Enterprise risk management and the (in) ability to anticipate and withstand the financial crisis

Enterprise risk management and the (in) ability to

anticipate and withstand the financial crisis

Master Thesis MSc Business Administration specialization

Organizational & Management Control

by

Robin van ‘t Veer

University of Groningen

Faculty of Economics and Business

First supervisor: drs. S. Sibum

Second supervisor: dr. W. Kaufmann

2

Abstract

This paper examines if firms that adopted Enterprise Risk Management (ERM) have better anticipated and withstand the financial crisis in comparison to firms that haven’t adopted ERM before the financial crisis of 2008, hereby investigating the effect of ERM on firm value. A sample of the S&P 500 from 2007 until 2011 is used. Overall it can be stated that firms that have adopted ERM have a lower (excess) stock return, lower return on assets / equity, lower growth opportunities and have more volatile earnings in comparison to firms that haven’t adopted ERM. Cash flow from operating activities is smoother from firms that have adopted ERM. In addition, a negative effect of the use of ERM on firm value is revealed.

Keywords

Enterprise risk management, firm value, financial crisis

When written in Chinese, the word "crisis" is composed of two characters. One represents danger and the other represents opportunity.

3 Table of Contents

Abstract ... 2

Introduction ... 4

Literature review ... 7

Traditional risk management ... 7

Enterprise risk management ... 9

The drawbacks of Enterprise Risk Management ... 11

The firm value creation of enterprise risk management ... 14

Research methodology ... 19

Sample collection and data source ... 19

Measurements of variables ... 21

Operationalization of the research ... 24

Exploratory data analysis ... 25

Results ... 28

Conclusion ... 31

Conclusion ... 31

Limitations and directions for future research ... 32

Reference ... 34

Appendix 1, Tillinghast-Tower Perrin (2001) model ... 37

Appendix 2, Examples of ERM and Non-ERM determination ... 37

Appendix 3, List of Non-ERM and ERM firms ... 38

4

Introduction

Initiative motive

This paper examines the effect of Enterprise Risk Management (ERM)¹ on firm value in the form of excess stock return in a global economic recession context. The financial crisis in 2008 has affected the global economy badly, causing an economic downturn lasting until today (Heng, Yu, and Li, 2011). The implementation of appropriate risk management by corporations in that respect already gained interest in the 1990’s, which supposedly should identify, analyze and manage significant risk exposure of the firm for the purpose of minimizing the negative (financial) risk exposure (Heng ea., 2011). Due to the continuation of the global recession and the collapse of numerous (financial) businesses in the past, one could wonder if these sophisticated risk management programs are effective enough in minimizing the significant negative exposure to firms. Over the last decade a new way of risk management called “Enterprise Risk Management” (ERM) gained substantial attention and has been adopted by numerous firms (Speklé and Paape, 2012). Its holistic approach towards risk management and the aggregation of risk creating a total portfolio of risk was advertised with substantial benefits over traditional risk management (TRM). Where TRM is generally seen as risk management in silo’s, where risks are seen individually and managed separately. The most important flaw of ERM, by looking at the aggregation of risks, is that the firm itself is lacking in controllability and manageability of certain risks (for example operational risk), as well as the lack of understanding of the interactions between those risks in the portfolio the firm created. These supposedly correlations between risks is one of the financial benefits of ERM. Here the revealing of these interactions would lead to so called natural hedges, which lowers the overall risk profile. However in practice, this new way of dealing with risks, has mainly produced a major economic downturn, with the fall of numerous large financial firms.

Simultaneously alongside the rise of ERM, leading up to the financial crisis in 2008 and in particular right after the financial crisis, governments proposed reform and implemented corporate governance rules in regards to risk management in reaction to previous and recent economic downturn (McShane, Nair and Rustambekov, 2011). Whereas the interest in ERM by top management is substantial, risk management supervision as a whole is at the agendas of governments (McShane ea., 2011) and numerous articles focusing on the benefits of ERM (Maurer, 2009; Nocco and Stulz, 2006; Beasley and Frigo, 2007; Bowling and Rieger, 2005; Hewitt, 2005), it is noteworthy that academic empirical research in this area has been scarce. More specifically, empirical researches focusing on firm value and ERM have been scarce, as well as empirical evidence on the relation between ERM and firm value.

5 Overview of extant literature

Academic empirical researchers in that respect have mainly focused on the financial sector, especially the insurance industry. For example: Hoyt and Liebenberg (2011) find positive significant results in the insurance industry of the US, using a maximum likelihood treatment effect model to jointly estimate the determinants of ERM and the relation between ERM and firm value. Pagach and Warr (2011) examining the effect of ERM adoption on firms long term performance in the financial and utility industry, however they find no significant effects of ERM implementation, except for the reduction of earnings volatility. Heng, Yu, and Li (2011) also focusing on the insurance industry in the US are one of the few that has a data sample covering the financial crisis. They find that well-designed ERM programs outperform the market and on the other hand, ineffective ERM programs perform under the market. McShane ea. (2011) are using the S&P rating for risk management as proxy for ERM effectiveness. By using this rating in combination with control variables (size, leverage, systematic risk, profitability, cash flow volatility, growth options and complexity) is determined if firms with a well-designed ERM program have higher firm value than firms with an ineffective ERM program. They use a small sample from the insurance industry in the US. However they find no significant difference in firm value, which is measured by the Tobin’s Q.

The inclusion of non-financial firms is clearly in the minority in empirical research. Examples of such research are: Beasley ea. (2008) examines the equity market reactions to announcements of appointments of senior executive risk officers. The appointment of an executive risk officer is seen as a sign of engagement of ERM and often used as proxy for ERM implementation (Hoyt and Liebenberg, 2011; Pagach and Warr, 2011; Gordon, Loeb, and Tseng, 2009; Beasley ea. 2008). They found no significance market response, indicating that general statements about value creation of ERM are not possible. Gordon, Loeb, and Tseng (2009) examine if the proper match between ERM and contingency variables increase firm performance. The contingency variables used are: environmental uncertainty, competition within industry, firm complexity, firm size and monitoring by board of directors. They are taken into account in non-financial firms and in addition, they use an Enterprise Risk Management Index determining the effectiveness of ERM, based on the firm’s ability on achieving its objectives in regards to strategy, operations, reporting and compliance. Gordon ea. (2009) find support that the proper match between ERM and contingency variables increases firm performance.

Contribution

6 inclusion of non-financial firms, I acknowledge the call from Heng, Yu, and Li (2011) for additional research focusing on ERM covering other industries than the insurance industry. This timeframe of economic downturn is a perfect practical test ground to investigate the effectiveness of risk management programs (McShane ea., 2011). By focusing on this timeframe, it is not only capturing the effects of the financial crisis, it also captures a more recent set of data of ERM. Where ERM is evolving throughout time and finds increasing amount of firms stating to have matured their ERM program (Beasley, Branson and Hancock, 2012), leading to increased effectiveness of ERM. This has been acknowledged by extant literature calling for researches covering more recent data (Heng, Yu, and Li, 2011; Hoyt and Liebenberg, 2011; McShane ea., 2011; Pagach and Warr, 2010). As final contribution, this paper uses excess stock return as proxy for firm value. This measurement has been used in the extant literature by Beasley ea. (2008) and Gordon ea. (2009) to look at the reaction of stocks in a pre and post announcement of the implementation of ERM; and the separation of high performing and low performing firms, respectively. Unlike previous research which uses excess stock return, this paper uses annual excess stock return as proxy for firm value covering multiple years.

Objective and research method

The objective of this paper is to examine if firms that adopted ERM have better anticipated and withstand the financial crisis in comparison to firms that didn’t adopt ERM before the financial crisis of 2008, hereby investigating the effect of Enterprise Risk Management on firm value. Via a random effect model this paper investigates the effect of ERM on firm value, as well as the effect of ERM on the determinants of firm value in the form of return, growth and consistency. The data I use is drawn from the S&P 500 over a period of 2007-2011.

Results

The result of our analysis show that firms that have adopted ERM have a lower (excess) stock return, lower return on assets / equity, lower growth opportunities and have more volatile earnings in comparison to firms that haven’t adopted ERM. Cash flow from operating activities is smoother from firms that have adopted ERM. In addition, a negative effect of the use of ERM on firm value is revealed.

Overview of the paper

7

Literature review

The first section sketches traditional risk management (TRM) and its value creation. The second section elaborates on the rise of enterprise risk management (ERM) and the definition of ERM. In the third section the drawbacks of ERM are revealed. The fourth section elaborates on the value creation of ERM, containing the hypothesis development of this paper.¹

Traditional risk management

When browsing through the extant literature on risk management, the term traditional risk management came to the front, along with the rise of literature on ERM. The TRM term in that respect seemed to be labeled by proponents of ERM, to refer to risk management before the rise of ERM and/or risk management practices without the characteristics of ERM. Indeed this categorization will be beneficial for the comparison of ERM with other risk management practices, and will be used for that purpose in this paper. However it must be noticed that this paper has no intent to minimize the importance of breaking through risk management practices in the past, by container labeling those risk management practice under one umbrella, namely traditional risk management. In addition, the aggregation of risk in a total portfolio is not a new phenomenon that was invented with the rise of ERM. Investors have applied this concept long before the rise of ERM, under the portfolio theory (Markowitz, 1952). Also conglomerates have reached out to this benefit via the use of diversification of their divisions globally and over different segments (Denis, Denis and Yost, 2002). In addition, studies in respect to cash holdings have supported the same ideal, namely the centralization of the cash holdings on a corporate level (Blijdenstein and Westerman, 2008).

The basic value creation of risk management lies within the imperfection of capital markets (McShane ea., 2011); where in perfect capital markets (Modigliani and Miller, 1958) the management of risk is irrelevant in terms of value. Under TRM, risk is seen as individual components, who are to be managed separately (Beasley ea., 2008), mainly for the purpose of the minimization of exposure towards downside risk. With this approach to risk management, different components of risk management is specialized in specific type of risks (Heng ea., 2012). Along with this specialization comes one of the prevailing classifications of risk types,

8 namely financial risk (in the form of market, credit, liquidity risk etc.) and operational risk. Here financial risk in general stands for the asset and liability risk and operational risk comprises business and event risks (Tillinghast-Towers Perrin, 2001). TRM implicitly tends to focus on downside financial risks, where the probability distribution of outcomes is easier to quantify and relative easier to manage. Whereas the image of risk are seen as independent hazards (Heng ea., 2012), and speculation on risk are considered not of the firm’s core value drivers. On the other hand are the operational risks, which are rather challenging to manage, since the frequency of occurrence and the vagueness of probability and inference are disrupting the accuracy of modeling (Mikes, 2009). Once the risk (either financial or operational) is measured it is up to management to decide to transfer, avoid, reduce or accept certain risks.

Examples of transferring risk are the use of insurance or outsourcing. The roots of insurance can be traced back to the early 1950’s, for risks related to natural disasters or accidents (Dickinson, 2001). Hoyt and Liebenberg (2011) highlight that corporate insurance is not only driven by offsetting independent hazards, but can be used as a policy to reduce asymmetric information, expected bankruptcy cost, firms tax payments and cost of regulatory scrutiny. Literature in that respect has found general support for their theoretical predictions in favor of the use of insurance (Hoyt and Liebenberg, 2011). A traditional example of reducing (financial) risks is the use of derivatives; where the value of derivatives derives from an underlying price or index (Jorion, 2010). Idem can the use of derivatives lead to additional benefits in regards to corporate governance. Extant literature in that respect mainly focused on reduction in expected cost via the use of derivatives, which is called hedging (McShane ea., 2011). In general extant literature is able to find justification for the firm’s decision to engage in the use of hedging, while a positive relation is found between hedging activity and firm value (Bartram, Brown and Conrad, 2011). Again, the use of derivatives focusing on the upside risk, better known as speculation are considered not of the firm’s core value drivers. A trend can be detected that the economical and statistical power of certain individual risk management activities, mainly in the form of hedging, in regards to firm value, finds values too small to account for, whereas perhaps the measurement on the overall risk management effect on corporate level find more results (Hoyt and Liebenberg, 2011). Examples of such insignificance can be found in studies that focus on exchange rate risk (Jong ea., 2006; Bartov and Bodnar, 1994; Jorion, 1990) and hedging activities in the oil and gas sector (Jin and Jorion, 2006). As final remark remains the operational hedging literature, which is rather limited and mainly restricted to the geographic and segment diversification of conglomerates (Denis ea., 2002).

9 Enterprise risk management

Starting from the mid-1990’s the environment of firms in regards to risk and the attitude of firms towards risk management simultaneously changed, giving the rise to enterprise risk management (ERM). Nowadays firms are continuously faced with fast changing business environments, more than ever prior to 1990. Adding to this is the recognition of an increased number and variety of risks the firm is facing, as well as the acknowledgement that these risks are interconnected with each other, which makes the management of risks more complicated, hence the traditional way of managing risks individually seems to be outdated (Gephart, Van Maanen, and Oberlechner, 2009; CAS, 2003). Alongside this development, the increased calculative power of information technology and the firms curiosity towards quantification of risk and risk modeling, made the management of risk in a holistic way even more tempting (CAS, 2003). In the past the financial institutions where the start of firms considering part of their risks to offset via insurance, and later on via the use of derivatives, it was again the financial institutions and government freedom who started change, when combining different transferable risk products into packages, giving firms the example of approaching multiple risks in a model, remaining with a single product/package of risk. Along this development arose the strategic management and contingency thinking of firms, encourages by shareholders. Here the need for long term planning as well as the inclusion of internal and external factors was essential for the shareholders wealth model, where this wealth model is based on the volatility of the future cash flows of the firm. In addition as one of the main causes of the rise of ERM are a number of high-profile firm failures, signaling the incompetence of risk management practices in place. This leading to increased scrutiny of corporate governance regulation in regards to internal risk control set by governments, as well as the necessity or voluntary change of the firms risk management policy (Beasley, Mark, Clune, and Hermanson, 2005; Dickinson, 2005).

Risk management was triggered to move beyond TRM and numerous firms have adopted a so called holistic approach towards risk management, named Enterprise Risk Management (Speklé and Paape, 2012). One could say that there are as many different definitions, as synonyms for ERM. However the most commonly referred to definitions of ERM are described by the Casualty Actuarial Society (CAS) Committee on Enterprise risk management (2003, p8) and the Committee of Sponsoring Organizations of the Treadway Commission (2004, p2). Starting with the definition of CAS:

“ERM is the discipline by which an organization in any industry assesses, controls, exploits, finances, and monitors risks from all sources for the purpose of increasing the organization’s short- and long-term value to its stakeholders.”

10 restricted to shareholders value creation. It considers all sources of risk, which emphasize that ERM is not limited to only financial risk or downside risk. In addition does CAS (2003, p8) state an implicit meaning in this definition; where ERM is recognized as a strategic decision support framework, where it improves decision making at all levels of the firm. COSO (2004, p2) on the other hand defines ERM in the following way:

“Enterprise risk management is a process, effected by an entity’s board of directors, management and other personnel, applied in strategy setting and across the enterprise, designed to identify potential events that may affect the entity, and manage risk to be within its risk appetite, to provide reasonable assurance regarding the achievement of entity objectives.”

Here a few additional fundamental aspects of ERM are displayed. First, ERM is seen as a process, unlike the project nature of TRM focusing on silos of probabilities and there associate outcomes, ERM is ongoing and flowing through the entire firm. Second, ERM is effected by every level of the firm, however it is noteworthy that ERM should be supported and directed from a top down approach. While the management of risks in such content covering the entire firm is rather challenging, a new senior executive role emerged. The chief risk officer (CRO), responsible for the co-ordination of risk management is of growing numbers to find on the executive board, simultaneously with the rise of ERM. Third, risk management is put into a strategic setting, emphasizing the long term importance of the firm. Fourth, ERM is related to the portfolio theory, highlighting that risk management is applied on every level of the firm, taken an entity-level portfolio view towards risk. Fifth, risk appetite is the level of risk the firm is willing to take and which risk should be mitigated or avoided (Pagach and Warr, 2010). Sixth, risk tolerance is the range or variance the firm is willing to take within its risk appetite. The reminder of the definition specifies that ERM is designed to identify potential events that, if occurred, will affect the firm and to manage risk within its risk appetite, as well as the reasonable assurance regarding the achievement of firm objectives (COSO, 2004).

11 The drawbacks of Enterprise Risk Management

Extant literature on the benefits or value creation of enterprise risk management (ERM) outnumbers the extant literature on the downside of ERM, which are rather scarce. Like most empirical papers on value creation of ERM a sketch is made from previous risk management practice in comparison with ERM, where expectations are formed in regards to value creation and these expectations are tested with success or failure to find significant relations (Heng ea., 2012; Hoyt and Liebenberg, 2011; McShane ea., 2011; Pagach and Warr; 2010; Gordon ea., 2009; Hoyt ea., 2008). The drawbacks of ERM is weighing the cons in financial aspect, keeping in mind insignificant or contradicting results in extant literature on the value creation of ERM. Operational risk, reporting and compliance

12 Danger of aggregation of risks

A potential drawback in ERM is the danger that lies within the aggregation of risks. Where ERM is no longer managing the root causes of risk, but directs itself at the residual risk that is calculated after the aggregation of risks (McShane ea., 2011). The management of risk can be characterized by being complex in today’s environment, where in coordinating and managing a portfolio of risk a danger can be found in the lack of understanding of; individual risks, the interconnectedness between different types of risks and risk embeddedness in a wider sense (Power, 2004). In addition, the aggregation of risks can be used to offload and re-individualize divisional risks towards enterprise level, which is tempting when a division has incentives of not bearing such risks. The aggregation of risks is often used for signaling towards shareholders that their overall risk profile is less risky. However the real differences could be just the reporting of risk to be changes described by previous paragraph (Power, 2004). This has two effects: First, the overall risk profile of the firm is considered less risky, whereas in reality the magnitude of this decrease in risk is likely to be lower (McShane ea., 2011). Second, the misinterpretation of the interconnectedness of risk and their embeddedness in a wider sense, miscalculates the real risk the firm is facing, which results in deviation of financial distress cost. Here the firm’s likelihood to get into financial distress might be decreased; however the actual impact when reaching financial distress is catastrophic. These two effects are following each other in a downwards spiral. Here more and more risks are aggregated, leading to stakeholders to consider that the firm is less risky, initiating incentives of the firm to increase risk taking, creating an increased underlying accumulated risk in the form of potential catastrophic financial distress (Power, 2009). This risk, behind the aggregation of risk is often forgotten and when taken into consideration, could substantially lower the value creation ability of ERM. This principal of diversifying away idiosyncratic risk¹ can be traced in the portfolio theory, often used by shareholders. The aggregation of risk, in the form of adding diversified stock into a portfolio by shareholders in that respect is cheaper than the aggregation of risk done on a firm level. Costly attempts to diversify this idiosyncratic risk away on the firm level is in line of this argument, value destroying (Beasley ea., 2008).

Disparity of risk preference

In previous paragraph the purpose of ERM described by CAS (2003) is to create value for all stakeholders. In addition, COSO (2004, p2) uses the phrase “manage risk to be within its risk

appetite” and “entity’s risk appetite”. Considering these two aspects with the enterprise-wide

view of ERM, it is assumed that the risk appetite can be generalized and formulated at the top management level and well distributed along the different risk management levels in the firm, for the purpose of value creation for all stakeholders.

14 The firm value creation of enterprise risk management

The basic argument opposing TRM and favor ERM is that the management of risk on a silo bases creates inefficiencies due to lack of coordination between risk management departments, leading to the failure to encounter the interconnectedness of different risk types. The coordination of risks gives a better overview and insight into the overall risk profile of a firm, enabling executive management to anticipate on risk more accurate and in an earlier stage, as well as the anticipation of risks that were unrevealed under TRM. This coordination is beneficial for internal decision making in a strategic setting. In addition the aggregation of risk and the knowledge of interconnectedness and correlation of risk, can avoid managing duplicated risks by exploiting natural hedges, which lowers the total cost of managing risk (Hoyt ea., 2008). The aggregation of risk can even be used to give an overview of the total risk profile, lowering the monitoring cost of management and the possibility to improve confidence of shareholders (Hoyt and Liebenberg, 2011; McShane ea., 2011; Pagach and Warr, 2010; Beasley ea., 2007; Nocco and Stulz, 2006; Bowling and Rieger, 2005; Meulbroek, 2002). The benefits of coordinating risk on an enterprise level and the aggregation of risks are key premises of the value creation of ERM. This value creation finds its background in different factors influencing the value of the firm. The model by Tillinghast-Tower Perrin (2001) is used to structure the underlying aspect that causes this value increase (appendix 1). The model postulated that value is increased via the appropriate allocation of capital supporting growth, return and consistency. The next sections elaborate on the benefits of ERM on the allocation of capital, followed by the elaboration of each pillar; enhancing growth, increasing returns and improving consistency. These pillars are subsequently used as building blocks to answer the following main hypothesis:

H1: The use of Enterprise Risk Management contributes to increased firm value

Appropriate allocation of capital

15 priorities and available capital, as well as better insight around the risk the firm is willing to take and improved transparency of the capital allocation choices of the firm (Lentino, 2012).

Increased return

With the coordination and aggregation of risk, increased operational costs and other drawbacks are involved; however the use of ERM comes with substantial (cost) benefits supporting the increased return of the firm, hence the effect of ERM adoption is ambiguous. The better insight in the overall risk profile, due to the coordination of risks might increase profits, while management is able to reduce avoidable losses in an early stage (Pagach and Warr, 2010). Where these losses could lead to catastrophic events in terms of bankruptcy and financial distress (Hoyt ea., 2008). However with absents of substantial “costly lower-tail outcomes”, the implementation of risk management, or even ERM is likely to be value destroying (Beasley ea., 2008). When looking at upside risk, the better insight in the overall risk profile can enhance proper selection of future projects in regards to return, where valuable projects are detected in an earlier stage, with more accurate and holistic information in regards to risk. Hereby, via the appropriate capital allocation, improvement in capital efficiency is created and hence increase return (Hoyt ea., 2008). Taken the perspective of the firm’s shareholders, the improved information about the overall risk profile of the firm is beneficial, lowering the information asymmetry between the firm and shareholders. This aspect is particular beneficial for opaque firms, where the understanding of risk is less transparent (Hoyt and Liebenberg, 2011; Meulbroek, 2002). The lower information asymmetry can be beneficial for the overall monitoring cost of the firm.

Magnifying the argument of increased long-term return of ERM are the continuous increased reporting and compliance regulations that started simultaneously with the rise of ERM. Firms in that respect are often required to update their risk management program, and are faced with the choice of either update their risk management policy alongside the regulatory change, or go the extra step and implement ERM. In real terms, therefore the additional implementation and/or operational cost of ERM with their benefits should be weighed against the additional cost already required to update the firms risk management program (Hewitt, 2005).

16 shareholders increased confidence of the firm’s ability to take increased risks at previous determined cost of capital. In both ways, via the lower cost of capital, or the firm’s ability to increase their risk profile and hence their overall returns at similar cost of capital, an increase in return can be detected (Pagach and Warr, 2011; PricewaterhouseCoopers, 2006; Bowling and Rieger, 2005). To investigate if the increased returns of ERM outweigh the additional operational cost and other drawbacks of ERM the following sub-hypothesis will be tested:

H1a: The use of Enterprise Risk Management contributes to increased return of the firm

Enhanced growth

By taking a closer look at the better insight of the firms overall risk profile, opportunities for enhanced growth can be detected. Before getting into detail, the coordination of risk is beneficial for the internal decision making in a strategic setting. For ERM to be efficient, the program needs to be linked with strategic management. Where ERM starts at executive level and it is crucial to set the right tone at the top, opportunities in regards to risk can be revealed when ownership of risks are taken in each level of firm (bottom-up approach). The proper strategic management and the enhanced growth of ERM go hand in hand, where ERM provides improved information in regards to risks, strategic management is intended to exploit this improvement for proper decision making to ensure enhanced growth (Ernst & Young, 2012).

Where TRM mainly focuses on mitigating the exposure to downside risks, ERM can be used to exploit upside risk. It is believed that ERM provides the overview of the firms overall risk profile, whereas future risks are accurately calculated while there calculations include their interconnectedness and embeddedness with current risks in place. In terms of growth, this calculation provides a more accurate risk-adjusted rate of return. Hence ERM is capable of more accurate net present value forecasting, enhancing the successful selection of future projects (Hoyt and Liebenberg, 2011). Via this overview of the firms overall risk profile and bottom-up approach focusing on business outlooks and capital needs, ERM is more capable of detecting upside risk opportunities. And via the appropriate allocation of capital the firm is capable of exploiting these upside risk opportunities (Lentino, 2012; Hoyt and Liebenberg, 2011; McShane ea., 2011; Pagach and Warr, 2010).

17 towards downside risks and greater exposure towards risks the firm is willing to take, the firm’s probability and extent of future projects having positive NPV’s is greater, hence the firm experiences enhanced growth.

In line with this approach is one of the main reasons of firms engaging in risk management by Nocco and Stulz (2006), namely the guarding against the underinvestment problem. Here risk management goes beyond the reduction of exposure towards downside risks for cost purposes and is able to manage certain risk before causing significant large cash shortfalls, ultimately resulting in value destroying cutbacks in investments (Nocco and Stulz, 2006). With the guarantee of certain cash levels, the firm is able to properly allocate its capital and ensures its future investments to enhance growth of the firm. In addition to these arguments of enhanced growth is the contribution of increased return with the main aspect being the lower cost of capital. These are both magnifying the enhanced growth opportunities of the firm. However, like ERM and return, the effect of ERM on growth is ambiguous. With the greater emphasis on all risk the firm is facing, the lack of understanding in regards to risks, the firm might overuse risk management which leads to the mitigating of upside risks, hereby restraining the firm from growth (Pagach and Warr, 2010). To investigate if ERM provides the firm with enhanced growth opportunities in comparison to firms that haven’t implemented ERM the following sub-hypothesis will be tested:

H1b: The use of Enterprise Risk Management contributes to enhanced growth of the firm

Improved consistency

18 resulting in the lower reliability on external (short-term) financing, which in general is more expensive (Allayannis ea., 2005).¹ By looking at earnings volatility, ERM may decrease the probability of lower-tail earnings outcome, where in an earnings-smoothing model; shareholders value firms higher with lower earnings volatility, leading to increased firm value especially for shareholders trading for liquidity reasons (Beasley ea., 2008). Leading to the sub-hypothesis:

H1c: The use of Enterprise Risk Management contributes to improved consistency of the firm

Figure 1. Conceptual model

¹) Both cash flow and earnings volatility are sensitive to management manipulation, which makes accounting measures of consistency ambiguous to interpret in regards to firm value. This paper doesn’t take into consideration the effect of smoothening of either cash flows or earnings and purely follows the reasoning mentioned in the hypothesis development. For literature on cash flow smoothing I like to refer to Scordis (2008).

19

Research methodology

Sample collection and data source

To investigate the effect of Enterprise Risk Management (ERM) on firm value during the financial crisis, panel data is collected from the S&P500 over the period 2002-2011. The data collection from this index is only US based and prevents the research from regulatory differences (Liebenberg and Hoyt, 2011). The S&P500 is chosen since this index is from a common law background, where the main focus of firms is to increase firm value. Here the financial impact from a shareholder prospective of the implementation of ERM is most likely to be found. The aim of this study is to look at effect of ERM on the anticipation and withstanding of the financial crisis, therefore the analysis will be performed on a timeframe of 2007-2011.

20 final sample consists of 478 firms; covering annual data collected over 5 years, resulting in 2390 data points (see appendix 3 for full list of firms). When taken the sample that have adopted Enterprise Risk Management, a total of 39.6% have adopted ERM, which is roughly in line with recent survey claiming 45.6% of public companies have adopted ERM (Beasley, Branson and Hancock, 2012). As a final note on the data sample, I follow the sector categorization of the Standard & Poor rating agency. S&P rating agency defines the following sectors: Consumer Discretionary, Consumer Staples, Health Care, Industrials, Information Technology, Materials, Telecommunications Services, Energy, Utilities and Financials. All other variables beside ERM activity are collected from DataStream.

Figure 2. Data Sample

0 10 20 30 40 50 60 70 80 90 Consumer Discretionary Consumer Staples Health Care Industrials Information Technology Materials Telecommunications Services Energy Utilities Financials 61 24 42 38 48 24 7 31 11 21 18 16 6 23 19 5 1 9 19 55 2 1 4 0 3 1 0 4 2 5

21 Measurements of variables

Dependent variable

To capture the value of the firm an annual excess stock return (1YESR) is taken as proxy, hereby measuring the portion of firm’s stock return exceeding the benchmark of the S&P 500 index. This is a leading indicator, measuring the future expectations of investors of a particular firm. Excess stock return is used in the study of Gordon ea. (2009), who favors this measure because its risk adjusted and leading indicator characteristics. The 1YESR is calculated in the following way: The percentage change between year t-1 and t are calculated, for the S&P 500 index and the firm’s stock, separately. Thereafter the difference is taken between the firm’s stock return and the S&P 500 index return, hereby deriving at an annual excess stock return. Alternatively, I will use the firm’s stock return as dependent variable for robustness check which is in line with Gordon ea. (2009).

Independent variables

22 Control variables

In line with prior studies regarding the benefits of ERM I have selected relevant control variables. The following control variables will be used in this research: firms size (SIZE), opacity (OPACITY), cash ratio (CASH) and leverage (LEVERAGE). Firm size is commonly used in accounting studies (Gordon ea., 2009) and it is believed that the size of the firm correlates with the complexity of the firm. With this increased complexity of the firm, the firm is facing more uncertainties, whereas the financial benefit of managing these uncertainties properly in a more complex firm is more beneficial. In addition the size of the firm can utilize its economies of scale, as well as to provide the resources needed to support an ERM program. The firm’s size is calculated by taking the natural logarithm of the total assets of the firm. By following the reasoning of Beasley ea. (2008) the predictive sign of SIZE is negative. In line with firm size and the increased complexity, firms that are more opaque are harder for outsiders (shareholders) to evaluate. Therefore the benefits of ERM, with the increased transparency of the risk the firm is facing, is more present in opaque firms. In line with Pagach and Warr (2011) opacity is included in this research. If the firm has sufficient and relatively easy and cheap excess to cash and short term investments, the firm is less likely to be in financial distress. ERM might aim for the same purposes of reducing the probability of financial distress. This research only focuses on risk management, whereas cash holdings are considered an effective method, for this matter will be controlled, to remain with the effect of the ERM program. In line with Beasley ea. (2008) I am using a cash ratio, which is calculated by dividing cash and short term investments to liabilities. The cash ratio is often used to look at the creditworthiness of a firm. By looking at leverage one could take two opposing idea’s in regards to risk management. Due to the implementation of ERM, the overall risk profile of the firm is lowered; hence the firm is able to increase leverage, which in general is considered cheaper than issuing equity. However ERM might look at the leverage the firm is holding as to risky, in their probability of financial distress that it’s initiate to lower the leverage of the firm. In sum the lower the leverage, the lower the probability of financial distress. The level of leverage is calculated by dividing total liabilities by total assets. Dummy variables

23

Table 1. Variable definitions

Variable Definition Exp.

sign DataStream code

1YESR Annual excess stock return RI

RETURN Annual firm stock return RI

ERM Dummy variable (0= non-ERM, 1= ERM adoption) + LEXIS-NEXIS, Factiva & Boardex

ROA Return on Assets = Net income / total assets + WC01706/ WC02999

ROE Return on Equity = Net income / total equity + WC08301

MB Market to book value = market value / book value

of equity + MVC / WC05491

CFV Cash flow volatility = standard deviation of the annual free cash flow over a period of 5 years, standardized by the average annual free cash flow

- WC04860, WC04870 & WC04890

CFVOP Cash flow volatility from operating activities = standard deviation of the annual cash flow from operating activities over a period of 5 years, standardized by the average annual cash flow from operating activities

- WC04890

EPSV Earnings per share volatility = standard deviation

over the earnings per share over a 5 year period - WC05201

SIZE Natural logarithm of the total assets - WC02999

Opacity Intangible assets / total assets +/- WC02649 / WC02999

CASH Cash ratio = Cash and short-term investments /

total liabilities + WC02001 / WC03351

LEVERAGE Total liabilities / Total assets +/- WC03351/ WC02999

FIN_Dumm

y Financial sector dummy variable

+

CRISIS_Dum

24 Operationalization of the research

The analysis of this research starts with exploratory data analysis, where basic assumptions in regards to parametric test are evaluated. Falling under this subject is the reduction of outliers, random effects and heteroscedasticity, descriptive statistics in the form of independent sample t-test and check for multicollinearity. Furthermore contains the main analysis out of a random effect model. This model is preferred over a fixed effect model since this paper investigates the effects of stable covariates in the form of ERM and Non-ERM firms, non-financial and financial firms, as well as pre-and current financial crisis. In addition it shows this model improved explanatory power over a pooled ordinary least square model. In total four analyses are computed. First and second will be the random effect model with the financial and crisis dummy, respectively. As the third and fourth analysis, the random effect model will be computed with the alternative measures, namely annual firm’s stock return, ROE and Market-to-Book ratio, for robustness check.

Each analysis contains out of three models. The first model contains out of the dependent variable, independent variables, control and dummy variables. Subsequently and individually are interaction effects added to the model, this to reveal the effects of ERM use, resulting in the second model. By computing an interaction variable, which is computed by multiplying, for example the ROA and ERM measure, the effect of ERM on ROA is measured influencing the dependent variable. The third model consists out of the dependent variable, independent variables, all interaction variables, control and dummy variables. The equation of the main analysis is as followed:

𝐹𝑖𝑟𝑚 𝑣𝑎𝑙𝑢𝑒 = 𝛼 + 𝛽1𝐸𝑅𝑀𝑖 + 𝛽2𝑅𝑂𝐴𝑖𝑡+ 𝛽3𝑆𝐺𝑖𝑡+ 𝛽4𝐶𝐹𝑉𝑂𝑃𝑖𝑡+ 𝛽5𝐸𝑃𝑆𝑉𝑖𝑡

+ 𝛽6(𝐼𝑁𝑇𝐸𝑅𝐴𝐶𝑇𝐼𝑂𝑁_𝑅𝑂𝐴𝑖𝑡) + 𝛽7(𝐼𝑁𝑇𝐸𝑅𝐴𝐶𝑇𝐼𝑂𝑁_𝑆𝐺𝑖𝑡)

+ 𝛽8(𝐼𝑁𝑇𝐸𝑅𝐴𝐶𝑇𝐼𝑂𝑁_ 𝐶𝐹𝑉𝑂𝑃𝑖𝑡) + 𝛽9(𝐼𝑁𝑇𝐸𝑅𝐴𝐶𝑇𝐼𝑂𝑁_𝐸𝑃𝑆𝑉𝑖𝑡)

+ 𝛽10𝐶𝑂𝑁𝑇𝑅𝑂𝐿𝑖𝑡+ 𝛿1𝐷𝑖+ (𝑢𝑖𝑡 + 𝑣𝑖𝑡)

Note; _i = 1,2 …, N, _t= YEAR, δ1= dummy coefficient, Di = Dummy, CONTROL = vector of variables consisting of

25 Exploratory data analysis

Reduction of extreme outliers, random effects and Heteroscedasticity

To reduce the influence of extreme outliers, the data collected has been adjusted via the Winsorization method. The extreme outliers of the data set of all quantitative variables (larger than the mean + 3 * standard deviation, or smaller than the mean -3 * standard deviation) are replaced, by plus or minus three standard deviations distance from the mean, respectively. A Hausman test is performed to conclude if the use of random effect model is preferred over a fixed effect model, as well as to investigate if the individual effects are not correlated with any other regressor (basic assumption for computing a random effect model). The Hausman test shows insignificance, concluding that the random effect model is the preferred method. In both the main analysis and the robustness check analysis heteroscedasticity is percent. Therefore a robustness adjustment of the standard errors is added to the model, here to control for heteroscedasticity.

Descriptive statistics

26 therefore firms that implemented ERM, could just have lower intangible assets. The ERM sample shows statistical and economical significant higher leverage, indicating that firms that have adopted ERM have a higher debt ratio.

Table 2. Descriptive statistics

N Mean SD t-value Mean

Difference 1YESR Non-ERM 1508 0,07 0,26 5,45 0,06*** ERM 850 0,01 0,25 RETURN Non-ERM 1475 0,14 0,37 5,09 0,08*** ERM 845 0,06 0,34 ROA Non-ERM 1535 0,07 0,07 8,92 0,02*** ERM 853 0,05 0,06 ROE Non-ERM 1525 0,17 0,18 2,86 0,02*** ERM 855 0,15 0,18 SG Non-ERM 1523 0,09 0,20 6,72 0,05*** ERM 852 0,04 0,17 MB Non-ERM 1530 3,50 3,54 4,65 0,71*** ERM 855 2,79 3,69 CFV Non-ERM 1474 1,05 1,17 -0,68 -0,04 ERM 796 1,09 1,20 CFVOP Non-ERM 1502 0,38 0,31 2,45 0,03** ERM 843 0,35 0,28 EPSV Non-ERM 1493 1,14 1,20 -3,87 -0,22*** ERM 832 1,36 1,34 SIZE Non-ERM 1524 15,89 1,02 -27,09 -1,48*** ERM 854 17,37 1,40 OPACITY Non-ERM 1365 0,26 0,20 7,41 0,07*** ERM 794 0,19 0,20 CASH Non-ERM 1533 0,36 0,41 10,12 0,16*** ERM 666 0,20 0,29 LEVERAGE Non-ERM 1522 0,54 0,20 -17,96 -0,15*** ERM 853 0,70 0,20

Notes: *, ** and *** correspond to 10%, 5% and 1% significance level. The sample is taken from the S&P 500, where ERM activity is separated in three samples representing the period 2007-2011. The Non-ERM sample doesn’t show ERM activity before July 2012, the ERM sample does show ERM activity before 2008 and the sample that showed for the first time ERM activity between 2008 and July 2012 are excluded from the analysis, leaving a total sample size of 478 firms.

Multicollinearity

27 coefficient indicates no perfect correlation, which makes the use of firm’s stock return a valuable alternative measure for excess stock return. Idem counts for the correlation between ROA and ROE. In line with the independent sample t-test is ERM negatively related to (excess) stock return of the firm. Both ROA and ROE are positively related to the dependent variables. Idem counts for the growth measures SG and MB. Noteworthy is the positive insignificant relation between the dependent variables and cash flow volatility from operating activities. This suggests that volatile cash flows from operating activities contribute to increase firm value. However the insignificance hinders accurate statements in that respect. Idem counts for the insignificant relation between earnings per share volatility and the dependent variables; however the direction is as expected negatively related. The control variable OPACITY shows insignificant relation with the dependent variables. In line with expectations is SIZE and LEVERAGE negatively related to the dependent variables and CASH is positively related to the dependent variables. OPACITY shows insignificant relation to excess stock return and stock return. Overall it is remarkable that the presence of ERM is negatively related with the dependent variables and the insignificant relation between the consistency variables and excess stock return. To test for multicollinearity I have taking the cut-off point -0.7 > X > 0.7 (X= Pearson correlation coefficient) in determine that variables are highly correlated and will cause a problem in further analyses.

Table 3. Pearson correlation coefficients (N=2101)

1YESR RETUR

N ERM ROA ROE SG MB CFVOP EPSV SIZE OPACITY CASH RETUR N ,805 ** ₁ ERM -,112** -,103** 1 ROA ,225** ,254** -,172** 1 ROE ,185** ,206** -,059** ,654** 1 SG ,248** ,394** -,131** ,260** ,152** 1 MB ,142** ,162** -,095** ,237** ,396** ,121** 1 CFVOP ,004 ,001 -,049* -,007 -,011 ,072** ,035 1 EPSV -,037 -,030 ,083** -,261** -,259** -,068** -,129** ,038 1 SIZE -,149** -,123** ,518** -,353** -,148** -,118** -,200** -,050* ,221** 1 OPACI TY ,016 ,003 -,158 ** _{,009 ,011 ,076}** _{,006 -,031 -,137}** _-,167** ₁ CASH ,106** _,098** _-,203** _,304** _,049* _,299** _,064** _{,035 -,045}* _-,259** _{-,022 1} LEVER AGE -,077 ** _-,078** _,346** _-,330** _{,017 -,189}** _-,080** _{,003 ,060}** _,416** _-,183** _-,511**

28

Results

Table 4 and 5 represents the outcomes of the main analysis computed over the total sample of the S&P 500, covering a timeframe of 2007-2011, with as dependent variable the annual excess stock return. Table 4 a financial sector dummy is used, whereas in table 5 a pre-and current crisis dummy is used. The statistical outcomes in regard to ERM implementation show significant deviations from extant literatures expectations. In the exploratory data analysis there were signs that ERM presence is negative related to firm value. The main analysis supports this trend, when using ERM as explanatory variable and finds significant negative effect of ERM presence on firm value. This negative effect is present in almost every model throughout the analysis. These outcomes give solid evidence to not only reject hypothesis 1, which state that the use of ERM contributes to increased firm value, but in fact is able to state that the presence of ERM contributes to decrease in firm value.

The proposed determinant of firm value in the form of ROA shows a positive significant effect on firm value. However the interaction variable of ROA shows no significant relation, hereby only able to not accept hypothesis 1a. When looking at the interaction variable of ROA beside the significant level, the direction of the interaction variable is negative, indicating that the use of ERM has negative moderating effect on the ROA and firm value relation, hereby mitigating the effect of ROA on firm value. The measure of sales growth shows significant positive effect on firm value. Here the interaction variable of sales growth reveals insignificant results. The direction of the coefficient however is negative, which indicates that ERM mitigates the effect of sales growth on firm value. Due to the insignificant results, this paper is not able to accept hypothesis 1b. The consistency measures reveal mixed results. The cash flow from operating activities reveals insignificant relation to firm value, whereas the direction of the coefficient is as expected; a negative relation between cash flow volatility and firm value. Earnings per share volatility on the other hand reveal significant positive effects on firm value, implying that increased earnings per share volatility leads to higher firm value. Both insignificant levels of the interaction variables cash flow volatility and earnings per share volatility leads to the inability to accept hypothesis 1c. The financial sector dummy reveals significant negative effect, resulting in the effect of being a financial firm lowers firm value in comparison to non-financial firms. The financial crisis dummy reveals in the period 2007-2008 overall lower firm value in comparison to the 2009 until 2011 period. This confirms the major downturn in the year 2008.

29

Table 4. random effect model, dependent variable = annual excess stock return with financial sector dummy (1) (2a) (2b) (2c) (2d) (3) ERM -0.023 -0.019 -0.023 -0.037 -0.033 -0.044 (1.97)** (1.17) (1.93)* (2.26)* * (2.31)* * (1.83)* ROA 0.682 0.700 0.682 0.680 0.675 0.676 (5.90)** * (5.32)** * (5.89)** * (5.87)** * (5.85)** * (4.99)** * SG 0.275 0.275 0.278 0.276 0.276 0.278 (7.17)** * (7.17)** * (6.30)** * (7.20)** * (7.20)** * (6.28)** * CFVOP -0.007 -0.008 -0.007 -0.021 -0.009 -0.021 (0.45) (0.46) (0.46) (0.96) (0.52) (0.97) EPSV 0.012 0.012 0.012 0.012 0.008 0.008 (2.67)** * (2.66)** * (2.65)** * (2.55)* * (1.28) (1.25) INTERACTION_ROA -0.067 -0.010 (0.32) (0.05) INTERACTION_SG -0.009 -0.004 (0.12) (0.05) INTERACTION_CFVOP 0.040 0.037 (1.21) (1.13) INTERACTION_EPSV 0.009 0.008 (1.06) (0.87) SIZE -0.010 -0.010 -0.010 -0.010 -0.010 -0.010 (2.07)* * (2.10)* * (2.06)* * (2.05)* * (2.11)* * (2.09)* * OPACITY -0.022 -0.022 -0.022 -0.021 -0.023 -0.021 (0.87) (0.84) (0.87) (0.81) (0.88) (0.82) SLACK -0.003 -0.003 -0.003 -0.002 -0.003 -0.002 (0.13) (0.13) (0.14) (0.09) (0.13) (0.10) LEVERAGE 0.073 0.073 0.073 0.070 0.073 0.070 (2.08)* * (2.08)* * (2.07)* * (2.00)* * (2.09)* * (2.01)* * FIN_Dummy -0.036 -0.037 -0.036 -0.035 -0.038 -0.038 (2.31)* * (2.32)* * (2.31)* * (2.29)* * (2.44)* * (2.39)* * Constant 0.118 0.118 0.117 0.122 0.126 0.128 (1.55) (1.55) (1.54) (1.60) (1.64)* (1.68)* Observations 2033 2033 2033 2033 2033 2033 Number of firms 440 440 440 440 440 440 R-squared 0.10 0.10 0.10 0.10 0.10 0.10 * significant at 10%; ** significant at 5%; *** significant at 1%

30

Table 5. random effect model, dependent variable = annual excess stock return with pre-and current crisis dummy

(1) (2a) (2b) (2c) (2d) (3) ERM -0.024 -0.023 -0.024 -0.038 -0.032 -0.049 (1.97)* * (1.43) (1.98)* * (2.28)* (2.21)* * (1.98)* * ROA 0.681 0.684 0.681 0.678 0.676 0.662 (5.95)** * (5.27)** * (5.94)** * (5.92)** * (5.91)** * (4.95)** * SG 0.292 0.292 0.292 0.293 0.292 0.293 (7.51)** * (7.50)** * (6.61)** * (7.53)** * (7.52)** * (6.61)** * CFVOP -0.005 -0.005 -0.005 -0.019 -0.006 -0.019 (0.29) (0.29) (0.29) (0.89) (0.35) (0.90) EPSV 0.010 0.010 0.010 0.009 0.007 0.006 (2.12)* * (2.11)* * (2.11)* * (2.01)* * (1.02) (0.95) INTERACTION_ROA -0.011 0.039 (0.05) (0.17) INTERACTION_SG 0.000 0.001 (0.01) (0.01) INTERACTION_CFVOP 0.043 0.041 (1.28) (1.22) INTERACTION_EPSV 0.007 0.007 (0.86) (0.77) SIZE -0.014 -0.014 -0.014 -0.014 -0.015 -0.014 (3.02)** * (3.03)** * (3.02)** * (2.98)** * (3.10)** * (3.03)** * OPACITY -0.015 -0.015 -0.015 -0.013 -0.014 -0.013 (0.59) (0.58) (0.59) (0.53) (0.58) (0.54) SLACK -0.004 -0.004 -0.004 -0.003 -0.004 -0.003 (0.18) (0.18) (0.18) (0.15) (0.18) (0.14) LEVERAGE 0.071 0.071 0.071 0.068 0.070 0.068 (1.96)* * (1.96)** (1.97)* * (1.88)* (1.96)* * (1.88)* CRISIS_Dummy 0.048 0.048 0.048 0.048 0.048 0.048 (3.95)** * (3.95)** * (3.94)** * (3.95)** * (3.97)** * (3.97)** * Constant 0.153 0.153 0.153 0.157 0.162 0.164 (2.05)* * (2.05)* * (2.06)* * (2.10)* * (2.16)* * (2.19)* Observations 2033 2033 2033 2033 2033 2033 Number of firms 440 440 440 440 440 440 R-squared 0.10 0.10 0.10 0.10 0.10 0.10 * significant at 10%; ** significant at 5%; *** significant at 1%

31

Conclusion

Conclusion

The objective of this paper is to examine if firms that adopted Enterprise Risk Management (ERM) have better anticipated and withstand the financial crisis in comparison to firms that haven’t adopted ERM before the financial crisis of 2008, hereby investigating the effect of ERM on firm value. Overall it can be stated that firms that have adopted ERM have a lower (excess) stock return in comparison to firms that haven’t adopted ERM before the financial crisis of 2008. In addition a negative effect of the presence of ERM on firm value is revealed. This difference can also be revealed by lower return on assets/equity, lower growth opportunities and more volatile cash flows / earnings of firms that have adopted ERM, in comparison to firms that haven’t adopted ERM. In addition it is revealed that firms that have adopted ERM are on average larger, have a lower proportion of intangible assets, are less able to repay their debt with current cash holdings and have higher leverage.

Furthermore the random effect model shows insignificant results of the supposedly positively effect of ERM on return, growth and consistency. Hereby unable to accept that ERM leads to increased return, enhanced growth or improved consistency. There are a few explanations for this insignificance as well as for the reverse outcomes when comparing the ERM sample with the Non-ERM sample. First explanation derives from the reasoning for adoption of ERM and the difference in re-active and pro-active behavior in regards to risk management. A firm’s initiative for adopting ERM is likely to be derived from their previous and current downturn in firm performance, experienced by the firm itself or the firm’s direct surroundings, when a firm is re-active in its risk management policy. Besides the downturn in firm performance, the initiative for adopting ERM can be determined by the increased scrutiny of governments in regards to risk management. Where the benefits of ERM are believed to be fruitful after ERM is matured, which takes several years; the present financial characteristics shown in this paper are mainly representing the current downturn of firm performance leading to the initiative of adopting ERM, as well as representing the implementation cost of adopting ERM. In addition the increase in scrutiny by governments could lead to the adoption of ERM; however the actual impact of improved risk management policy is still lacking. This idea of ERM adaptation would indeed result in the lower firm value revealed by firms that have adopted ERM. Support for this reasoning can be found in the firm performance downturn revealed in the high leverage of ERM firms and the lower cash ratio, indicating that the firm that have adopted ERM are less able to pay off current debt, while their debt level is substantially high.

32 increasing the overall leverage of the firm. This wouldn’t be an issue if the return, growth and mainly consistency act like it is forecasted under ERM. However when those projections are somehow unrealistic in terms of the perceived benefits of ERM, the firm only puts itself in a downwards spiral with their increased leverage, ultimately leading to tremendous amounts of financial distress cost, leading to the downfall of the firm.

In final, it can be noticed, that a substantial number of flaws detected with the use of ERM relate back to the complexity of coordination and aggregation of a firms total risk profile, in combination with increased number and variety of risks a firm is facing. With that the firm itself is lacking the controlling and managing ability of their overall risks and specific risks, due to the lack of understanding of those specific risks, their interconnectedness with each other and their embeddedness in a wider sense. With this inability, from a management perspective, it is difficult to translate top-down risk enterprise risk management policy that is unambiguously understood and put into action by the individuals of the risk management department. This is all leading up to and adding to the limitations of the anticipation and withstanding of firms that have adopted ERM before the financial crisis.

Limitations and directions for future research

By referring to the quote; when written in Chinese, the word "crisis" is composed of two

characters. One represents danger and the other represents opportunity (John F. Kennedy). One

34

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37

Appendix 1, Tillinghast-Tower Perrin (2001) model

Figure of Tillinghast-Tower Perrin (2001), the objective is to increase enterprise value by establishing the proper foundation of capital, enhancing growth opportunities, increasing return on capital and improving the consistency of results.

Appendix 2, Examples of ERM and Non-ERM determination

Examples of ERM

1. Business Wire, November 7, 2001,

AGL Resources Names Rozgonyi Vice President and Chief Risk Officer

BODY: AGL Resources Inc. (NYSE: ATG) today announced Gene Rozgonyi has been named vice president and chief risk officer.

38 2. Business Insurance, August 27, 2001, Monday

Comings & Goings: Buyers - Praxair taps Inserra as risk exec

Richard M. Inserra has been named assistant treasurer and director-risk management at Praxair Inc., a Danbury, Conn.-based producer of specialty gases for chemical companies and other industries.

Mr. Inserra's responsibilities in the newly created position cover global risk management and risk financing. He also is the president of Praxair's captive insurance subsidiaries.

Example of Non-ERM

1. ALEXION PHARMACEUTICALS, INC. proxy statement 2011

Board's Role in Risk Oversight

The Board is responsible for overseeing Alexion's risk management processes. The full Board performs a periodic risk assessment with management to review the primary risks facing Alexion and to manage the activities of Alexion in identifying and mitigating such risks. Management identifies risks in multiple areas, including compliance, financial, strategic, political and operational risks, and on a regular basis the Board reviews together with management. The Board recognizes that Alexion is subject to both internal and external risks, within and outside its control, and that management and the Board should regularly seek to identify those risks and mitigate to the extent possible. As part of the risk management process and consistent with its standing oversight role, each Board committee considers the risks within its areas of responsibility and assists the Board in its oversight of the risk management process.

Appendix 3, List of Non-ERM and ERM firms

Non-ERM sample sorted by sector

CONSUMER DISCRETIONARY HEALTH CARE

ABERCROMBIE & FITCH CO EDWARDS LIFESCIENCES CORPORATION AMAZON.COM, INC. ELI LILLY AND COMPANY

APOLLO GROUP INCORPORATED EXPRESS SCRIPTS HOLDING COMPANY AUTONATION, INC. FOREST LABORATORIES, INC. AUTOZONE, INC. GILEAD SCIENCES, INC. BED BATH & BEYOND INC. HOSPIRA, INCORPORATED

BIG LOTS, INC. HUMANA INC

CABLEVISION SYSTEMS CORPORATION INTUITIVE SURGICAL, INC.

CARMAX, INC. LABORATORY CORPORATION OF AMERICA HOLDINGS CARNIVAL CORPORATION LIFE TECHNOLOGIES CORPORATION

CBS CORPORATION MCKESSON CORPORATION CHIPOTLE MEXICAN GRILL, INC MEDTRONIC, INCORPORATED

COACH, INC. MYLAN INC

D.R. HORTON, INC PATTERSON COMPANIES, INC. DARDEN RESTAURANTS, INC. PERKINELMER INCORPORATED DEVRY INCORPORATED PERRIGO COMPANY