In the last paragraph of this section the statistic model being used in this study will be explained.
3.1 Sampling procedure
In this research data is used from organizations that are listed in the Netherlands. All of the organizations in the sample are listed at the AEX, AMX or the AScX. Instead of using al the organizations that are listed at one of these three indexes only organizations who can be divided into the following sectors are taken into account: banking, insurance, technology and energy. The choice to select organizations in these sectors arises from the fact that these organizations are exposed to operational risks in a greater extent than for example organizations in the consumer services sector and that risk management in these sectors has been more developed due to external regulators and supervisors. The data is collected from the annual reports and websites of the organizations of the years 2007, 2010 and 2013. The choice to use these three years comes from the fact that 2007 and 2010 can be described as pre and post crisis years and 2013 as a year that show some measure that took more time to implement in the organization. These reasons could possibly affect that organizations do operational risk reporting. From the 69 Organizations selected 61 are part of the final sample used in this research. The difference between the sample and the final sample is due to the fact that from these eight organizations little or no information was available (e.g. some organizations did not mention risk management at all). The table below gives an overview of the four sectors and the number of organizations per sector that are part of the sample in this research.
Sector Sector number Number of organizations
Banking 1 15
Insurance 2 6
Technology 3 32
Energy 4 6
Total: 61
Table 1: Number of organizations per sector
3.2 Variables
In this paragraph the variables being used in this study will be operationalized. At first the dependent variable is defined and followed by the independent, moderating and control variables.
Dependent variable
In this study the dependent variable is operational risk reporting. To measure the quality of operational risk reporting it is necessary to find out to what extent an organisation reports on this type of risk. For measuring the quality of operational risk reporting an Operational Risk Disclosure-score, hereinafter referred to as ORD-score, is used. The use of an index is in my opinion a proper way of measuring the quality of risk reporting because a lot of aspects are taken into account. The use of an index instead of a single measure strengthens the reliability and validity of operational risk reporting in this paper. Instead of developing a new risk disclosure index the preference has gone to an existing model used by
other researchers which has proven its worth. The ORD-score that is applied in this research is also used by Hemrit & Ben Arab (2011) in their study on operational risk disclosures in Tunisian insurance companies. In their article, Hemrit & Ben Arab (2011) mention no restrictions for the applicability of this model in further research. The ORD-score consists of four subindexes that relate to operational risk. These four subindexes are: the definition of operational risk, the management of operational risks, regulatory issues and operational risk events. Each of these subindexes consists of several items and together they form the ORD-score. The four subindexes are briefly described below:
Definition of operational risk (OPRISKDEF): The items in this category are concerned with the definition
of operational risk given by the BCBS that is mentioned before (p.3) and covers the several types of risks suggested. The definition of BCBS covers the most important items of operational risk reporting and is therefore in this research applied to all sectors instead of only the financial institutions.
Management of operational Risks (OPRISKMGT): In this subindex the items that reflects the process of
managing the operational risks are captured, such as identification and measurement of risks.
Regulatory issues (REGISSUES): Reporting on operational risk is mandatory for companies in the financial
sector. In other sectors this mandatory reporting does not exist. The items in this category indicate the regulatory issues and gives an indication of the awareness of these regulations by organizations.
Operational risk events (OPRISKEVN): This subindex is included to comprise the operational risk events
categorized by the BCBS.
The four subindexes consists of seven items related to OPRISKDEF, nine items for OPRISKMGT, four items for REGISSUES and seven items related to OPRISKEVN. The total index contains 27 items as can be seen in table 1 below.
Subindexes Items
OPRISKDEF
Definition of operational risk
OPRISKMGT
The management of operational risks
REGISSUES
Regulatory issues
1. Direct/Indirect loss
2. Technology and system risk 3. Risk of human error
4. Legal risk
5. Catastrophes and crises 6. External events 7. Criminal actions 8. Risk management 9. Exposure 10. Identification 11. Measurement 12. Monitoring 13. Controlling 14. Database 15. Internal communication/reporting 16. Audit 17. Supervision 18. Solvency II/Basel III
19. Capital charge and provisions 20. Unexpected loss
OPRISKEVN
Operational risk events
21. Internal fraud 22. External fraud
23. Employment practices and workplace safety 24. Clients, products and business services 25. Damage to physical assets
26. Business disruption and system failures 27. Execution, delivery and management process Table 2: Disclosure index to measure the quality of operational risk reporting.
Following Helbok & Wagner (2006), as many other researchers in their favour for unweighted items, each of the 27 items have the same weight in the final ORD-score for the organisation. The reason for doing so is the difficulty of determining objectively the importance of each of the items within the subindexes. The presence of an item will be marked with a score of 1 and the absence of an item relates to a score of 0. Therefore, an organization can score a maximum ORD-score of 27 and a minimum score of 0.
Independent variables
The independent variables in this study are board tenure and board gender. Board tenure (TENURE) is measured as the average of the number of years each director served in the board of directors. To measure board gender (GENDER), the presence of female directors in the board is counted and divided by the number of total directors in the board. In doing so the variable board gender (GENDER) will be presented as a value between 0 and 1.
Moderating variable
The presence of a Big X auditor (BIG4) is the moderating variable in this study. The effect of the presence of a Big X auditor on the relation between board tenure and operational risk reporting is being measured. The presence of a Big X auditor is measured by searching in the annual report for the auditor who controlled the firm’s financial statements. When this auditor is one of the Big 4 auditors (PWC, EY, KPMG and Deloitte) than the variable will receive the value 1 and if the financial statements are controlled by any other auditor it is valued as 0.
Control variables
The control variables used in this study are commonly used in past studies in the area of governance and risk reporting. Following previous studies (Pathan & Faff, 2013; Barakat & Hussainey, 2013; Ntim, Lindop & Thomas, 2013), we included three control variables. The first control variable is firm size (TotAssets) measured as the natural logarithm of the total assets. The natural logarithm (ln) is used due to large differences in the size of organisations and doing so a more correct proportion is created. The second control variable is leverage (LEVERAGE). Leverage is measured as the percentage of total liabilities to total assets. The third control variable is the presence of an audit committee (SbAC) within the organisation. The variable SbAC is recorded in the dataset as a 1 or 0. A value of 1 indicates that there is an audit committee present in the organization, and a 0 indicates that there is no audit committee.
3.3 Econometric model
In this study we are using linear regression to measure the influence of the independent variables on the dependent variable Operational risk reporting. The regression model used in this study is as follows:
ICD-score = β0+ β1*Tenure+ β2*Gender+ β3*Big4+ β4*(Tenure*Big4)+ β5*TotAssets+ β6*Leverage+ β7*SbAC+
ε
iThe regression model displayed above consists of several parts. The first is the βi, these are the coefficients. The second is the
ε
i, which is the error term. The effect of the moderating variable is shown in this regression model with the product term β4*(Tenure*Big4). This product term iscalculated using the standardised values of the variables Tenure and Big4 and multiply these two with each other.
Variable Proxy Measure
Dependent variable:
ORD-Score Degree of operational risk reporting in the annual report of the organization.
Total score of the item
mentioned in paragraph 3.2. A high score indicates a higher degree of risk reporting Independent variables:
Explanatory variables:
TENURE Average time in the board. Years that directors serve the board.
GENDER Ratio between female directors and male directors
The number of female
directors present in the board.
BIG4 Presence of a Big 4 auditor. Control of the financial statements by a Big 4 auditor.
Control variables:
TotAssets Total assets Ln of the total assets of the organization
LEVERAGE Ratio between debt and total assets.
Total liabilities at the end of the financial year divided by the total assets at the end of the financial year.
SbAC Presence of an audit
committee.
The presence of an audit committee in the financial year Table 2: Measurement of the variables.
4.
Results
The hypothesis formulated in the previous paragraphs shows that a positive relationship is expected between the degree of operational risk reporting, the characteristics of the board (BrdTenure & BrdGen) and the presence of an accountant of the Big 4 (Big4). The control variables that are taken into account in this research are: TotAssets, Leverage and SbAc.
Table 3 below represents the descriptive statistics of the sample in this research. To reduce the influence of outliers in the data the technique of winsorizing is applied for the following variables: TotAssets, Leverage, BrdTenure and BrdGen. The values of these variables were required to meet the mean minus three times the standard deviation and the mean plus three times the standard deviation. When a variable exceeds the required value or was below the required value it is adjusted to the minimum or maximum value. To reduce the impact of skewed distribution the Natural Logarithm (LN) is used for the variable TotAssets as organizations in the financial sector have significant higher assets than for example the organizations in the technology sector.
Variable N Mean Standard deviation Minimum Maximum
Dependent variable ORD-score 61 13,850 4,979 5 27 Independent variables Explanatory variables Tenure 61 4,946 2,035 1 10,367 Gender 61 0,121 0,118 0 0,375 Big4 61 0,93 0,250 0 1 Control variables TotAssets (LN) 61 21,880 2,786 17,564 27,549 Leverage 61 0,588 0,232 0,224 0,970 SbAc 61 0,840 0,373 0 1
Table 3: Descriptive statistics
The mean and standard deviation of respectively 13,850 and 4,979 for the ORD-score indicates that almost all of the organisations that are part of the sample to a certain extent report about operational risks in their annual report. For most of the organizations operational risk reporting is not obligatory but based on these figures it can be said that they attach value to operational risk reporting. The members of the Board are on average five years (4,946) part of the board with a standard deviation of 2,035. In some organizations boards are together for more than 10 years where in other organizations they are only 2 years together as a board. So a lot of organizations have board members who are connected to the organization for multiple years. As mentioned in paragraph 2.1 a longer tenure of board members indicates sufficient knowledge about the firm and their internal processes. The mean and standard deviation for Gender are respectively 0,121 and 0,118. This indicates that women are in many organizations member of the Board but that they are still a minority compared with male board members. The mean of 0,93 and standard deviation of 0,250 shows that a lot of organizations hire an external auditor that is part of the Big 4 to check their financial statements. These figures indicate that a lot of organizations attach value to the hiring of an accounting firm from the Big 4.
Before the actual regression is executed to test the hypothesis a check on multicollinearity has to be done. This check shows if there is a relation between the independent variables themselves. If these
relationships are present multicollinearity exists and further measures have to be taken into account. The table below shows the findings of the multicollinearity test.
Variable ORD-score BrdTenure BrdGen Big4 TotAssets Leverage SbAc
ORD-score 1 BrdTenure -0,034 1 BrdGen 0,260* -0,198 1 Big4 0,341** 0,044 0,134 1 TotAssets 0.627** -0,051 0,293* 0,294* 1 Leverage 0,599** -0,080 0,254* 0,173 0,555* 1 SbAc 0,372** 0,75 -0,,45 0,419** 0,502** 0,238 1
* Correlation significant at the 0.05 level (2-tailed) ** Correlation significant at the 0.01 level (2-tailed)
Table 4: Correlations
Multicollinearity could be an issue when the correlation efficient is higher than 0,7 á 0,8. The results of the test on multicollinearity between the variables shows that there is no question of multicollinearity. Some of the variables are significant but none of the variables has a value that exceeds 0,7. A second and more precise measure of multicollinearity is called the Variance Inflation Factor (VIF). A value of +/- 10 indicates that multicollinearity is probably an issue. The results of this test show that none of VIF values is located close to 10. The VIF values found were all in the range between 1,020 and 1,973, so this test also shows that there is no question of multicollinearity.
Table 5 below presents the findings of the linear regression. The dependent variable in each model is the ORD-score. In the first model only the control variables were taken into account. In model 2, 3 and 4 the hypothesis based on the independent variables (BrdTenure, BrdGen and Big4) were tested. In the last model (5) the moderating variable was tested. By developing the hypothesis the choice for an unilateral connection was made. This means that in an one tail test for the detection of a significant correlation the p-values must be divided by two. The p-values represented in table 5 are the original undivided values.
In model 1 the control variables have been tested. The variables TotAssets and Leverage are significant which means that they have an influence on the degree of operational risk reporting. A significant correlation between the presence of an Audit committee and the degree of operational risk reporting is not found, so we cannot validate if the presence of an Audit committee has an influence on operational risk reporting within organizations.
The first hypothesis was tested in model 2 and was formulated as follows: There is a positive relationship
between the board of directors’ tenure and the quality of operational risk reporting. The results of the
linear regression show as expected a slight positive relationship (B=0,017). However, no significant relationship is found as p > 0,100 (p = 0,942). To find out of the influence of board characteristics on the degree of operational risk reporting is sector specific, tests by sector are also carried out but no significant relationship was found either. Based on this the hypothesis is rejected as it cannot be proven that the tenure of the board of directors is of influence on the degree of operational risk reporting. In model 3 the second hypothesis was tested and was formulated in paragraph 2.2 as follows: There is a
positive relationship between the presence of female directors in the boars and the quality of operational risk reporting. The second hypothesis is also rejected as no significant relationship has been proven (p
= 0,486). The value of B = 3,052 indicates just as in the hypothesis a positive relationship. The third hypothesis was formulated as follows: There is a positive relationship between the presence of a Big X
auditor and the quality of operational risk reporting and was tested in the fourth model. Based on the
results of this model the hypothesis can partially be accepted as the value of B = 3,094 and the p-value of 0,14 (0,07 when divided) indicates a significant relationship at the level of 10%. So based on these results we can conclude that the presence of an auditor of the Big 4 has a positive impact on the degree of operational risk reporting within organizations. The fact that almost all the organizations in the sample (56 of 61) are hiring an auditor of the Big 4 makes this finding not very reliable. The last model included the moderating variable. The hypothesis tested in this model was formulated as follows: The
presence of a Big X auditor strengthens the relationship between board tenure and the quality of operational risk reporting. Were a positive relationship was expected show the results that there is a
negative relationship (B = -0,400). As no significant relationship can be proven the fourth hypothesis is also rejected.
As can be seen in the table below each model contains also the Adjusted R-square and the F-value to add explanatory power to each model. Model 4 has the highest value of the adjusted R-square (0,476) which means that compared to the other models model 4 has a higher explanatory power. A high rate of explanatory power is also present based on the F-value. For each of the models a significance at the level of 1% is present.
Variable Model 1 Model 2 Model 3 Model 4 Model 5
ORD-score -6,478* (0,110) -6,580* (0,128) -5,948* (0,150) -8,113** (0,052) 13,870*** (0,000) TotAssets 0,667*** (0,005) 0,668*** (0,005) 0,622*** (0,012) 0,642*** (0,006) 1,822*** (0,000) Leverage 7,899*** (0,002) 7,909*** (0,002) 7,717*** (0,003) 7,781*** (0,002) 1,825*** (0,002) SbAc 1,296 (0,378) 1,284 (0,390) 1,537 (0,312) 0,541 (0,725) BrdTenure (H1) 0,017 (0,942) BrdGen (H2) 3,052 (0,486) Big4 (H3) 3,094* (0,140) Moderator (H4) BrdTenure*Big4 -0,400 (0,224) Adjusted R-Square 0,464 0,455 0,459 0,476 0,469 F-value 18,334*** (0,000) 13,512*** (0,000) 13,752*** (0,000) 14,610*** (0,000) 14,252*** (0,000) *** Significance of 1% ** Significance of 5% * Significance of 10%
5.
Discussion
In the first paragraph of this chapter the findings will be taken under discussion. The second and third paragraph mention the theoretical and practical implications of this research and in the last paragraph the limitations and recommendations for further research are taken into account.
5.1 Findings
The influence of board characteristics on the degree of operational risk reporting is studied in this research. The characteristics of which were assumed that they had an effect were board tenure and board gender as in the percentage of female directors.
As mentioned in the result section no significant relationship is found between the tenure of board members and the degree of operational risk reporting. The expectation was that board tenure had influence on operational risk reporting, as a more experienced board has gained more skills and knowledge about the firm. In their research Wang & Hsu (2013) found that tenure has a significant positive association with the likelihood of operational risk events when focused on event type. Based on these findings it is possible to say that board tenure has an influence on operational risk events, but not a direct influence on the degree of operational risk reporting within organizations.
With regard to the gender diversity within boards the expectation was that female directors pay more attention to risk reporting and therefore have a positive influence on the process of operational risk management within organizations. A significant relationship is not found between female directors and the degree of operational risk reporting. That women in boards have an influence on the performance of organizations is shown by Carter et al. (2003) who found that female directors and firm value are positively related. According to Adams & Funk (2012) female directors are slightly more risk-loving than male directors and they suggest that having women on the board need not lead to more risk-averse decision-making. This strengthen the result of this research of not finding a significant relationship between female directors and operational risk reporting. Based on these findings the presence of women in the board is still an interesting object of research.
An answer can yet be given on the research question developed for this research: “To what extent do
board characteristics influence the quality of operational risk disclosure?”. As expected, the board
characteristics have according to hypothesis 1 and 2 a slight positive influence on the degree of operational risk reporting but a significant relationship between these variables cannot be proven.
5.2 Theoretical implications
The purpose of this research was to make a contribution to the theory of risk reporting and the influence that corporate governance characteristics have. In the theoretical part of this research the importance of the Board as corporate governance mechanism within the Agency theory is discussed. Past research showed that board characteristics can be of influence on the degree of risk reporting. The assumption in this research was that the tenure of board members and the number of female directors within the board was influencing the degree of operational risk reporting. The results showed that this assumption cannot be proven. The theoretical implication of this specific research is that not all of the board characteristics are influencing the process of operational risk reporting within specific organizations.
5.3 Practical implications
The results of this research showed that evidence for a relationship between the tenure of members the Board and the presence of female members of the Board with the degree of operational risk reporting is not found. Based on this it is not possible to state that Board members who take place in the Board for a long period perform better in the area of operational risk reporting than members who take place in the Board for a short period. Based on the results of this research, the increasing pressure that companies face in hiring more female Board members instead of male members has no effect on the degree of operational risk reporting. Perhaps the increasing pressure on hiring female board members is on influence on operational risk reporting in the future.
5.4 Limitations and further research
The central aspect in this research was the influence of the board of directors on the degree of operational risk reporting within organizations that are listed in The Netherlands. The first limitation is the fact that only two characteristics were investigated. The decision to investigate only two characteristics was made due to the fact that choices had to be made in order to keep the amount of data in this research manageable and that more. The fact that this research was about organizations that are listed in the Netherlands can also been seen as a limitation. These two limitations are interesting topics for further research. Another limitation of this research is the fact that only four sectors were taken into account.
Besides tenure and gender it could also be interesting to look in further research for example at the age of Board members, the size of the Board, the number of independent directors and the compensation policy of the directors. Another interesting topic for further research is to take a broader sample. A sample that contains organizations from multiple countries can tell us probably more about the influence of the Board on operational risk reporting as cultural factors can be of influence.
6.
Conclusion
The purpose of this research was to find out if certain aspects of corporate governance influence the way in which organizations report on operational risks in their annual reports, as the board can be seen as the most important and powerful corporate governance mechanism in organizations. With the Agency theory as the theoretical basis the behavior of board tenure and board gender on the degree of operational risk reporting in organization is examined. Based on the theory four hypothesis were drawn up and tested with the use of linear regression. The results of the regression showed a significant relationship for the presence of a Big 4 auditor on the quality of operational risk reporting, but as mentioned before almost all of the organizations in the sample are hiring an auditor of the Big 4 which makes this finding not very reliable. No significant relationship was found for the other three tested hypothesis. The negative relationship found between the presence of a Big 4 auditor and the degree of operational risk reporting may be due to the specific sample of Dutch listed organizations. It can be concluded that board characteristics as tenure and gender therefore have no influence on the degree of operational risk reporting within organizations listed in the Netherlands.
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