COMPOSITION, STRUCTURE & RISK-TAKING - a study on Danish bank boards 2003-2008
COPENHAGEN BUSINESS SCHOOL 2010
STINE MARIE SKOV CAND.MERC(FIR) 270881-xxxx CASPER JUUL KAUFMANN CAND.MERC(FSM) 110683-xxxx
SUPERVISOR: PROF., DR.MERC. FINN ØSTRUP
CHARACTERSCHARACTERS:::: 272.481 PAGES: 226
Individual contribution to the thesis at hand: Casper Juul Kaufmann wrote all even pages Stine Marie Skov wrote all odd pages
2 EXECUTIVE SUMMARY
The thesis at hand is motivated by the criticism directed at Danish banks’ boards in the wake of the financial crisis and poses the research question: “Have the structure and composition of Danish bank board affected risk-taking in the period from 2003-2008?” To answer this, the thesis constructs ten hypotheses in a deductive, comparative research design: six hypotheses regard the composition of Danish bank boards, four regard the structure. The thesis defines five groups of stakeholders, who are all affected by the bank’s actions: the shareholders, the board of directors, the management of the bank, the depositors and society at large. The hypotheses emerge from a thorough review of the corporate governance literature field with a special dedication to agency theory, as well as from extensive literature reviews on the theory and empirical research. The answer to the research question is found through the subsequent data analysis, built on 4.829 manually collected, unique data points. The thesis finds that the structure and composition of Danish bank boards in the period 2003-2008 has indeed affected risk-taking in Danish banks, because: • Independent directors are found to allow more risk-taking than dependent directors. • Experienced board members are found to allow less risk-taking than inexperienced (less than five years of board experience) • Directors with more than three simultaneous directorships are found to allow more risk- taking than directors with three or less directorships • Directors are found to allow increasingly more risk as their years on the board increases • Directors with a master’s degree in finance, economics, business economics or accounting are found to allow more risk-taking than those without such an educational background • The existence of incentive programs (bonuses and stock (option) plans) is found to be positively related to risk-taking • It is found that if the CEO has been in place longer than the board on average, risk-taking has been increased relative to a situation in which the board has served longer than the CEO.
“Gender” and “board size” are tested as well, but do not yield any results. The origins of the findings are then discussed at length, leading to a final part that draws up three models; an actuarial model that suggests pricing the banks’ risk insurance correctly, a soft-law model that recommends specific bank governance recommendations and finally, a society model in which a government representative is (re-) introduced to banks’ boards.
3 1 INTRODUCTORY PART 12
1.1 BACKGROUND , JUSTIFICATION AND MOTIVATION 12
1.2 RESEARCH OBJECT AND AREA 13
1.3 REAL ECONOMIC IMPACTS 13 1.3.1 THE HOUSING MARKET BUBBLE AND BUST 14
1.3.2 CREDIT AND LIQUIDITY FREEZE 15
1.3.3 STOCK MARKET TURBULENCE 16
1.3.4 OTHER IMPACTS 17
1.4 ACTORS AND ACTIONS 17 1.4.1 THE GENERAL POPULATION 17
1.4.2 THE REGULATORS 17
1.4.3 THE BANKS 18
1.5 THE RESEARCH QUESTION 18
1.6 AIM AND CONTRIBUTION 19
1.7 DELIMITATIONS 19
1.8 LIMITATIONS 20
1.9 STRUCTURE OF THE THESIS 21
2 METHODOLOGY 22
2.1 METHODOLOGICAL REFLECTIONS 22 2.1.1 EPISTEMOLOGY 22
2.1.2 ONTOLOGY 23
2.2 RESEARCH DESIGN 23
2. 3 DATA 24 2.3.1 PRIMARY DATA 24
2.3.2 SECONDARY AND OTHER DATA 24
2.3.3 DATA QUALITY 24
2.4 THEORY 25
2.5 PARTIAL CONCLUSION 25
3 THE RESEARCH FIELD 26
3.1 THE BANKING INDUSTRY IN DENMARK 26
3.2 THE BANKS IN SOCIETY 26
3.3 THE STAKEHOLDERS 27
4 3.3.1 THE OWNERS 27
3.3.2 THE DEBTHOLDERS 28
3.3.3 THE MANAGEMENT 28
3.3.4 THE BOARD OF DIRECTORS 28
3.3.5 THE SOCIETY 29
3.4 RISK 29
3.4.1 CREDIT RISK 29
3.4.2 MISMATCHING 30
3.4.3 FUNDING LIQUIDITY RISK 30
3.5 REGULATION AND RISK -MONITORING 30
3.6 PARTIAL CONCLUSION 31
4 THEORY 32
4.1 CORPORATE GOVERNANCE 32
4.2 TRANSACTION COST ECONOMICS 33
4.3 AGENCY THEORY 33 4.3.1 FUNDAMENTAL AGENCY THEORY 34
4.3.2 THE EXTENDED AGENCY PROBLEM 34
4.3.3 CONTRACTS 35
4.3.4 EX-ANTE INFORMATION ASYMMETRY – HIDDEN CHARACTERISTICS 36
4.3.5 EX-POST INFORMATION ASYMMETRY – MORAL HAZARD 37
4.4 TYPES OF AGENCY PROBLEMS 37
4.4.1 TYPE 1: OWNER VS . MANAGER 37
4.4.2 TYPE 2: MINORITY VS . MAJORITY INVESTORS 38
4.4.3 TYPE 3: SHAREHOLDERS VS . STAKEHOLDERS 38
4.5 DEPOSIT INSURANCE 38
4.6 RISK AND RISK PREFERENCES 41 4.6.1 THE SHAREHOLDERS 42
4.6.2 THE BOARD OF DIRECTORS 42
4.6.3 THE MANAGEMENT 42
4.6.4 THE DEBTHOLDERS 43
4.6.5 THE SOCIETY 43
4.7 ALTERNATIVE CEO RISK PREFERENCES 44 4.7.1 OTHER MODELS OF CEO RISK PREFERENCES 44
4.8 THE BOARD OF DIRECTORS 45 4.8.1 THE ROLE OF THE BOARD 46
5 4.8.2 THE OPTIMAL BOARD 47
4.9 PARTIAL CONCLUSION 48
5 HYPOTHESES 49
5.1 DETERMINING THE TESTABLE PARAMETERS 49
5.2 INDIVIDUAL LEVEL 49 5.2.1 INDEPENDENCE 50
5.2.2 BOARD EXPERIENCE 52
5.2.3 GENDER 53
5.2.4 MULTIPLE DIRECTORSHIPS 56
5.2.5 BOARD TENURE 59
5.2.6 FINANCIAL EDUCATION 61
5.3 HYPOTHESES - THE BOARD LEVEL 63
5.3.1 BOARD SIZE 63
5.3.2 INCENTIVE PROGRAMS 64
5.3.3 THE CEO’ S TENURE VERSUS THE BOARD ’S TENURE 67
5.4 PARTIAL CONCLUSION 68
6 SAMPLE CONSTRUCTION 69
6.1 THE TIMEFRAME 69
6.2 THE POPULATION AND SAMPLE 69 6.2.1 EXCLUDED BANKS 71
6.3 THE BOARD MEMBERS 72
6.4 WEIGHING THE INFLUENCE 72
6.5 INDIVIDUAL LEVEL VARIABLES 72 6.5.1 INDEPENDENCE 72
6.5.2 BOARD EXPERIENCE 73
6.5.3 GENDER 73
6.5.4 MULTIPLE DIRECTORSHIPS 73
6.5.5 TENURE 74
6.5.6 FINANCIAL EDUCATION 74
6.6 BOARD LEVEL VARIABLES 74 6.6.1 BOARD SIZE 75
6.6.2 INCENTIVES 75
6.6.3 THE CEO’ S TENURE VS . THE BOARD ’S TENURE 75
6 6.7 PARTIAL CONCLUSION 75
7 RISK MEASURES 76
7.1 ASSEMBLING RISK IN ONE MEASURE 76
7.2 STOCK VOLATILITY 76
7.3 ABSOLUTE GROWTH IN LOANS 77
7.4 ANNUAL RELATIVE INCREASE IN LOANS 77
7.5 GROWTH IN THE LOAN /DEPOSIT RATIO 78
7.6 THE ABSOLUTE LEVEL OF LOANS TO DEPOSITS 79
7.7 CHOICE OF RISK MEASURE 81
7.8 PARTIAL CONCLUSION 82
8 DESCRIPTIVE STATISTICS 83
8.1 THE SAMPLE 83
8.2 THE RISK MEASURE 83
8.3 INDIVIDUAL VARIABLES 84 8.3.1 INDEPENDENCE 84
8.3.2 BOARD EXPERIENCE 84
8.3.3 GENDER 85
8.3.4 MULTIPLE DIRECTORSHIPS 85
8.3.5 TENURE 87
8.3.6 FINANCIAL EDUCATION 87
8.4 BOARD LEVEL VARIABLES 88 8.4.1 BOARD SIZE 88
8.4.2 INCENTIVE PROGRAMS ; BONUS AND STOCKS 89
8.4.3 CEO VS . BOARD 89
8.5 PARTIAL CONCLUSION 90
9 DATA ANALYSIS 91
9.1 REGRESSION ANALYSIS 91
9.2 MODELS FOR ANALYSIS 91
9.3 STATISTICAL RESULTS 93
9.3 REFERENCE CATEGORIES 93 9.4.1 INDIVIDUAL LEVEL , INCLUDING EMPLOYEE -ELECTED REPRESENTATIVES 94
7 9.4.2 INDIVIDUAL LEVEL , EXCLUDING EMPLOYEE -ELECTED REPRESENTATIVES 94
9.4.3 BOARD LEVEL , INCLUDING EMPLOYEE -ELECTED REPRESENTATIVES 94
9.4.4 BOARD LEVEL , EXCLUDING EMPLOYEE -ELECTED REPRESENTATIVES 94
9.5 RESULTS 95 9.5.1 INDIVIDUAL INDEPENDENT VARIABLES 95
9.5.2. INDEPENDENCE 95
9.5.3 BOARD EXPERIENCE 95
9.5.4 GENDER 96
9.5.5 MULTIPLE DIRECTORSHIPS HELD BY THE BOARD MEMBER 96
9.5.6 TENURE (TIME SPENT ON THE BOARD ) 96
9.5.7 FINANCIAL EDUCATION 97
9.6 BOARD LEVEL INDEPENDENT VARIABLES 97 9.6.1 BOARD SIZE 97
9.6.2 STOCK PAYMENT / STOCK OPTIONS 97
9.6.3 BONUS SCHEMES 98
9.6.4 CEO VS . THE BOARD 98
9.7 CORRELATIONS 98 9.7.1 MODEL 1A AND 1B. 99
9.7.2 MODEL 2A AND 2B 99
9.8 FULL MODELS 100
9.9 MOST RISK -TAKING DIRECTOR AND BOARD 100
9.10 PARTIAL CONCLUSION 101
10 DISCUSSION AND IMPLICATIONS 102
10.1 INDEPENDENCE 102 10.1.1 DISCUSSION OF THE FINDINGS 102
10.1.2 THE SAMPLE 103
10.1.3 IMPLICATIONS 104
10.2 BOARD EXPERIENCE 105 10.2.1 DISCUSSION 105
10.2.2 THE SAMPLE 106
10.2.3 IMPLICATIONS 106
10.3 GENDER 107 10.3.1 DISCUSSION 107
10.3.2 SAMPLE 107
10.3.3 IMPLICATIONS 107
8 10.4 MULTIPLE DIRECTORSHIPS 108 10.4.1 DISCUSSION 108
10.4.2 THE SAMPLE 108
10.4.3 IMPLICATIONS 109
10.5 TENURE 109 10.5.1 DISCUSSION 109
10.5.2 THE SAMPLE 110
10.5.3 IMPLICATIONS 110
10.6 FINANCIAL EDUCATION 110 10.6.1 DISCUSSION 110
10.6.2 SAMPLE 111
10.6.3 IMPLICATIONS 111
10.7 BOARD SIZE 112 10.7.1 DISCUSSION 112
10.7.2 THE SAMPLE 112
10.7.3 IMPLICATIONS 113
10.8 INCENTIVE PROGRAMS 113 10.8.1 DISCUSSION 113
10.8.2 THE SAMPLE 114
10.8.3 IMPLICATIONS 114
10.9 THE CEO VERSUS THE BOARD 114 10.9.1 DISCUSSION 114
10.9.2 THE SAMPLE 115
10.9.3 IMPLICATIONS 115
10.10 PARTIAL CONCLUSION 115
11 RECOMMENDATIONS 118
11.1 THE BANK AND ITS ENVIRONMENT 118 11.1.1 THE ACTUARIAL MODEL 120
11.1.2 THE SOFT LAW MODEL – WITH HARD LAW EXTENSIONS 121
11.1.3 THE SOCIETY MODEL 121
11.1.4 FINAL RECOMMENDATION 122
11.5 PARTIAL CONCLUSION 122
12. CONCLUSIONS 123
9 13 REFERENCE LIST 125
14 TABLE OF CONTENTS - APPENDICES 133
10 TABLE OF FIGURES, GRAPHS, TABLES AND CHARTS FIGURE 1.1 REAL ESTATE PRICE DEVELOPMENT IN DENMARK (1995-2009) ...... 14 FIGURE 1.2 ILLUSTRATION OF THE TED SPREAD FROM 1995 TO 2009 ...... 15 FIGURE 1.3 ILLUSTRATION OF VARIOUS STOCK MARKET INDICES (2003-2008) ...... 16 FIGURE 1.4 OVERVIEW OF THE THESIS STRUCTURE ...... 21 FIGURE 4.1 GRAPHICAL DEPICTION OF THE CALL OPTION ON EQUITY ...... 39 FIGURE 4.2: GRAPHICAL DEPICTION OF THE DEBTHOLDER’S PUT OPTION ...... 41 FIGURE 4.3: GRAPHICAL DEPICTION OF THE RISK PREFERENCES OF THE 5 STAKEHOLDER ...... 41 TABLE 5.1 DIVERSITY PARAMETERS ...... 54 FIGURE 6.1 SIX LARGEST DANISH RETAIL BANKS IN THE SAMPLE ...... 70 FIGURE 6.2 THE MEDIUM-SIZED RETAIL BANKS IN THE SAMPLE ...... 70 FIGURE 6.3 THE SMALLEST DANISH RETAIL BANKS INCLUDED IN THE SAMPLE ...... 71 TABLE 6.1: EXCLUDED BANKS ...... 71 TABLE 7.1: LOAN/DEPOSIT RATIO FOR SELECTED BANKS IN 2007 ...... 81 TABLE 8.1 LOAN/DEPOSIT RATIOS FOR THE PERIOD 2003-2008 ...... 83 TABLE 8.2 INDEPENDENCE ...... 84 TABLE 8.3 BOARD EXPERIENCE ...... 84 TABLE 8.4 GENDER ...... 85 TABLE 8.5 MULTIPLE DIRECTORSHIP ...... 86 TABLE 8.6 TENURE ...... 87 TABLE 8.7 FINANCIAL EDUCATION ...... 87 TABLE 8.8 BOARD SIZE ...... 88 TABLE 8.9 INCENTIVE PROGRAMS ...... 89 TABLE 8.10 BOARD VS. CEO ...... 89 TABLE 9.1 MODEL STATISTICS ...... 93 FIGURE 11.1: THE BANK’S STAKEHOLDERS; IMPACT AND INFLUENCE ...... 119
11 1 INTRODUCTORY PART
The following thesis finds its motivation in the criticism directed at Danish banks and especially Danish banks’ boards of directors in the wake of the economic boom and subsequent bust. In the public debate it is a common perception that Danish bank boards have ratified excessive risk-taking in banks, which leads to the research question of the study at hand: “Have the structure and the composition of Danish bank boards affected risk-taking in the period from 2003-2008?” Methodologically, the investigation into the research question is conducted deductively through the examination of ten hypotheses. The hypotheses are of course not arbitrary; rather, they are derived from a comprehensive review of the corporate governance research field and from multiple literature reviews on specific subtopics of corporate governance. However, in accordance with deductive methodology, it is not argued at length why the hypotheses in question are chosen as they are. Rather, they are justified by actually leading to significant results in the course of examination. Agency theory is the most important basis for formulating these hypotheses. Six hypotheses are directed at the individual director’s characteristics and are thus concerned with the composition of boards, while four investigate the board’s characteristics and thereby the structure of boards. The sample used to test these hypotheses is comprised of 67 Danish banks and 749 directors, a data pool of 4.829 unique data points. Data analysis leads to a number of results and observations, which are interpreted and discussed further. The discussion lays a foundation for recommendations to improve current corporate governance practices. The concluding sections answer the research question by determining that risk-taking and board structure/board composition are in fact related to a certain extent.
1.1 Background, justification and motivation The thesis at hand is fundamentally motivated by the global financial crisis 1 observed in the past years and its research is justified by the real economic impacts this crisis has had (and still has) on large parts of society. This introductory part of the thesis outlines the research object and area and subsequently elaborates on its justification by outlining the real economic
1 For clarification reasons it should be noted that while the term “financial crisis” may represent a rather populist version of “financial turbulence, financial turmoil, economic contraction, recession” and so forth, it is used in this thesis as a covering term for the abnormal happenings in the financial markets in the later years. Also, ‘financial crisis’ is a well-known term.
12 impacts the crisis has had and following this, the actors and actions that have been publically discussed as culprits are presented.
1.2 Research object and area While the culprit of the crisis is still being debated, the real economic effects are clearly visible, as presented in the next paragraph. The public debate points towards financial institutions as those responsible for engendering a crisis at such a scale by lending out too much money. More specifically, the criticism is aimed at the management of the financial institutions (‘management’ in this sense including the board of directors and the executive level within the institutions). At the time of writing, a consensus seems to have formed to the effect that financial institutions in general and banks in particular have engaged in irresponsible, excessive risk-taking. However, the criticism is still imprecise, which impedes the development of corrective measures to prevent similar crises in the future. This motivates researching the management and the management systems of the banks, specifically those in the bank holding the final responsibility – the board of directors. This is the research object of the thesis and therefore, the natural field of research is that of corporate governance . The criticism aimed at the banks’ boards is a global phenomenon, but in order to reduce potential bias stemming from different political, economical, social, technological and legal business environments, the research sample is concentrated on one area; Denmark. Danish banks provide a relevant sample as it has been argued that the Danish banking industry, once considered a safe, conservative one, has been hit relatively hard by the financial crisis. Thus, the research object for the thesis is the relevant aspects of the constitution of boards of directors in Danish banks.
1.3 Real economic impacts Before venturing into describing the institutions criticized in the wake of the crisis, its impacts on various parts of society are outlined. Generally speaking, the impacts of the financial crisis fall into three different, but surely inter-linked, categories. They are identified as the housing market bubble (and bust), the credit and liquidity freeze and the abnormal stock market fluctuations as well as unusual fluctuations in ‘other’ markets. They will each shortly be described and their impact on the real economy will be outlined to justify the treatment of the financial crisis as a researchable problem.
13 1.3.1 The housing market bubble and bust Throughout many parts of the world, house prices increased rapidly from about 2002-2003 until reaching peaks in the late part of 2006, in 2007 or in 2008. In the research area of the thesis, Denmark, the house price boom took off around 2003 and peaked in late 2006 2:
Figure 1.1 Real estate price development in Denmark (1995-2009)
Real-estate prices 29000 24000 19000 14000 9000 4000 Q1 1995 Q1 1995 Q4 1996 Q3 1997 Q2 1998 Q1 1998 Q4 1999 Q3 2000 Q2 2001 Q1 2001 Q4 2002 Q3 2003 Q2 2004 Q1 2004 Q4 2005 Q3 2006 Q2 2007 Q1 2007 Q4 2008 Q3 2009 Q2
Houses Apartments
All real-estate price data in figure 1.1 have been retrieved from Realkreditrådet (Realkreditraadet 2010a) When the boom ended, prices plummeted as depicted in figure 1.1 and (partly) because of the high leverage in home purchases during the boom, numerous home owners now face negative equity on their mortgages (linearly correlated to the size – in % - of the mortgage taken out). This effectively immobilizes these groups of people in the housing market as they cannot move without converting their negative equity into a loan without collateral. This loan will in some instances end up being more expensive than the payment on the mortgage taken out in the home purchased. This is clearly an efficiency loss in the housing market which risks spilling into the labor market as a second-order effect, as increasing labor force immobility can lead to increasing mismatching in the job market. On the other hand, those who did not enter the housing market during the boom are affected by much stricter credit policies by the banks if wanting to purchase a home (Børsen 2009b, Direkt 2010, Kjær 2010). This is also an indication of ineffective allocation of resources in the housing market as entry into the housing market in recent years can be said to have been determined as much by timing of entry as by economic ability. With hindsight, a consensus is forming that some loans should not have been granted – although housing prices are somewhat stabilized at the time of writing, the number of foreclosures on homes is still rising (Realkreditraadet 2010b).
2 Considerable geographical variation exists, but the first markets to stagnate, Copenhagen apartments, did so in the 3 rd quarter of 2006
14 In summary, the seemingly lax credit policies of mortgage lenders (who finance upwards of 80 % of the home purchase) and the banks (who finance the rest) have been suggested to have led to too many and too expensive home purchases, which could be defined as a housing bubble (Kindleberger 1987). The behavior of the banks has drawn critical remarks from several sources. For example, the Danish Social Democrat opposition leader writes that “[we] are determined to never again be placed in a situation in which recklessness in the financial sector would present a real threat to our national wealth and welfare”, (Thorning-Smith 2009) (translated for this thesis), a view shared by others (Formsgaard 2008, Lunde 2008)
1.3.2 Credit and liquidity freeze Another visible pointer towards the suggestion that banks in general had lend out too much money was the credit and liquidity freeze beginning in the Spring of 2007 and culminating with first Bear Stearn’s fire sale in March 2008 to JPMorgan and finally with the bankruptcy of Lehmann Brothers in August 2008 (Wearden, Teather et al. 2008, Brunnermeier 2009). Interbank-overnight rates climbed as insecurity about the banks’ investment portfolios spread and banks across the board sought to reduce engagements to stock up on equity because the loan portfolios suddenly were deemed of much less quality than originally anticipated.
Figure 1.2 Illustration of the TED Spread from 1995 to 2009 3
450 TED SPREAD
400
350
250
200
100
50
2000 20012002 2003 2004 2005 2006 2007 2008 2009 Source: Data in figure 1.2 was retrieved from Yahoo Finance (Yahoo Finance 2010) 4
3 The TED spread the difference between the interest rate on three-month Treasury bills and three-month LIBOR, the rate banks charge on loans to each other. The TED spread is an indication of lack of trust in financial markets; its widening was a sign that things were going bad (Krugmann 2008).
15 Hence, many small businesses, dependent on running lines of credit, suddenly faced harder conditions when re-negotiating terms and interest rates with their banks (Børsen 2009b, Børsen 2009a). Undoubtedly, some negative-NPV-projects have been avoided by stricter credit policies - which is economically sound - but it must be considered likely that some projects with arguably positive NPV have been turned down due to lack of credit facilities. This, too, constitutes a real economic impact of the financial crisis and it too can be traced back to the lax lending policies in the years leading up to the crisis.
1.3.3 Stock market turbulence Stock markets lost substantial amounts of value as the forecasts for future demand and economic activity on the whole changed. Also, with the contraction of credit, leveraged investments decreased significantly once the future projections turned sour (European Commision 2010)
Figure 1.3 Illustration of various stock market indices (2003-2008)
FTSE OMX OMX FTSE 600,0000 7000 6500 500,0000 6000 400,0000 5500 300,0000 5000 4500 200,0000 4000 100,0000 3500 0,0000 3000 01 -01 -2003 01 -01 -2004 01 -01 -2005 01 -01 -2006 01 -01 -2007 01 -01 -2008 02 -01 -2003 02 -01 -2004 02 -01 -2005 02 -01 -2006 02 -01 -2007 02 -01 -2008
Nasdaq Nasdaq Dow Jones Dow Jones 3.000,0000 16000 2.800,0000 2.600,0000 14000 2.400,0000 12000 2.200,0000 2.000,0000 10000 1.800,0000 1.600,0000 8000 1.400,0000 6000 1.200,0000 1.000,0000 4000 02 -01 -2003 02 -01 -2004 02 -01 -2005 02 -01 -2006 02 -01 -2007 02 -01 -2008 02-01-2003 02-01-2004 02-01-2005 02-01-2006 02-01-2007 02-01-2008
All stock data in figure 1.3 has been retrieved from Euroinvestor in July 2010 for the period 2003-2008 (Euroinvestor 2010) .
It is not argued that it is an economic problem that stocks lose value per se , nor is it a problem that investors re-calibrate their risk forecasts; these events are part of keeping the markets efficient. It is argued, though, that markets work less efficiently if booms and busts occur and the transition from one to the other is characterized by (irrational) euphoria or panic (Jorion
16 2007), which can distort the fundamental value (as measured by the share price) of companies temporarily, leaving room for arbitrage, which can only occur in imperfect market conditions. The impact on the broader parts of the population is found – mainly – in pension funds, whose value increased as markets did and then decreased along with the market, leaving savers with greater uncertainty about their future income stream.
1.3.4 Other impacts Other impacts include commodities markets (copper, oil, gold), which have shown indications of smaller booms following the withdrawal of investments from the stock markets. These local booms exhibit the features of an investor ‘flight to safety’ in which funds are withdrawn from corporate shares and placed in commodities carrying real, intrinsic value. When commodities become investment objects, those utilizing the commodities for production and consumption face inflated prices and less purchasing power, thus hindering production/consumption with the commodity, because it is crowded out by the investment purchases.(Forbes.com 2008) Aside from the purely business and private economic impacts, the financial crisis has sparked national economic crises that are in many cases related to high lending and borrowing 5(European Commision 2010, Caballero, Farhi et al. 2008).
1.4 Actors and actions Having now looked at (some of) the effects of the financial crisis, the focus turns to the actors in the events leading up to the crisis and to the actions taken by these actors.
1.4.1 The general population While not the research focus of the thesis, reactions and perceptions within the general population and the climate surrounding the boom cannot be completely left unmentioned. A general sense of real estate as an eternally superior investment (Skovgaard 2006, Carstensen 2007, Hansen 2007), and unprecedented increases in consumption spending as a result of second mortgages taken out in the hastily rising home equity have arguably led to pressure on banks to finance the outer 20 % of expensive home purchases.
1.4.2 The regulators In the area on which this thesis is focused, Denmark, it is the Danish Financial Supervisory Authority (“Finanstilsynet”, DFSA) which has been in charge of monitoring the banks’ loans
5 Greece springs to mind as an infamous example.
17 and their portfolios (Financial Business Act 2003, Financial Business Act 2003, Financial Business Act 2003, Financial Business Act 2003). The deposit insurance in Danish banks as well as the perceived notion of the society as a ‘lender of last resort’ for the banks necessitates a supervisory authority. The DFSA has been criticized for not intervening in the period 2003- 2008, especially for de-facto allowing the banks to build up large and/or undiversified loan portfolios (Børsen 2008, DR 2009, Heering, Jeppesen et al. 2009) which in some cases have been much too large, causing financial distress when the financial crisis commenced.
1.4.3 The banks Concerning the banking sector, management and governance structures have been condemned for having been too optimistic, too focused on short-term gains and for not having shown caution enough, which has led to the effects outlined above. There seems to be a consensus that those responsible for the banks’ actions have failed to live up to their responsibilities (Ritzau 2008, Børsen 2010a, Børsen 2009). This means, in effect, the banks’ boards as they are the supreme governing body of the banks (in theory, the shareholders are, but they act through the board of directors, practically as well as legally). The criticism, however, is partly inconsistent or at least points in many directions; from some sides, the boards have been criticized for not being knowledgeable enough about the relevant bank’s operations to properly monitor the top management’s actions. From other sides the criticism is that bank boards are merely rubberstamping risk-seeking CEOs’ proposals and others again point towards the incentive systems proposed/approved by the boards as the culprit of the financial crisis – in Denmark as well.
1.5 The research question This thesis seeks to remedy some of the confusion outlined in the paragraphs above. The motivation and justification have centered the attention on the banks and specifically, those holding ultimate responsibility in the banks: the board of directors, which emerges as the object of research interest to the thesis at hand. It is an assumption of the thesis that no comprehensive study on the Danish bank boards exist. Rather, many fragmented perspectives (incentive pay, education etc.) have been proposed by academics and public commentators alike. As the value and consequences of having a board cannot be tested – all banks must have a board, thereby making it an exogenous factor – the attention shifts to the differences between boards; their respective different structures and the composition of each individual board member’s characteristics in the years leading to the onset of the financial crisis, to be precise.
18 The research question of the thesis is then: “Have the structure and the composition of Danish bank boards affected risk-taking in the period from 2003-2008?”
The question is sought answered through an exhaustive examination of the Danish bank boards and each of their directors. Instead of dividing the research questions into sub- questions, the thesis answers its research question through building ten hypotheses and subsequently testing and analyzing these, leading to a frame for the discussion and recommendations.
1.6 Aim and contribution It is the aim of the thesis to provide the reader with a comprehensive overview of the Danish bank boards in the period of economic boom and subsequent bust (2003-2008), specifically of the characteristics of the boards and of the board members that take significance in risk-taking behavior. The thesis aims to equip shareholders in Danish banks with a study that can guide the election of board members dependent on the behavior wished on the board, yet it is also the aim to provide the public debate and, in turn, the policy makers with information on which type of bank board structures and which type of bank board director that have taken on or allowed relatively more/less risk in the researched period. The thesis’ contribution is that it is the first study to undertake such an exhaustive review of the Danish bank boards with respect to the period leading up to (and including some of) the financial crisis.
1.7 Delimitations The thesis places itself within a large theoretical field as well as in a large subject field: the study of corporate governance applied to the financial crisis could go in almost any direction and could take several theoretical approaches. This thesis chooses to follow core corporate governance theory by deploying an agency problem perspective to the dynamics observed in Danish banks. Social theories at one end of the spectrum might yield other and differently qualified discoveries, as would at the other end of the spectrum the politological approaches to the governance issues in Danish banks. Furthermore, it is not the aim of the thesis to test the applicability of the agency theory field; it is the aim to answer the research question through its hypotheses.
19 The thesis will not seek to investigate the social dynamics of the relations between shareholders, stakeholders, the board and top management; neither will it embark on socio- psychological dynamic in an intra- nor an inter-organizational perspective. While these factors may indeed be relevant to the general understanding of boards of directors, they are taken as exogenous factors in the thesis at hand. The environment in which the banks work are also taken as exogenous factors in all parts of the thesis except for that of the final recommendations. That means that for instance Basel-II, the legal foundation for the Danish Financial Supervisory Authorities, whether deposit insurance should exist etc. are not the focus of this paper. In relation to the specific actions of the Danish bank boards and top managers in Danish banks, it is also a delimitation of the thesis that it is assumed that actors act in good faith. Thus, criminal acts and other actions in bad faith are not taken into account as endogenous factors.
1.8 Limitations First of all, the thesis is limited by the fact that by all accounts, not all impacts of financial crisis, (which have motivated the production of thesis), known yet. For example, at the time of writing the concluding remarks on this paper, Amagerbanken was still in considerable financial distress. Secondly, the research design and the nature of this comparative study carry with them their own limitations. For example, the chosen design is conducive to a (primarily) quantitative analysis, but it is acknowledged that a case study could capture qualitative phenomena not captured in this research design. Furthermore, the data collection is conducted as a desk study, which may limit the scope of the investigation and it is acknowledged that a more qualitative field study may have revealed relevant perspectives not presented in this investigation. Due to the scale of the research objective, specific limitations are explained when appropriate to increase the intuitive understanding of the respective sections for the reader.
20 1.9 Structure of the thesis
Figure 1.4 Overview of the thesis structure
RESEARCH QUESTION PART OBJECTIVE
Outline the motivation, introduce the research problem and objectives and Introduction present the structure and research design
Provide a solid foundation for understanding the research field
Theory
Build testable hypotheses Have the structure and composition of Danish Hypotheses bank boards affected the risk-taking in Statistically analyze the hypotheses based on the data collected. the period from 2003-2008? Analysis Discussion and implications of the findings and further recommendations
Evaluation
Summarize the findings and present the concluding remarks Conclusion
Source: own contribution Figure 1.4 illustrates the overall structure of the thesis. It is divided into six thematic parts. The parts comprise twelve distinct sections each covering numerous paragraphs. Each of the twelve sections is commenced by a partial introduction where the purpose and the structure of the respective section will be outlined. In order to capture the main pointes each section will be summarized in a partial conclusion.
21 2 METHODOLOGY
The purpose of the following section is to give an accurate account of the basic considerations and assumptions employed in this thesis. First, it is defined what is considered acceptable knowledge within the scope of this thesis through a review of its epistemological and ontological position. Then, the appropriate research design is identified. Next, the general data selection process and its sources are outlined. Finally, the theoretical field is critically reviewed.
2.1 Methodological reflections “Corporate governance” presents certain challenges as a chosen research area (as described in section 1.2); the field spans the entire social sciences theory/empirical field, ranging from in- depth qualitative social research to econometrical applications of concepts from the natural sciences. Because of the apparent width and depth of the research area, it is necessary to explicitly define the epistemological and the ontological assumptions being made, as this directs a selection process when obtaining primary data and secondary data, when identifying relevant theoretical foundations for the arguments presented, when analyzing the data and when discussing the findings.
2.1.1 Epistemology It is a basic assumption of this thesis that the outlined research problem can be understood in terms that are measurable and observable, and this is reflected in the research design. Therefore, this thesis is primarily positivist in its epistemological considerations, as it is the conviction underlying the research approach that what is observed is tangible and quantifiable (Bryman, Bell 2003). However, as this thesis seeks to provide not only an understanding of the problem, but also suggestions for optimized board structures and board composition (both implied through measurements of optimality in board work (section 4.8.2) and explicitly in the recommendations (section 11), the epistemological stance of the critical realism is appointed as well (Langergaard, Rasmussen et al. 2006). As an example, a pure positivist stance would regard all actors as (equally) rational (at least ideally), whereas this thesis acknowledges the concept of bounded rationality in human actors in economic transactions, which by definition is neither equally present nor equally constant in the individuals examined in the sample.
22 In adhering to a critical realist’s stance, it is acknowledged that human differences are real and in principle objective, even though grounds and explanations for these are not. This separates the considerations of this thesis from those of the structuralist’s or the social constructivist’s.
2.1.2 Ontology Having defined above what the thesis at hand considers acceptable knowledge the ontological perspective should be outlined to establish the understanding of the observed phenomena. As it is a founding conviction that the research objective – the board of directors – is a separate structure independent of its social actors the ontological stance must adhere to objectivism. More specifically, even though the research objective can only be approached through a specific perspective it is considered to exist independently of the perspective chosen.
2.2 Research Design The research design chosen in the thesis can be characterized as a comparative design (Bryman, Bell 2003). While the data collection and subsequent analysis may resemble that of the cross-sectional design (ibid), the objective is to determine differences between the observed entities in the sample, not to give conclusive answers on the whole sample’s features. The comparative design provides the opportunity to examine the same variables in different cases (in this case, in boards, board members and CEOs), which is crucial to solve the proposed research question. In terms of the level of research, the investigation is on the individual level when examining CEOs and board member characteristics and on the group level when examining the features and interactions of the board as a whole. The comparative research design applied in this thesis is sought to be strong in replicability by consciously choosing measurement variables that are relatively easily obtained (see section 6). Also, by being very explicit in the criteria employed, it is believed that the study could be replicated without much alteration by other groups of researchers. The design chosen should also be externally valid as none of the parameters tested are specific to the focal industry and geographic area. It therefore provides a research ground for generalization beyond the context (the sample taken into consideration) (Langergaard, Rasmussen et al. 2006). However, comparative designs have been criticized for lacking internal validity as the causal links can, in some cases, be hard to determine to a satisfactory extent. This problem is mitigated when variables are non-manipulative, which – to the extent possible – they are sought to be (Bryman, Bell 2003).
23 The nature of the study, following the research question’s and the design’s structure is that of hypothesis building, hypothesis testing with subsequent data description, data analysis and discussion of the findings in relation to the outlined hypotheses and the theory underlying these. This approach is best described as a deductive approach (ibid). The sample construction has been assigned its own paragraph, in which the specifics of the data selection are outlined, see section 6.
2. 3 Data The thesis at hand bases its findings on extensive data collection to support the testing of the constructed hypotheses. The data was collected in the period from March – July 2010 and comprises approximately 6000 manually collected unique data points. In addition to this, vast financial data on stock volatility, loan/deposit rates and other risk parameters have been collected in pre-assembled form from governmental and industry sources. To assist the hypothesis building and to structure the data analysis, thorough attention has been paid to previous studies and to existing theories in the field.
2.3.1 Primary data The primary data for the study is obtained primarily from various data sources: annual reports, online databases/directories and from the general news outlets. The primary data serves as the foundation for the investigation into the boards of Danish banks, as this data is not obtainable from any already-assembled sources. For example, the online directories provide the professional title of a board member, but do not indicate whether this amounts to having ‘experience’ or having a ‘financial education’ or not (see sections 5.2.2 and 5.2.6). These distinctions rest solely on the data obtained in the course of the research leading to this thesis at hand.
2.3.2 Secondary and other data The secondary data is obtained primarily in the form of other researchers’ articles. Also, some data is collected from researchers, who do meta-studies on previous research; thus, some data might be ‘tertiary’ in nature. The use of this data is mainly for supporting the risk-parameters (see section 7) or to support the hypothesis building through theory (see all sub-sections in section 5.
2.3.3 Data quality In the data collection, due consideration has been paid to the reliability and validity of the data sources. The validity of the data is of course only as strong as the validity of the sources.
24 Thus, some information has been found in sources that are inherently prone to information of questionable quality – such as Linkedin and Facebook profiles. However, all such sources have been cross-checked in case of doubt. For example, a person’s own claims on her/his Linkedin profile have been checked with the bank’s information or with general news. It has been the general principle to exclude data that could not be readily verified throughout the data collection process, a fact which has resulted in the omission of a few board member characteristics. This does not distort the overall data reliability, though, as more than 99.9 % of the data sought after has been found and verified.
2.4 Theory As described in section 2.1 the corporate governance area is a broad field. At the same time, the theoretical frameworks available to the researcher in corporate governance often stem from other fields and the application of these related theories to the corporate governance field have resulted in many middle range theories emerging from empirical work. Thus, the apparent ‘lack’ of grand theories is – for now – a condition which research in the field circumvents by building middle range theories through empiricism.(Bryman, Bell 2003) The theoretical works used in the thesis are found primarily in the hypothesis building. Multiple findings are cited and referenced throughout the paper.
2.5 Partial conclusion It was outlined that the thesis is positivist, critically realist and objectivist in its scientific nature. The deployed research design is that of a deductive, comparative design conducted as a desk study. The data consists of primary and secondary data and the theory is drawn from the corporate governance research field, which itself draws on a broad range of social science fields.
25 3 THE RESEARCH FIELD
The following section on the Danish banking industry serves two purposes: first, it provides the reader with an understanding of the research area and its dynamics. Second, it serves the purpose of elaborating on the relevance of researching the industry by defining the banks’ role in society (as it is seen from this thesis’ perspective) and by defining the stakeholders to the Danish banks – the latter undoubtedly being intertwined with the former.
3.1 The banking industry in Denmark The Danish banking industry is at the time of writing comprised of 133 banks, which in total have DKK 2.7 trillion. of capital at work 6. The industry is relatively concentrated with the six largest banks making up > 80 % of the total capital. The largest bank, Danske Bank, alone accounts for 52 % of the total capital (Finanstilsynet 2010). In Denmark, three types of banks serving individual consumers exist: retail banks (“banker”), savings banks (“sparekasser”) and cooperative savings banks (“andelskasser”). The legislation on the three types has in the later decades converged and differs only when regarding ownership structure. All retail banks must be incorporated, whereas savings banks can be owned by self-governing foundations. Cooperative banks are owned by the members of the cooperative. Retail banks cover 95 % of the total banking industry, savings banks and cooperative savings banks the remaining 5 %(Finanstilsynet 2010). Due to the similarities between banks and because retail banks make up such large part of the industry, the incorporated ownership structure is the one considered in this thesis. This would justify referring to the owners of the banks considered in the paper at hand as the “shareholders”.
3.2 The banks in society As outlined in section 1, the banks have drawn massive criticism to themselves as the financial crisis took hold. The instability (allegedly) caused by the banks’ practices has, as described in section 1.3, had ramifications far beyond the bank and its shareholders. This presents a peculiar dilemma: apparently, the bank as a firm looks like other industry companies – it is listed at stock exchanges, has private owners, runs marketing campaigns etc. – but its actions impact non-shareholding stakeholders to an extent much larger than a regular product company is capable of.
6 Capital-at-work is not to be confused with working capital. It is comprised of the sum of deposits, equity, issued bonds and sub-ordinated loan capital.
26 These observations are supported by the findings of Ahn and Choi (2009), who observe that banks are “special” economic units due to their distinctive roles in financial intermediation, in the payment system and in liquidity, etc. The banks’ own interest organization in Denmark supports this view and it expresses this in the following way: “The banks are a part of daily life in Denmark. The banks’ role is to channel money to the right places for citizens, the businesses and for governmental institutions […]The banks are a part of the Danish national economy and they hold a great importance for the development of the economy.”(Finansrådet 2010) (translated). Thus, the banks themselves acknowledge that their role is to serve their stakeholders at large and this view will not be contended further. This does not mean, of course, that banks do not run for profit and for maximization of shareholder wealth, but it justifies the existence of a supervisory authority to oversee that the banks do not take risks that endanger the economic health of the society as a whole because of their special status as a financial institution.
3.3 The stakeholders As the bank fulfills a role larger than that of the ordinary corporation and thereby affects its stakeholders to a greater extent and whose stakeholders on the other hand (through legislation, regulation etc.) impact the bank’s actions, it is deemed imperative to outline the bank’s and the stakeholders’ interrelation. The bank is seen as having five groups of stakeholders. Throughout the thesis, these will be the angles from which to consider the bank’s actions and the findings of the research. Surely, more groups could be included and considered, but the five groups represent the full environment the banks operate in, each of them containing subgroups of stakeholders. The thesis is considered relevant for all five stakeholder groups and the implications of the research (see sections 10.1-10.9) will address the five stakeholder groups’ views separately when necessary.
3.3.1 The owners The bank’s owners are its shareholders or owners who own different types of stakes in the bank. Some banks are primarily owned by foundations, some are listed at the Copenhagen OMXC stock exchanges, some are incorporated but not traded etc. The owners will be addressed “the shareholders” in general as previously mentioned, because the main body of literature on ownership and specifically on ownership in banks assumes incorporation. The
27 main focus of the thesis is on incentives and they do not differ considerably from shareholder to foundation owner – the execution and engagement in the ownership do differ, but it is the incentive structure that is primarily researched and analyzed upon, unless otherwise specifically stated.
3.3.2 The debtholders The bank’s debtholders are primarily its depositors, secondarily its institutional lenders. The depositors are insured by the Deposit Insurance Fund 7, which means deposits in almost the entire research period were guaranteed up to DKK 300,000 – in the last days of 2008 depositors enjoyed unlimited deposit insurance. (Financial Business Act 2003). The dynamics and hazards of deposit insurance are evaluated in section 4.5, but as stakeholders, the depositors are rather passive if they hold deposits smaller than the deposit insurance guarantee, because their deposit is guaranteed and is not dependent on the bank’s risk-taking. In the paper, the terms “depositors” and “debtholders” are used interchangeably although it is recognized that they are, in fact, not completely identical 8.
3.3.3 The management The term “the management” is directed at the top management of the bank, but it essentially covers all individuals deriving the main part of their human capital investment from being employed at the banks. Since it is assumed that the executive management employs its own incentive system inside the bank (through management style, pay programs etc.) and it thus has every opportunity to align “their” corporation with their incentives, only the management that answers to the board is considered in the thesis unless otherwise stated. To be clear, the terms “the management”, “the CEO”, “the executive management” and similar expressions all refer to those inside the banks who are employed by the board of directors.
3.3.4 The board of directors The board of directors is hired by the shareholders, elected at the general assembly of the bank. In some banks, the board of directors is not elected directly at the general assembly, but instead, a board of representatives is elected which in turn elects the board of directors. In any case, the general assembly is the institution that the board of directors directly or indirectly answers to(Erhvervs- og Økonomi Ministeriet 2009).
7 In Danish “ Indskydergarantifonden” . 8 The incentive conflict between depositors, insurer and shareholders is the one considered in the main body of the banking agency literature and also in this thesis.
28 3.3.5 The society Society as a whole is a stakeholder in the bank. The society includes the economic environment, the political environment, the social environment, the customers and trading partners of the bank as well as all parties that are affected in some way or another by the bank’s actions, but who are not officially a part of the bank’s governance system.
3.4 Risk 9 In order to measure risk and risk-taking in the banking industry, as set forth in the research question of this thesis, an outline of banking risk must be undertaken. Later, in section 7.7, the specific choice of risk measure is explained; this part covers banking risk as a phenomenon only. Generally, banking risk falls in two categories: credit risk and mismatching (London External 2009).
3.4.1 Credit risk Credit risk is the risk that the counterparty to the transaction the bank has engaged in does not fulfill his duties. In plain terms, credit risk is the risk that loans will not be paid back in due time. Proper credit risk management consists of three principles: selection of the borrower, limitation in loan-giving, meaning to differentiate the loan amount and terms based on the creditworthiness of the customer and finally diversification in terms of borrower types so that the bank is less exposed to specific, local economic contractions (ibid). A related phenomenon observed in the financial crisis in Denmark is the operational stress that heavy growth in loans puts on proper credit assessment; it is argued in the wake of several bank failures that the credit management did not adhere to the three credit management principles, witnessed by e.g. Roskilde Bank’s 45 % exposure to the real-estate market. Furthermore, there are strong indicators that the limitation principle was not adhered to as many (and large) loans were given without collateral and as expedite cases which, ceteris paribus increases operational risk and, subsequently, credit risk (Skipper-Pedersen, Stenbjerre 2008, Venderby 2007).
9 “Risk in banking” is a topic worth a thesis on its own; due to limitations in scale and scope of this thesis, the paragraph on risk will neither venture into a detailed, technical analysis of the different definitions, mechanisms and applications of risk, nor will it seek to investigate the risk management instruments of the banking industry (VaR comes to mind). This paragraph primarily serves as a toolbox to provide the reader with a basic understanding of the risk financial intermediaries are exposed to in their business environment as well as to provide reasoning for this thesis’ choice of risk-taking behavior measurement in section 7.7.
29 3.4.2 Mismatching The bank’s balance sheet is somewhat different from other companies’: on its asset side are its outstanding loans and investment activities, on its liabilities side are deposits from depositors, which can be regular checking accounts connected to the customers’ salary payment accounts, as well as loans taken out from other banks and finally, its equity. A bank’s balance sheet is inherently mismatched; loans usually have long maturities while deposits and interbank funding usually have shorter maturities. The discrepancy in time to maturity is more specifically defined as a bank’s ability to “settle obligations with immediacy” (Drehmann, Nikolaou 2009) and is termed funding liquidity risk (ibid).
3.4.3 Funding liquidity risk This creates a need for outside funding, for example if an unusual amount of depositors want to withdraw money at the same time – loans are not especially liquid, but many deposits can be withdrawn without notice. Naturally, a bank with many deposits and few loans will not experience a need for intermediary funding, unless in a bank run. However, the larger the loans compared to the size of deposits, the greater the need for the bank to obtain loans itself to cover its own investment (the loans given), which is obtained from a wholesale funding provider. If the bank cannot obtain funding in the interbank market, through alternative sources or through raising capital, its existing capital and, subsequently its solvency, is threatened, because it will not be able to “settle obligations with immediacy” (ibid). The reasons for not being able to obtain funding can be name-specific (the individual bank cannot obtain funding) or systemic (no banks can obtain funding) (London External 2009)– the name-specific reasons can be that of the bank’s loan portfolio’s quality, the systemic reasons can be that of insecurity about common traits of all banks’ portfolios (Bechmann, Raaballe 2008) .
3.5 Regulation and risk-monitoring As the bank’s business model entails risk-taking to some extent and because this risk-taking, as explained in previous paragraphs, can affect large groups of the population, the industry’s risk-taking is regulated by the Danish Financial Supervisory Authority (DFSA)10 , acting in accordance with the Basel (I and subsequently II) requirements, which all banks must adhere
10 In Danish “ Finanstilsynet ”.
30 to in Denmark 11 . Moreover, the regulators (DFSA) will also monitor a bank’s risk choice because they have the responsibility to maintain a stable financial system (Merton 1977a). However, because the banks are regulated, it has been suggested that no need exists for bank- specific soft law in the form of banking governance codes. Therefore, banks are encouraged to follow the general corporate governance recommendations as set forth by the so-called Nørby committee in 2001 (revised numerous times since).(The Danish Commerce and Companies Agency 2005)
3.6 Partial conclusion It was found that the banking industry in Denmark comprises 133 banks, but is rather concentrated. It was argued that banks strive to maximize profits and shareholder wealth, but that they also serve a role as financial intermediaries. The five stakeholder groups were identified as the owners, the debtholders, the management, the board of directors and the society. Risk in banking was found to stem from two main sources; credit risk and funding liquidity risk. These risks to the financial institution were outlined as being overseen by the DFSA.
11 The specific requirements of the Basel accords (2006) can be found here: http://www.bis.org/publ/bcbsca.htm
31 4 THEORY
In this part, the general governance field as employed in this thesis is outlined. The section aims to thoroughly investigate the theoretical foundations in the field to be able to properly analyze incentive conflicts in the bank’s ownership and governance structure. The reason for undertaking a rather comprehensive examination of the foundational literature of the field is two-pronged: primarily, the underlying incentive structures in the corporation, which rationalize the existence of having a board of directors, are crucial. Secondarily, without a fundamental understanding of the incentive drivers, the central hypotheses for the thesis would be impossible to construct properly. First, corporate governance is defined and the development of the field is explored. Then, agency theory as a corporate governance framework is thoroughly examined. The relation between relevant elements of agency theory and financial theory is subsequently highlighted through the incentive conflicts found in the existence of deposit insurance. Finally, the risk preferences of the individual bank stakeholders are outlined, which serves two purposes: it sums up the theoretical part and it lays the foundation for undertaking hypothesis building and –testing in the rest of the paper.
4.1 Corporate Governance As reasoned in the introductory section, the angle chosen to shed light on the subject of ownership structures and risk-taking in Danish banks is that of the corporate governance research field. In order to be able to draw upon this field’s central theories and assumptions, a theory review of key elements from the field is undertaken. Corporate governance is concerned with the systems in which businesses are governed. That is, corporate governance does not concern itself with the actual management of the firm, but rather the frames in which management takes place (Thomsen 2008, Solomon 2004, Solomon 2004) Research on the governance mechanisms of organizations dates back in the literature from Adam Smith’s (1776) cornerstone writings in “The Wealth of Nations” :
“The directors of such [joint-stock] companies, however, being the managers rather of other people’s money than of their own, it cannot well be expected, that they should watch over it with the same anxious vigilance with which the partners in a private copartnery frequently watch over their own. Like the stewards of a rich man, they are apt to consider attention to small matters as not for their master’s honour, and very
32 easily give themselves a dispensation from having it. Negligence and profusion, therefore, must always prevail, more or less, in the management of the affairs of such a company”
Adam Smith’s thinking predates numerous later scholars’ thinking on the incentives in the inter-personal and inter-organizational relations.
4.2 Transaction Cost Economics No seminal pieces – to the best of this thesis’ authors’ knowledge – manage to further conceptualize governance ideas until the 1930s. After Berle and Means (1932) touch upon the separation of ownership and control, Coase (1937) publishes the “The Nature of the Firm”, in which the trade-off between internalization and market transactions is described. In particular, Coase describes the cost of controlling and monitoring a large network of internal contracts as the factor determining when to source goods, services or managerial efforts in the market instead of owning these within the firm. This lays the foundation for transaction cost economics, which is later developed by several scholars, most notably by Williamson in several works (e.g. ( Williamson 1981, Williamson 1985, Williamson 1996, Williamson 2007). Beginning with Williamson’s (1981) article, transaction cost economics scrutinizes the individual’s incentives and possible course of actions through the concepts of opportunism and bounded rationality (ibid). Opportunism applies to the individual’s self-interested actions which do not benefit the company. Bounded rationality as a term seeks to describe how the notion of rational economic players is restricted by lack of complete information, cognitive limitations and time constraints on the part of the individual. Relating back to Smith’s claim that “negligence and profusion […] must always prevail”, Coase’s (1937) notion of the cost of internalization and Williamson’s further work on (among other subjects) opportunism and bounded rationality provide insights into the costs associated with separation of ownership and control. In other words, the transaction cost research field lends important themes to the corporate governance area, because the remedy to these dilemmas is implied to be found in the organization of the firm.
4.3 Agency theory Another perspective on the inter-personal and inter-organizational conflicts of interest is that of agency theory. In modern corporate governance literature, agency theory and associated agency costs provide the theoretical foundation for describing most governance issues related
33 to human capital and its deployment (Thomsen 2008). This thesis adheres to this assumption and uses agency theory as a theoretical foundation. Therefore, a thorough outline of the basic tenets of the agency theory and its extensions is given in the following. Although several scholars acknowledge that it may be hard to distinguish transaction cost economics’ issues from those of agency theory (Williamson 1996, Gilson, Mnookin 1985), it is noted that agency theory uses as its unit of analysis the individual, whereas transaction cost economics analyzes the transaction itself (Solomon 2004, Williamson 1996). As this thesis is ultimately concerned with the incentives and actions of the individual, more specifically the board member, agency theory takes the predominant position as a theoretical foundation for this thesis.
4.3.1 Fundamental agency theory Following Ross’ (1973) first description of the principal-agent relation, Jensen and Meckling (1976) build the first theoretical exposition on the agency problem. Agency theory seeks to explain the incentive issues arising with the separation of ownership and control, or using Fama and Jensen’s (1983b) more precise term; the separation of decision control and decision management where important decision agents do not bear substantial share of the wealth effects of their decisions. The literature on agency theory concerns itself with the principal (the owner/decision controller) and the agent (the decision manager), who face an available surplus (from the interaction), who have a conflict of interests and who have an information asymmetry between them (Hendrickse 2003). The agent acts on behalf of the principal and the agent is assumed to have the information advantage. The principal, on the other hand, is assumed to be the claimant to the surplus generated in the interaction, lest the amount of compensation agreed a priori between the parties. A classic and simple example of the principal-agent problem is that of the doctor-patient: the doctor (the agent) has the information needed to treat the patient (the principal) who is willing to pay for the doctor’s services (surplus to be generated if the offered sum is higher than the doctor’s reservation price). The patient is unable to control the doctor’s efforts, as their relationship is informatively asymmetrical.(Culyer,Newhouse 2000).
4.3.2 The extended agency problem In modern, large corporations, the agency problem is vastly more complex. The extended agency problem as a term refers to the multitude of agency problems found in firms with shareholders, a board of directors and with several layers of management (Thomsen 2008). In
34 practice, complexity is attained by the introduction of limited liability ownership and the opening of corporate ownership to the public 12 (Solomon 2004). In public listed companies, the shareholders are the owners. Unable and unwilling to run the business on a daily basis, shareholders elect a board of directors to oversee and control the company’s operations. The board in turn hires the executive management, who should ultimately be acting on behalf of the company’s owners; the shareholders. The board is thus agents to their principals, the shareholders, and the board also serves as principals to the executive management, who in turn are agents to the board and to the shareholders (Hendrickse 2003). The board of directors is carefully examined in section 4.8. The various agency problems come with agency costs , defined as the costs of structuring, monitoring and bonding a set of contracts among agents with conflicting interests (Fama, Jensen 1983b), and as the cost of aligning the agent’s incentives with those of the principal’s (Jensen, Meckling 1976, Stiglitz 1989) .
4.3.3 Contracts The firm as a whole can generally be seen as a nexus of contracts (Jensen, Meckling 1976), which – among other purposes – serve to mitigate the outlined agency problems by specifying which tasks are transferred to agents and at which compensation (Fama, Jensen 1983b). The existence of asymmetrical information is one of the characteristics of an agency problem (Hendrickse 2003, Mankiw 2008). In the decision process when hiring and controlling an agent, information asymmetry can arise at two separate stages: before signing the contract and/or after signing the contract (Thomsen 2008). When a contract is entered into by a principal and an agent, the contract should ideally be complete contingent, meaning the agent’s effort and the outcome of this is known and can be observed and verified by everyone. In most cases, when entering into a contract some characteristics are not observable to everyone, but the outcome of them is; for example, a manager’s skill set might not be observable to the principal at the time of signing the contract, but the outcome of his actions can be. As an example, the owner (the principal) may know that a future manager is financially educated, but not if he is a hard-working manager who deploys his financial knowledge to his work efforts. Such a situation forms the basis for a complete contract, which then entails ex-ante informational asymmetry.
12 This view is derived from the “Fisherian Separation Principle”, which is the notion that capital markets are the reason separation of control and management exists at all.
35 If the outcome depends on other circumstances and skills than the ones contracted for with the agent, the contract is incomplete , reflecting informational asymmetry ex-ante as well as ex- post, because now the full characteristics as well as the outcome are unknown to some degree. This means that the outcome obtained from the agent’s efforts might be a result of all other things than the characteristics the agent was hired on and the effort he chose to put into the work. (Fama, Jensen 1983b, Hendrickse 2003, Mallin 2010).
A good example of employment contracts that in hindsight clearly should have been characterized as “incomplete” is the many publically lauded investment managers in the years leading to 2008: they were thought of as being hard-working financial wizards, whose dedicated efforts resulted in incredible returns on the portfolios they managed. In return, they negotiated astronomical salaries and incentive plans for themselves. It turned out, however, that when markets stalled, so did their funds: most of the upside could be ascribed to business cycle effects and to un-diversified risk-taking.
4.3.4 Ex-ante information asymmetry – hidden characteristics The possible informational asymmetry before a principal contracts with an agent is labeled a hidden characteristics problem. The principal can observe whether the agent accepts the contract drafted by the principal, but not his motivation to do so. The principal may use methods to infer certain things about the agent’s characteristics (education, past results, hobbies and so forth), but cannot always exactly determine the qualities of the agent (Thomsen 2008, Solomon 2004). Several applications of the hidden characteristics problem are found in the extended agency problem (see section 4.3.2). When the shareholders elect a board, they want to be sure the individual director has the qualities needed to govern the corporation effectively on their behalf. They cannot, however, completely know all the details of the prospective director’s qualities and his motivation for running for the election. Informational asymmetry therefore exists ex-ante. In the extended agency problem, the elected board members face the same obstacles when hiring top management, who in turn will have to hire middle management; thus, the hidden characteristics problem is one of (possible) importance in all principal-agent relations throughout the corporation’s control chain. (Hendrickse 2003, Mallin 2010)
36 4.3.5 Ex-post information asymmetry – moral hazard The result of ex-post information asymmetry is regularly characterized as “moral hazard” – the agent, knowing that the principal cannot fully observe her effort, but only the outcome of the combined effort and other circumstances, chooses to deliver an effort that does not (necessarily) maximize the owner’s value(Hendrickse 2003). Holmström (1979) describes this as “[…] moral hazard may arise when individuals engage in risk sharing under conditions such that their privately taken actions affect the probability distribution of the outcome” and may be the result of the agent’s attempt to benefit from the principal’s inferior information set (Beaver 1989).
4.4 Types of agency problems As previously described, agency problems are ubiquitous and the term ‘agency problem’ can be applied to a multitude of different interactions between individuals, groups, businesses and so forth. In order to characterize the agency problems found in the organization of firms, scholars have grouped different types of agency problems to enhance the application of agency theory as an analytical framework (Thomsen 2008, Encyclopedia for Business 2010). As a result, three main groupings have been identified:
4.4.1 Type 1: Owner vs. manager These agency problems are those that relate to the separation of ownership and management of the company. To understand the dynamics of this relation, the relation itself should be outlined. The owners (the principal) in many companies do not themselves manage their company (Denis 2001, John, Senbet 1998). This can be associated with the nature of the ownership structure in a particular company; an owner can be an institutional investor, a large number of individuals holding the company’s stock, a fund etc. Instead, owners hire a manager (the agent) to run the company on a daily basis (Thomsen 2008). In the agency theory literature, the main assumptions are that the principal is risk-neutral while the agent is risk-averse (Demsetz, Saidenberg et al. 1997)and that the owner wants the agent to maximize his efforts, while the agent’s incentive is to minimize them 13 . The mechanics of this contradiction is found in the fact that the agent is administering the business risk in the firm on behalf of the principal and is also found in the circumstance that the agent is assumed to derive most of his income from his salary package in that business, while the principal has the opportunity to diversify his portfolio risk. Contract design and enforcement
13 Provided that it is more costly on the agent’s own resources to work than not to work.
37 are assumed crucial to mitigate these conflicts of interests (Hendrickse 2003). Supporting this, John & John (1993) conclude that the CEO desires to enjoy benefits of control in solvent state 14 and that such incentives result in management being too conservative when deciding on projects because he, the manager, cannot diversify his investment15 . They also conclude that the only way to mitigate such incentive conflicts is to align the CEOs interests with that of the shareholders – more on this in section 5.2.2. Contracting costs together with monitoring costs are thus assumed to constitute the agency costs of the type-1 agency problem (Hendrickse 2003, Fama, Jensen 1983a)
4.4.2 Type 2: Minority vs. Majority investors In a company with more than a single owner, the presence of a majority owner will make this majority owner – who is assumed to have a majority vote when accepting or declining the projects undertaken by the firm – acts as an agent on behalf of the minority owners (Thomsen 2008).
4.4.3 Type 3: Shareholders vs. Stakeholders A type 3-agency problem concerns the extraction of wealth from either group by the other’s action. A common problem is the relationship between creditors and shareholders of a company: the creditors, having limited upside potential from their investment in the company are not interested in risk on the company’s assets. The shareholders, on the other hand, facing limited liability and unlimited upside potential, have an incentive to increase risk on the firm’s assets 16 (Demsetz, Saidenberg et al. 1997). In the banking industry, this effect can be particularly evident: most creditors do not exercise discipline on the shareholders, because the latter’s risk-seeking motives cannot erode the creditor’s wealth due to the presence of deposit insurance. Therefore, special attention is given to this phenomenon in the following:
4.5 Deposit insurance Equity – the shareholders’ shares - can be viewed as a call option on the firm’s assets (John, Senbet 1998, Copeland, Weston et al. 2005, Brealey, Myers et al. 2008), with debtholders being the holders of the firm’s assets until the value of these exceeds the value of the debt. To
14 “Solvent state” describes all scenarios in which the business is not bankrupt and is still a going concern. 15 “Investment” means the manager’s own, human capital – it cannot be diversified due to obvious constraints of time, space etc. 16 The shareholder is as previously described risk-neutral in nature, due to the possibility of diversification, but limited liability motivates relatively risk-seeking behavior.
38 elaborate: if the value of the assets does not exceed the value of the debt, the shareholders do not get any pay-off (in reality, the stock market will value the stocks lower, going towards zero as a declining function of the probability of asset value exceeding debt value). The exercise price on the call is therefore equal to the point where the value of the assets equals the value of the debt.
Figure 4.1 Graphical depiction of the call option on equity
Equity value
Assets = Debt
Asset value The call option is of no value to the shareholder The call option is in in-the-money Source: own contribution
As depicted above, equity holders whose pay-off is zero until the assets’ net worth exceeds zero, generally prefer larger amounts of volatility than the debt-holders: their certainty equivalent 17 of the credit given to the bank decreases with increases in risk, as the distance to default decreases (Crosbie, Bohn 2003). All unexpected upside gains befall on the equity-holders (or the option holders at maturity, to stay in the option theory linguistics) (Jorion 2007). Galai and Masulis (1976) also find that shareholders effectively hold a call option on the firm’s value with the exercise price of the total amount of debt outstanding. If the interest rate is not properly priced to reflect this risk - which is more likely to be the case for banks due to deposit insurance and regulatory rescue - then the bank’s shareholders have an incentive to gain from this call option by increasing the bank’s asset risk. This type-3 agency problem is acknowledged in the literature: John and Senbet (1998) terms this phenomenon ‘debt agency’, while remarking that the cost of debt should reflect the firm’s overall riskiness. However, as transactions do not happen
17 The “certainty equivalent” is the amount debtholders would be willing to accept at maturity if credit risk was eliminated. If the banks increase the risk on their assets, then without deposit insurance, the debt would be worth less and the risk-free amount debtholders would accept in return for the loan, they have given the bank, would be smaller.
39 simultaneously (banks obtain loans at different points in time than when they choose their risk-level on their investments) and because of the inherent problems with forming complete, contingent contracts (debtholders cannot fully appreciate the risk that the bank might take), the disciplining role of rising costs of debt-financing may happen after the loan to the bank has been given and thus not be optimally efficient (Dewatripont, Tirole 1994).
Galai and Masulis (1976), Jensen and Meckling (1976) and John et. al (1991) all find that as in any corporate firm, due to the moral hazard problem and with the limited liability and with the associated convex pay-off (as seen in the model above), the shareholders have preference for excessive risk. This notion of risk-seeking behavior on the shareholders’ part is thus shared by many corporate governance and many corporate finance researchers.
John et al. (1991) find that with deposit insurance, bank shareholders enjoy a subsidy which increases in value with leverage and bank risk. As previously stated, this paradox is exacerbated in the banking industry because debtholders do not exercise a monitoring function on the shareholders’ risk-taking. Thus, bank shareholders have even stronger incentives for excessively risky investments that potentially benefit themselves at the expense of the deposit insurance fund and the taxpayers who back it (John, John et al. 1991). This is not because the deposit insurance covers the shareholders, but because the deposit insurance – which effectively insures a large chunk of the bank’s debt – work like a put option for the debtholders: Merton (1977b) uses the Black-Scholes model to demonstrate this and finds that bank debtholders’ claim on the insurer or guarantor can be thought of as holding a put option on the value of banks’ asset with an exercise price of depositors’ claims. This is illustrated in the following model
40 Figure 4.2: Graphical depiction of the debtholder’s put option
Value of put option
Assets = Debt
Asset value The put option is in-the-money The put option holds no value to the debtholder and becomes an insurance in the event in the case of financial distress or bankruptcy, as of financial distress and bankruptcy the debtholder’s claim is covered by the assets Source: Own contribution
When the value of the bank’s assets decreases, the debtholders’ claim would normally decrease in value as well, had the bank been a ‘normal’ corporation. However, because the debt in most cases is in fact a deposit, it is insured. Therefore, if the assets decrease in value, the deposit does not – the depositors are still certain to get their loan to bank returned. This is equivalent to holding a put option on the bank’s assets, a put option in reality issued by society.
4.6 Risk and risk preferences To illustrate and summarize the risk preferences of the various stakeholders to the bank’s activities, a review supported by a graphical depiction is undertaken:
Figure 4.3: Graphical depiction of the risk preferences of the 5 stakeholder
RISK PREFERENCES Risk
A B* D
B C
Risk preference Solvent state Financial distress/ Bankruptcy
Source: own contribution
41 The five classes of stakeholders outlined in section 3.3 are: the owners of the bank (the shareholders), the board of directors, the management of the bank, the bank’s debtholders and the regulatory environment (the society). Adhering to the agency theory framework outlined above in section 4.3, these five different classes of stakeholders theoretically have different risk preferences.
4.6.1 The shareholders The shareholders of the bank hold a call option on the assets of the bank and are, all other things equal, interested in increased volatility and thus, risk on the bank’s assets. However, in the state of bankruptcy, the option is worthless and the possibility for abnormal upside gains is equal to zero. Thus, even though shareholders are assumed to prefer higher levels of risk, there is an upper limit in absolute terms to the level preferred. The shareholders’ risk preference is assumed to be depicted by the point A in figure 4.3. At this point, risk is close to maximized in a solvent state, i.e. before the bank enters financial distress, in which situation the pay-off to shareholders start decreasing before finally disappearing in the bankrupt state. The shareholders’ risk preferences conflict with those of the manager’s, with the debtholders’ and with the society’s.
4.6.2 The board of directors The board of directors is hired by the shareholders to represent their interests and to control the company in lieu of them. The board of directors is assumed to be aligned with shareholders and thus have a risk preference similar to those in point A. This is seen in a purely agency theoretical sense in which the agency relation between shareholders and the board is not considered, but only the ‘owner-manager’ relation is. This is not to exclude the possibility of a plethora of other conflicting incentives that may distort the board’s combined preference, but the view that the board is relatively risk-seeking compared to the manager is followed, as it is – by far – the most acknowledged in the general corporate governance research field. The board’s risk preferences (if completely aligned with shareholders) should conflict with those of the manager, with those of the debtholders and with the society’s.
4.6.3 The management The management is hired by the board, but derives most of its wealth from the bank and cannot diversify its human capital investment. Therefore, the bank manager is assumed to be
42 risk-averse (see section 4.4.1) which is at odds with shareholders and the board, but if management is behaving in a risk-averse manner, then management is aligned with debtholders and the society 18 . The management’s risk preference is depicted by point B in the figure 4.3. Alternatively, if the incentive mechanisms of the management are better explained by the theories outlined below in section 4.7 Alternative CEO risk preferences, the risk preference of the top manager may be depicted by the interval B*. It should be noted that the agency perspective in section 4.4.1, as represented by point B in figure 4.3 is the management incentive used to build and test hypotheses in the following parts of the paper, though.
4.6.4 The debtholders The debtholders have limited upside gain and are not interested in much risk on the bank’s assets. Their incentives conflict with those of the shareholders and the board of directors, but they are aligned with the management’s and the society’s. Debtholders’ perceived risk preference in accordance with agency theory is depicted by point C in figure 4.3. Debtholders face incentive conflicts with the shareholders – the type-3 agency problem – and with the board of directors, but not with management nor with the society. However, since the surrounding society insures the deposits in the bank – the bank’s debt – debtholders have little incentive to monitor the bank’s risk and under deposit insurance, debtholders are indifferent to the bank’s risk, in which case point C is not relevant.
4.6.5 The society The surrounding society is mainly interested in smooth, efficient operation of the banks. On one hand, the society is interested in efficient allocation of capital in the society through the banks in their role as financial intermediaries. Therefore, the society at large is not overtly risk-averse on the banks’ behalf. However, two effects limit the risk the society prefers that the banks take: first, if the banks enter financial distress, the possible contagion effects and the general forecasting uncertainty for consumers and businesses may prove costly to the society. Second, if banks default on their debt to depositors, the society as represented by the
18 Insofar the risk-averse behavior does not exclude positive-NPV projects to a large extent, thereby foregoing potential tax payments. “The society” is understood as having the insurer’s function in relation to the depositors, i.e. the bank’s debt. By logic, a bank that does not take any risk is suboptimal – to the society, too – but the incentive conflict is deemed larger when evaluating the direct liability of the insurer, who prefers – ceteris paribus – not having to cover deposits over foregone tax payment from marginally better, but more risky, projects on the bank’s side.
43 Deposit Insurance Fund 3.3.2 The debtholders is liable to pay the bank’s debts. Therefore, the society prefers an intermediate level of risk taken by the banks, represented by point D. The society finds itself at odds with the bank managers, who are risk-averse, and with shareholders and the board, who prefer more risk. The society and debtholders are not at odds, although society may be liable to debtholders in the case of bankruptcy.
4.7 Alternative CEO risk preferences Although the thesis strictly adheres to the theoretical foundation of agency theory as a predictor of risk preferences for all economic actors involved, this paragraph will briefly present some alternative theories on the top manager’s risk preferences as they are found in the corporate governance literature. The reason for this is that other researchers have stumbled on the concept of the CEO being risk-averse and therefore, alternative risk preferences on his part have been suggested, implying economic irrationality (or bounded rationality) on the CEO’s part. It should be stressed that this paragraph is included to offer alternative interpretations on the findings in the data analysis part of this paper, not to distort the general assumption of risk-averseness on the CEO’s part: regardless of what the following alternative perspective suggests, the assumption of the thesis in the subsequent hypothesis building is that CEOs are risk averse, as described in section 4.4.1 and summarized in section 4.6.
4.7.1 Other models of CEO risk preferences The corporate governance and the management literature on the CEO offer a plethora of theories and empirical studies on her incentives and her actions. Fortunately, for the purpose of this study, only the main theories on actions by the CEO that can be characterized as risk- taking are needed 19 . Two related phenomena emerge as important when describing behavior that will lead to an increase in the bank’s risk profile: Overinvestment and empire building (Thomsen 2008). Overinvestment is characterized as the action of investing more of the company’s money into a specific type of projects that the manager would rationally do (ibid). For example, the fixation on real estate and the apparent urge to channel large sums of the banks’ available funds into project financing in this particular market can be characterized as overinvestment that increased the riskiness of the bank’s assets – even the annual reports of some banks from
19 Usually, the literature is concerned with actions by the CEO that extract wealth from shareholders in a traditional agency theory frame. This paragraph does not consider this perspective, but is only interested in the incentives the manager might have to act in a way that is risk-increasing.
44 2007, published in the beginning of 2008, still maintain that the real estate investments are sound, signaling significant over-commitment. Thus, CEOs who become fixated on one target may overinvest in a particular asset type and the increase in risk that follows in some cases ((Thomsen 2008, Solomon 2004)). Another, and plausibly larger, issue is empire building. Empire building is characterized by acquisitions (e.g. of companies), by taking on new prestigious projects, or by ventures into un-related diversifications – motivated not by rationally evaluated business opportunities, but by the CEO’s desire to lead a larger company. The reasons for doing so can stem from many sources, but reputation, prestige, celebrity have been noted in the corporate governance literature (Thomsen 2008, Solomon 2004, Byrd, Parrino et al. 1998). Bechmann and Raaballe (2009)specifically suggest that CEOs of Danish banks might be motivated by those types of social factors. There may be economics incentives for risky empire building, too: Murphy (1985) finds that CEO compensation is better explained by firm size than firm performance, indicating that a CEO, who intentionally (over-)grows the company he manages, may have very rational motives of doing so; higher pay. This also, ceteris paribus, leads to higher risk, because the growth strategy is not motivated by business opportunity, but by the CEO’s desire to manage a larger company (and in turn, receive a larger compensation package) (Byrd, Parrino et al. 1998). As stated in the beginning of this paragraph, the main assumption for the CEO’s risk preferences is that he is risk-averse compared to shareholders. His eventual risk-seeking behavior, inferred through overinvestment and empire building actions, is returned to in the discussion section of the thesis.
4.8 The board of directors The board of directors has been an unexplored entity in the thesis so far. However, as the paper at hand is ultimately focused on the board of directors, and its structure and composition, the attention is turned to the board of directors itself. The reasoning behind having a board in the first place is given by Huang (2006), who finds that when the ownership of a corporation is dispersed among many people, it becomes hard for the shareholders to control the management of the firm. That means, in other words, that the separation of ownership and control and the subsequent dispersion of owners through shareholding and –trading in the capital markets require a board of directors to represent the owners of the company.
45 4.8.1 The role of the board Following Fama and Jensen’s {{188 Fama, Eugene F. 1983/a;}} terminology (1983b), the board of directors in the Danish banks chosen in this study can be characterized as decision controllers, who ratify and monitor the top management’s actions. Other scholars use slightly different terminology; Adams and Ferreira {{218 Adams, R. 2003/a;}} conclude that the board serves two main functions, advising and monitoring top management(2003) in alignment with Raheja {{180 Raheja, Charu G. 2005/a;}}, who finds that the board’s tasks are to monitor the projects undertaken and to hire/fire the executive management (2005). The American Bar Association’s guidelines further support these scholars and recommend that the board oversee and monitor top management (Corporate Director's Guidebook 2001). The top management on the other hand initiates projects and, if ratified by the board, implements them and are thus the decision managers (Fama, Jensen 1983b). If the board fails to fulfill this role as an agent to the shareholders and the principal to the top management, in effect being a mediator of incentive conflicts between management and shareholders, it creates conditions that may lead to management overreaching and disregard for the legal and moral framework the firm operates in (Breeden 2003, Ide 2003). Fama and Jensen(1983a) find that the board of directors is the most important body of an organization’s internal governance system and Weisbach (1988) argues that the board is judged to be the first line of defense or, as Weisbach and Hermalin (2003) find, at least the second-best 20 efficient solution to the shareholders against incompetent management. If a company’s ownership structure requires a board, it will need a board that is equipped to properly oversee management and the company’s operations as a whole. The bank board is even more important as a governance mechanism than its non-bank counterparts because the directors’ fiduciary responsibilities extend beyond shareholders to depositors and regulators as well (Macey, O’Hara 2003). This argument is supported by BIS (2006) who require enhanced corporate governance for banking organizations, which is supported by the Basel-II (2006) who recognizes the role of the board of directors as an integral part of risk management.
For the remainder of the paper, it is the assumption that the board’s role is as outlined above: to verify and ratify the proposed projects from the top management and subsequently monitor
20 The best defense being the owners managing the company themselves
46 these. Another role of the board is to hire and fire the executive management as well (Thomsen 2008, Solomon 2004, John, Senbet 1998).
4.8.2 The Optimal Board Raheja (2005) argues that an optimal board design maximizes the probability that a majority of the board will vote against sub-optimal projects and instead recommend higher-NPV projects. Furthermore, Breeden (2003) argues that the board should be informed and in a position to exert its power. John and Senbet (1998) find that an optimal board – elusive as the ‘optimal’ or ‘good’ label may be – lowers the corporation’s financing costs. In the same study review, it is found that the board’s effectiveness in monitoring executive management is determined by its independence, size and composition (ibid), which is the underlying assumption for building the hypotheses in section 5 that the board and its performance may exhibit endogenous features that determine board performance. Adams and Mehran (2008) and Andres and Vallelado (2008) show evidence that bank board structure is relevant to bank performance and thus support the focus of this thesis: bank boards and their structure and composition.
Thus, it also is the assumption of this paper that the board, in order to fulfill the duties as described above, should be carefully elected and structured so as to approach an ‘optimal’ composition. Raheja finds, however, that “very little theory provides insights into the effects of different board structures on firm value” (Raheja 2005), a view which other scholars agree with, e.g. Denis (2001) in her survey of the central fields of corporate governance research. Finally, the research leading to this thesis also agrees that board composition and structure, essentially the human capital put into boards, is in many research cases taken as a given constant, not as a research object in itself, which is supported by other literature in the relevant research field – see for example (Hall, Keane et al. 2005, Linck, Netter et al. 2008, Abdullah 2006). John and Senbet (1998) share this perspective too and argue that research into the field mainly take the structure of boards as given. As a result, this paper summarizes different recommendations to the board director’s characteristics (professional as well as personal) and to the structure of the board to testable hypotheses from different sources as referenced above and below. Many – nearly all - of the recommendations or inferences refer to board structure in a general corporate governance setting: the existing literature on corporate governance and the incentive economics it
47 concerns itself with offer few, if any, specific theories on how bank boards should be structured. Those recommendations official to Denmark, as put forth by The Danish Commerce and Companies Agency through the Nørby committee, have taken priority as well (The Danish Commerce and Companies Agency 2005).
4.9 Partial conclusion This section of the thesis has laid out the theoretical foundation for the research on Danish bank boards. First, corporate governance was defined as the systems with which corporations are governed; the development of incentive theories from Adam Smith over transaction cost economics to agency theory was outlined. Agency theory was described as being concerned with the incentives between a risk-neutral principal and a risk-averse agent. The extended agency problem was outlined and the associated agency costs were defined. Three main types of agency problems; the owner-manager problem (type 1), the minority-majority owner problem (type 2) and the possible extraction of wealth of owners from debtholders (type 3) were described. The type-3 problem was expanded with an in-depth presentation of the phenomenon and the dynamics of deposit insurance. The outlined incentive structures were applied to each stakeholder group’s predicted risk- preferences, followed by a paragraph suggestion alternative preference of the top management. Finally, the board’s role in the corporation was thoroughly outlined.
48 5 HYPOTHESES
The purpose of the following section is to build testable hypotheses in order to frame the investigation of risk-taking behavior in Danish bank boards as proposed in the research question. First, the testable parameters are determined. Each hypothesis is built from existing theory 21 , from empirical research and the existing recommendations. Subsequently, relevant existing theory (insofar such exists), the empirical research and finally, the official both national and international recommendations (if applicable) are summarized in testable hypotheses. The hypotheses are built with the two levels set forth in the research question: the first six relate to the composition of the board and are therefore related to the characteristics of the individual board director, the latter four relate to the structure of the board and are therefore focused at the board level as a whole.
5.1 Determining the testable parameters The sources for finding variables to test in the thesis are plentiful: previous research in the field, the public debate following the onset of the financial crisis (some of which is outlined in the motivation) and from the soft law governing the field (Danish as well as international recommendations), as explained and argued for in section 4.8 right above this section’s beginning. It is acknowledged that the list of testable variables is not exhaustive, as other researchers may choose to deploy different parameters than the ones used for the thesis at hand. However, the following ten hypotheses are built on those parameters judged most prevalent at the time of writing. It should be recalled that the method used is in principle deductive. The parameters chosen are not arbitrary, but the choice of parameters is not argued for at length in each case. Rather, the hypotheses are discussed and explained and the choice of parameters is subsequently justified by the fact that they do prove to be testable and, in most models, lead to significant results.
5.2 Individual level The following six hypotheses relate to board composition as they are built on the individual director’s characteristics and thus hypothesize on the first part of the research question.
21 Not all hypotheses can be backed by established theory, but will be backed by the empirical research in the relevant field.
49 5.2.1 Independence The corporate governance literature distinguishes between dependent and independent directors. An independent director is defined as a “non-management director free of any family, material business or professional relationship (other than stock ownership and the directorship (the board directorship, ed.) ) with the corporation or its management . (Corporate Director's Guidebook 2001). The literature on whether independence improves efficiency in monitoring management and consequently protecting shareholders’ claims to the company’s residuals is somewhat mixed. In the 80s, it was widely assumed in research on board independence that the board is more efficient in ensuring shareholders’ rights when board directors, or the majority of these, are independent. Examples abound and Weisbach (1988) finds significant differences between inside and outside directors in their ability to monitor the CEO and finds that outside directors - who monitor and credibly exert their firing power towards poorly performing CEOs – create value for shareholders. (See also: (Baysinger, Butler 1985, Kosnik 1987, Hermalin, Weibach 1988)for research that supports these arguments). This view lasted until Fosberg (1989) finds that the degree of independent directors on the board does not affect the performance of the board to a measurable degree. John and Senbet (1998) offer explanations for this by suggesting that management might succeed in getting incompetent outside directors elected. Another suggestion is that management is not disciplined by boards at all, but by reputation and the managerial labor market (ibid). However, Cotter, Shivdasani and Zenner (1997) find that the more independent the board of directors, the more likely it is that the board of directors will act in the financial interest of the shareholders. Hermalin and Weisbach (2003) somewhat settles this in their study review and conclude, among other things, that boards with a greater number of independent directors lead the management team to take more actions in alignment with shareholder interests. In relation to the findings outlined above, it is assumed that dependent directors share the same risk-willingness as the management; simply, dependent directors derive (a significant part of their) personal income from the company or have other vested interests that might lead to a sub-optimal, subjective decision process when evaluating proposed projects. The case for dependent directors on the board (or “insiders”) is that these are assumed to have less of an informational asymmetry when evaluating projects proposed by the CEO (Huang 2006) and can be assumed to have lower monitoring costs due to their relation to the corporation. An insider on the board – who by default cannot be independent - can mitigate
50 the hidden action problem described in section 4.3.44.3.4 Ex-ante information asymmetry – hidden characteristics, as he is closer to the daily efforts taken by the top management. However, while dependent directors may experience less information asymmetry, they might find it hard to act upon their concerns with the decision implementation by the CEO (Huang 2006). It may be opportune for the dependent director to side with the CEO in spite of the latter proposing inferior projects or exhibiting acts of shirking (Hendrickse 2003) (see also section 4.3.5). Dahya (2005) studies firms that recently increased their board's independence and find that those boards are significantly more likely to replace the CEO after a record of poor firm performance, supporting the case that dependent board members are likely to experience internal conflicts of interests when holding a board directorship in an organization, from which they derive other interests (e.g. income). Furthermore, as described in section 4.8.1, the board’s role is to ratify projects. The ratification process entails evaluation of the project’s optimality in relation to the company and its risk. If dependent directors - whose incentives are ceteris paribus closer aligned with the top management’s than independent directors’ - ratify sub-optimal projects, their lesser monitoring costs and smaller informational asymmetry might not be offset by the cost of accepting an inferior project (Raheja 2005).
While independent directors may have higher monitoring and verification costs than the inside/dependent director, the knowledge the independent director brings to the corporation’s overall knowledge pool can be valuable (Carpenter, Westphal 1999) As mentioned in section 4.8.1, one role of the board is to advise management on the projects undertaken in the firm (Adams, Ferreira 2003). Independent directors are also more likely to fire an underperforming CEO (Dahya, McConnell 2005).
From a legislative perspective, these views are supported by the Sarbanes-Oxley Act of 2002 , which addresses the issue of board independence and can be viewed as the legal response to the blurring of interests discovered in the wake of the corporate scandals in the USA around the turn of the millennium. Sarbanes-Oxley establishes that a majority of board members must be independent. The Danish soft law recommendations are, though considerably longer in wording, alike and also recommend that the majority of directors be independent so as to ensure that special interests do not take precedence over the running of the company. (The Danish Commerce and Companies Agency 2005)
51
To arrive at a testable hypothesis regarding the risk-taking of independent directors, section 4.8.2 is revisited: if board members are elected to represent shareholder interests and the board members are assumed to be aligned with the interests of shareholders, the option theory on the equity held in the company suggests that board members, who are not otherwise immersed in the corporation, should prefer a higher level of risk as this ultimately will lead to the chance of a larger pay-off. Therefore, it is hypothesized that risk-taking in banks and the independence of board members exhibit a positive relationship:
Ho: There is no relationship between independence of board members and risk- taking in Danish banks H1: There is a positive relationship between the independence of board members and risk-taking in Danish banks.
5.2.2 Board experience Board experience, which in this paper is defined as the experience obtained on other boards before joining the board at the bank in question, has been researched relatively little when compared to other parameters of board or board member characteristics. This can be somewhat puzzling, as Westphal and Milton (2000) find that many boards in the US have appointed directors with expertise from other positions in the business landscape – prior experience from boards is consequently a common characteristic of directors on boards.
The research that exists in this subfield, however, is relatively one-sided. Kosnik (1987) argues that the experience of independent, non-executive directors is measured in terms of the directorship in “un-connected” companies, since they are more likely to draw on their wider experience and expertise in monitoring management and be better performing board members. This finding is inferred to support Gul and Leung (2004) who argue that the effectiveness of non-executive (independent) directors varies depending on their expertise in terms of their experience. The findings by Gul and Leung (2004) could apply to the number of simultaneously held board seats as well see section 5.2.4; the distinction in the research is not completely clear, but does not yield it invalid.
Sirmon et al. (2008) support the argument that prior board experience positions the director better to be effective in his judgments (ratification) and monitoring duties. Thus, they find that
52 prior board of director experience is especially important in relation to strategy formulation and in determining the aggressiveness of the firm’s strategies. Moreover, directors with prior board experience are expected to have strong(er) influencing skills and thus take prominent roles on the board. This is supported by Burell and Morgan (1979) , who argue that board members with prior board experience have greater prestige and power than do members without prior board membership 22 .
In the same thread of argumentation, seasoned board members can be argued to share their experience with other board members and top management in an effort to guide formulation of effective strategies (Business Roundtable 2005, Finkelstein, Hambrick 1996, Lorsch, MacIver 1989) The Danish Recommendations on Corporate Governance offer little argumentation other than the following citation: “The Committee recommends that the supreme governing body annually assess whether the skills and expertise of its members need to be updated” (DRCG 5.2.2) and other references to the importance of relevant knowledge are made (The Danish Commerce and Companies Agency 2005).
The synthesis of these arguments is the following hypothesis:
Ho: There is no relation between prior board experience of the individual member and risk-taking in Danish banks H2: There is a positive relation between prior board experience of the individual member and risk-taking in Danish banks.
5.2.3 Gender It is implicitly and explicitly assumed across the literature on the board’s role, its composition and its duties that knowledge reduces monitoring costs (see section 5.2.2 and 5.2.4). To ensure that the board has sufficiently broad knowledge to perform effective ratification and monitoring, some scholars argue that the board should be diverse enough to bring all relevant knowledge resources to the board. For example, some researchers suggest that diversity leads
22 The notion that experience leads to power, which leads to an important role on the board or in any group is, among many, studied by Pfeffer (1981), who argues that power can influence behavior, change the course of events, overcome resistance and get people to do things they otherwise would not.
53 to a greater knowledge base, creativity and innovation, and therefore becomes a competitive advantage (Watson, Kumar et al. 1993) On the other hand, larger groups seem to incur higher communication and coordination costs (see section 5.3.1). It is the bold suggestion at this point of the thesis’ hypothesis building, as the research on the topic is comparatively sparse (Krawiec, Broome 2008), that heterogeneity on the board of directors may have the same effect. Krawiec et al. (2008) conclude that first of all, the body of work on diversity on boards has significant gaps. Secondly, their research suggests that the signaling effect of having a diverse board, i.e. reflecting the stakeholders’ world, complying with corporate social responsibility norms and so forth may have beneficial effects. They find, however, that the distribution of costs and benefits of board diversity in “good” firms versus “bad” firms is unknown (ibid).
In the broader field of diversity research, Erhard et al. (2003) suggest that a general distinction exist when defining diversity; the observable (demographic) diversity and the non- observable (cognitive). Examples include:
Table 5.1 Diversity parameters DIVERSITY DEMOGRAPHIC COGNITIVE Gender Knowledge Age Education Race Values Ethnicity Perception Affection Personality Characteristics Source: Erhard et al. (2003)
While this thesis hypothesizes on some of these parameters separately, it should be noted that those hypotheses relate to the possible efficiency in the board role signaled by either having or not having a certain characteristic. This paragraph – and the subsequent hypothesis – focuses on the diversity itself as an endogenous factor (i.e. a board of only women is as un- diverse as a board of only men). In this thesis, “gender” is used as a proxy for diversity as it is an observable characteristic and it is an easily defined one in the data collection. Also, “gender” and specifically, equal rights, are common debate topics and therefore should be comparatively better researched than “diversity” is.
54 On the existence of female directors, previous research has concluded that women are (beginning to be) represented on company boards. For example, Catalyst (1995) reported that of the top 100 US companies in terms of revenue, 97 had at least one woman board member. In an earlier study by Catalyst(1993), 82 per cent of the 50 most valuable Fortune 500 firms were found to include at least one woman director on the board. Daily et al. (1999) conclude, for a study of Fortune 500 firms, that women have made significant progress in terms of assuming seats on boards of directors. Bilimoria (2000) reports that even though the number of female board members is increasing slightly, few companies actively recruit females and there is still sex bias, stereotyping and tokenism on boards where women serve. Mattis (2000) concludes that women board members are increasing in numbers but the changes are small and incremental. In terms of efficiency gains or losses from creating diverse management (in terms of gender representation), Hambrick et al. (1996) conducted a longitudinal study on the effects of diversity on top management team performance in 32 major US airlines. Diversity was measured by functional, educational and tenure heterogeneity. Their findings indicated that homogeneous top-management teams outperformed heterogeneous ones. They found that heterogeneous teams were slower in their actions and responses and less likely than homogenous teams to respond to competitors’ initiatives. They suggested that in a heterogeneous group individuals were more likely to disagree, thereby weakening the team consensus, which aligns with the analogy made earlier in this paragraphs about heterogeneity being comparable (in concept) to a larger board. It should be noted, though, that this study had management, not directors, as its study focus.
Regarding management teams Knight et al.(1999) also found that demographic diversity was negatively related to consensus. They further suggested that greater time and effort was necessary for heterogeneous teams to reach decisions, ultimately reducing team performance. This, too, relates to management and not boards, but is included here due to the lack of research on the board of directors in terms of efficiency vs. diversification.
On the other hand, other researchers have found positive performance effects from increased diversity. Shrader et al. (1997) examined firm financial performance with gender diversity at the middle- and upper-management level, and at the board of director levels for large firms. They found general organizational effects, but few top-level diversity effects on performance and, in general, reported a positive link between women (diversity) in management positions
55 with firm financial performance. Shrader et al. (1997) explain the positive performance relationship by suggesting that these companies were recruiting from a relatively larger talent pool, and subsequently recruited more qualified applicants regardless of gender. In a more recent study conducted by Richard (2000), the relationship between organization- wide diversity, business strategy and firm performance was examined in the context of the banking industry. Performance was measured by productivity return on equity, and market performance measured from 64 banks in three states. Study results showed that diversity added value and it was perceived as a relative competitive advantage for banks. In another recent work, Burke (2000) found significant correlation coefficients between the number of women directors and revenue, assets, number of employees and profit margins for Canadian firms. Therefore, the findings of the section above indicate that profitable firms may be amenable to diverse director appointments.
In summary, the research on the benefits/disadvantages of diversification point in opposite directions. It is noted that the causal relationships might be double-sided; perhaps diversity exists as a result of a good corporate culture and management performance or perhaps corporate culture and management performance are boosted as diversity increases. The Danish Recommendations on Corporate Governance do not offer any explicit recommendations on diversity nor on female representation.
The hypothesis tested leans on the body of research that suggests that diverse knowledge could increase monitoring efficiency and alignment with shareholders and, as described, it uses gender as a proxy for diversification. Keeping the basic assumptions of the risk incentives in mind, this thesis reaches the following hypothesis:
Ho: There is no relationship between the representation and share of women on the board of directors and risk-taking in Danish banks H3: There is a positive relationship between the representation and share of women on the board of directors and risk-taking in Danish banks
5.2.4 Multiple directorships Generally, two competing arguments exist when determining the effectiveness of a board member who holds multiple positions on other boards. Following Ferris, Jagannathan and Pritchard (2003) and subsequently Jiraporn et al.’s (2008) terminology, either a “reputation
56 hypothesis” or a “busyness hypothesis” hold when hypothesizing the effect of multiple directorships held by one board member. While the two streams of thought are characterized by Jiraporn et al., they build on multiple sources and these are sourced where appropriate (Ferris, Jagannathan et al. 2003, Jiraporn, Kim et al. 2008). The reputation hypothesis maintains that holding multiple director seats is an important signal and the hypothesis builds on arguments put forth by Fama (1980) (1980) and Fama and Jensen (1983b, 1980), who contend that the market for directorships works as an incentive for the individual director (with multiple seats) to develop good monitoring skills (ibid). Mace (1986) suggests that other directorships provide prestige, visibility and commercial contacts, thus hinting at the beneficial effects of having several directorships. It is found in other studies that the number of outside directorships has been used to represent the director’s reputation in the external labor market (Brown, Maloney 1999, Vafeas 1999). The reputation hypothesis’ view on holding many board seats thus suggests that individuals who hold multiple board seats are – allegedly – high-quality executives, whose skills and experience are superior. Hence, they are able to relatively effectively monitor and oversee management and they take (or ratify) less value-destructing decisions (Jiraporn, Kim et al. 2008). Furthermore, the study hypothesizes that members with multiple seats are ‘hard- working’ individuals interested in their reputation as a decision expert; it can be inferred that this mechanism becomes stronger as the number of board seats increases – should the hypothesis hold true, that is. Additionally, board members with many board seats are predicted to be placed on many boards because they are good at being a director. This is supported by the notion that the likelihood for outside directors to obtain additional board seats is related to the performance on the board in which they currently serve (Ferris, Jagannathan et al. 2003, Fich, Shivdasani 2006). These findings lead to the measurable hypothesis (of Jiraporn et al. (2008), not this paper) that they engage in less value-destroying behavior. This final part of the hypothesis is in alignment with Shivdasani (1993), who employs the average number of additional directorships as a measure of director quality and find a negative association with agency problems.
The reputation hypothesis is countered by the busyness hypothesis. Shivdasani and Yermack (1999) assert that the number of outside directorships held by independent directors is important in determining firm value; although several outside directorships can be looked at as a signal of quality (Fama, Jensen 1983b, Fama 1980), independent directors with more than
57 three additional directorships will be looked at as too having little time to properly monitor the businesses he/she is directing, thus increasing agency costs (Shivdasani, Yermack 1999). The underlying idea is that the monitoring function of the busy board member is poorly taken care of. Holding too many outside board seats may make the executive so busy that his or her ability to monitor management is compromised, resulting in less managerial oversight. As a result, managers – taking advantage of less effective oversight - engage in activities that enhance their own private benefits or activities at the expense of shareholders. For example, the inclination of managers to make acquisitions unnecessarily is documented widely(Jensen, Ruback 1990, Bradley, Desai et al. 1988, Bradley, Desai et al. 1988, Loderer, Martin 1990, Jarrell, Brickley et al. 1988)and this value-destructing activity is one of those that an effective board could mitigate. Also an exhibit of potential value-destructing behavior by ‘busy’ directors is the report by Core et al. (1999), who contend busy outside directors provide CEOs with excessive compensation packages which in turn lead to poor firm performance. Markets have discovered this, apparently: Fich and Shivdasani (2006) find that busy directors are negatively associated with the firm’s financial performance. This is consistent with the view of the NACD (1996) and the Council of Institutional Investors (2003) that adopted resolutions calling for limits on the number of directorships held by directors. The Danish Recommendations on Corporate Governance state that: “ A member of the supreme governing body, who is also a member of the executive board of a company, should generally not take on more than a few non-executive directorships or one chairmanship and one non-executive directorship in companies not forming part of the group”. (DRCG, 5.7.1) (The Danish Commerce and Companies Agency 2005).
Finally, pointing in both directions, Sarkar and Sarkar (2009) note that the trade-off between expertise and knowledge gained from outside directorships vs. the time constraints on the individual director might exhibit non-linear features; it is suggested that some outside seats benefit the director’s ability to perform effective monitoring, while many might be detrimental.
Thus, the literature on whether directors holding many board seats is positive or negative in terms of his/her monitoring capabilities is somewhat mixed, but leaning in the busyness
58 hypothesis direction, pointing towards a notion that directors can only fully fulfill their monitoring and advising duties if they have relatively few boards seats. Keeping the incentives for management outlined in section 4.6.3 in mind, and summarized as a either/or option to provide clarity, it is hypothesized in this thesis that:
Ho: There is no relation between holding more than three outside directorships by the individual board member and risk-taking in Danish banks. H4: There is a negative relation between holding more than three outside directorships by the individual board member and risk-taking in Danish banks.
5.2.5 Board Tenure Generally, two competing perspectives influence the research literature when examining previous empirical studies on the optimum board tenure (number of years spent on the board) in relation to board effectiveness and more specifically to risk-taking behavior. Following the terminology of Vafeas (2003) the two distinct streams of thought are hypothesized; the expertise hypothesis and the management-friendly hypothesis. While Vafeas (ibid) can be accredited for constructing the two hypotheses, several empirical studies within the research area lie well before his article and will be sourced when appropriate.
The expertise hypothesis holds in favor of directors with long-term board service by suggesting a positive relation between time served and commitment, greater experience and competence. The founding argument for the expertise hypothesis is the accumulation of company knowledge and in-depth understanding of the business environment over time. The hypothesis builds on the arguments put forth by Buchanan (1974), in which he argues that extended tenure enhances the organizational commitment and the willingness to increase the efforts toward the company’s strategic goals. Vance (1983) supports these findings and further purports that rigid term-limits on maximum board time lead to a waste of talent and expertise, which may result in the composition of sub-optimal boards. The hypothesis thus indicates that the accumulated company-specific knowledge in board members minimizes the informational asymmetry (thereby lowering the monitoring costs) as their time served on the board increases. The expertise hypothesis is further supported by the reputational effect (see section 5.2.4), as the time served on the board sends an important signal of acquired expertise and successful
59 directorship, which - all things equal- will add to the market value of the individual board member. It can thereby be inferred that the reputational incentive to hold a board position for as long as possible will increase the board member’s focus on shareholder interest, as this stakeholder is the key to re-election.
The expertise hypothesis is contradicted by the management-friendly hypothesis. Katz (1982) argues that extended tenure significantly reduces the intra-group communication and tends to isolate the board from important informational sources. Vafeas (2003) further suggests that tenured board members are less likely to monitor managers, which (under the theoretical condition of a risk-averse CEO) could lead to an increase in the type-1 agency problem. Canavan (2004) supports these arguments by asserting that board members who ‘overstay’ fail to keep up with changes in the business environment, become strategy-fixated by defending past decisions and lack the ability to create innovative solutions to company challenges. The underlying idea is that the board member’s learning curve is very steep in the first years, but tends to flatten out as tenure increases. Having a board member hold a seat for too long is therefore not optimal for shareholders as their accumulation of knowledge becomes a declining function over time. As a result, the effectiveness of their monitoring efforts may decrease as their expertise is outdated, which ultimately could increase the type-1 agency problem. The latter hypothesis is in alignment with the NACD 1996 (1996) recommendations, which suggest a term limit of a maximum of 15 years, due to the increasingly dynamic business environment that requires new perspectives and critical thinking. This is however countered by The ISS Proxy Voting Manual, which asserts that: " Although establishing limits on the number of times a director may be elected to the board provides a mechanical or 'bloodless' means for addressing a real or potential performance issue with a director, it does not take into consideration the fact that a board member's effectiveness does not necessarily correlate with the length of board service ." (Institutional Shareholder Services 2005) These contradicting views are bridged by Standard and Poor’s who recommend a case-by-case evaluation of tenure (Standard and Poors 2009).
Thus, the literature and recommendations on whether directors’ tenure is positive or negative in terms of his/her monitoring capabilities is somewhat mixed as well, but leaning towards the expertise hypothesis this thesis holds the notion that tenured board members are more
60 efficient in their monitoring efforts and thus hypothesizes a positive relation between time served on the board and risk-taking behavior.
Ho: There is no relation between the years served on the board and risk-taking in Danish banks. H5: There is a positive relation between the years served on the board and risk- taking in Danish banks.
5.2.6 Financial education Whereas sections 5.2.2 and 5.2.4 hypothesize on the knowledge obtained from previous board experience or board experience gained simultaneously on other boards – both in relation to the firm’s core production and the board work itself – this part focuses on the theoretical knowledge about the workings of the field studied; banks 23 and their operation. Financial education is assumed to signal a better theoretical understanding of the financial position of the firm, whether that be a production company or a service provider such as a bank. In a similar stream of thought, Hall et al. (2004) find that reputation (and thus the possibility of being asked to run for a board seat) is associated with human capital derived from investments in education and other visible attributes that stand as proxies of actual capabilities of the person.
It is assumed throughout this thesis – in consistency with the cited references – that knowledge reduces monitoring costs. This is confirmed by Raheja (2005), who find that because the default option when the CEO proposes a project is to ratify it, educated board members have lower monitoring costs when analyzing the project and may easier opt to reject an inferior project. The empirical findings point in the direction that markets appreciate the appointment of financially educated directors to the board. Thus, evidence by Rosenstein and Wyatt (1990) indicates that the appointment of a financial outside director to the board of a public corporation is associated with a positive, abnormal return on the stock. The reasoning behind this may be found in Easterbrook (Easterbrook 1984), who argues that financial directors should have expertise in monitoring financial performance in their role as appraisers of creditworthiness and that the appointment of a commercial banker or an insurance company executive may serve to reduce agency costs between creditors and shareholders. In a
23 The specific criteria for determining whether a director has financial knowledge are developed in section 6.5.6.
61 later survey, Rosenstein et al. (1999) find that a significant positive wealth effect associated with the appointment of a financial outside director.
Ferris et al. (2003) find that since the board of directors is the primary instrument for the formulation and implementation of effective corporate governance, it is critical that this group be populated with an “appropriate membership”. Their findings suggest that a key selection criterion for board membership should be financial expertise, which in this context is translated as financial education. While it cannot guarantee effective governance, they find, it does appear to be a necessary precursor. It is argued that as representatives of the company’s shareholders, financial expert independent directors are more likely to cause management to adopt higher quality policies. The NACD (1996) asserts that imperatives to board of director effectiveness include director independence, level of activity and expertise. Financial expertise is reflected by a director’s background in or knowledge of accounting or finance.
The implicit assumptions seem to be that board members with financial education have lower monitoring costs, which ceteris paribus lowers overall cost to shareholders and to be better aligned with shareholders through their superior skills in monitoring, ratifying and possibly rejecting projects. Interestingly, Booth and Deli (1998) study the characteristics of firms that have financial directors and find that firms with a financial outside director have more debt than those without financial outsiders.
In the Danish Recommendations on Corporate Governance, no explicit recommendation on specific knowledge is mentioned, but it is stated that: “The Committee recommends that the supreme governing body annually assess whether the skills and expertise of its members need to be updated” (DRCG 5.2.2) and other references to the importance of relevant knowledge are made (The Danish Commerce and Companies Agency 2005).
Ho: There is no relation between the level of financial education of directors and risk-taking in Danish banks. H6: There is a positive relation between the level of financial education of directors and risk-taking in Danish banks.
62 5.3 Hypotheses - the board level The following four hypotheses relate to board structure as they are built on the board’s characteristics as a whole and thus hypothesize on the second part of the research question.
5.3.1 Board size As the board’s role is to ratify, verify and monitor the actions initiated by the top management (see section 4.8.1), a trade-off seems to emerge between resources held on the board and coordination and communication costs between the board’s members. While the capacity to monitor the top management increases with board members, this benefit may be outweighed by the additional costs of decision-making between extra board members. (John, Senbet 1998). In plain terms, the trade-off is between having a large, resourceful board and having a small board, which has lower communication and coordination costs. Lipton and Lorsch (1992) find that coordination and communication costs increase with the number of members on the board. The additional cost may impede the benefits from having a larger array of resources available in the monitoring function, which Jensen (1993) endorses. He finds more specifically that boards with more than seven or eight members are unlikely to be effective. The markets appear to agree with these findings, as Yermack (1996) finds that valuations of firms decrease over a range over board sizes from four to ten members. Furthermore, the study finds that profitability and asset utilization decrease as the board becomes bigger, again in a range from four to ten members. Bhagat and Black (1996) confirm Jensen’s (1993) predictions and confirm Yermack’s findings. Mak and Yi (2001) remark that smaller boards are associated with effective monitoring and less free-riding on behalf of the individual director. In a traditional finance research stream of thought, the trade-off between resources on the board and increased communication and coordination cost should be solved by the market forces. If Yermack’s findings are applicable in a broader sense, shareholders – interested in maximizing the value of their share and, in principle, nothing else – should punish boards that are too large (as having too large a board would mean forgone value increases of their shares). However, the very existence of the findings above suggest that market imperfections may exist (John, Senbet 1998) that eliminate or reduce the effect of the arbitrage mechanism, also in this relation. Denis (2001) remarks that board size may be a reflection of firm dynamics and while she concludes that the literature point in one direction only, she finds that board structure in general and size in particular may be a result of other corporate governance
63 mechanisms. Either way, the empirical studies on board size are greatly in favor of smaller boards, although not completely linear in the sense that a single member on the board is the most effective. Smaller boards thus seem to be value-creating for the shareholder, or; the communication and coordination costs increase rapidly as the number of board members increase. When the board is poorly coordinated, it can be argued that its power base erodes and leads to less regard for shareholder interests. Hermalin and Weisbach (2003) find exactly this and conclude that smaller boards lead management to act increasingly in alignment with shareholder interests. In the same review it is found that smaller boards are more likely to remove poor executive managers. Finally, relating these findings to risk, Cheng (2008) notices that firms with larger boards have less volatility on their stock and thus display less risk-taking behavior (which, ceteris paribus, is not in the interest of the shareholders, see section 4.6.1). The Danish Recommendations on Corporate Governance formulate the recommendation rather vaguely: “The Committee recommends that the supreme governing body have only so many members as to allow a constructive debate and an effective decision-making process enabling all members to play an active role” (DRCG, 5.3.1) (The Danish Commerce and Companies Agency 2005). Therefore, the thesis at hand finds its support in the empirical research, which finds that smaller boards are more aligned with shareholders. In this thesis, the findings above are formed into the following hypothesis:
Ho: There is no relation between board size (for sizes over 4) and risk-taking in Danish banks. H7: There is a negative relation between board size (for sizes over 4) and risk- taking in Danish banks.
5.3.2 Incentive programs As this thesis is a corporate governance-focused study, management is seen as a product of the system generated by (among other things, such as culture, legislation etc.) the owners or, as a representative of these, the board. Therefore, a deeper literature review on management and its influence in organizations is viewed as outside the scope and interest of the paper at hand, because the main issues in the relation between owners (and the board) and management have already been outlined in section 4.4.1.
64 What is the focus, however, is which actions the board of directors take in asserting the shareholders’ rights and incentives in the daily management. The literature on incentive programs is rather one-sided, though, and therefore, the hypothesis construction is not one of weighing a trade-off, but one of reviewing the prevailing view among scholars in the field (Core et al. 1999). Many corporations use incentive programs to mitigate the type-1 agency problem described in section 4.4.1. Two main types of incentive programs exist (Merchant, Van der Stede 2006), stock options (or stock payment) and bonus systems. Usually, stock options increase in value with the corporation’s stock’s value, while bonus programs pay a specified bonus and a percentage of this in relation to the fulfillment of certain, pre-specified measurement goals. Gore et al. (2010) and Core et al. (1999) define the CEOs incentives as the change in executive rewards brought about by changes in shareholder wealth and this thesis leans upon this definition in relation to stock option payment schemes.
The rationale behind using these is to shift the incentives of the management to those of shareholders, thus reducing the type-1 agency problem, but increasing the type-3 agency problem which is in the interest of the shareholders (Kose, Mehran et al. 2010). Kose et al. (ibid) find specifically that aligning managerial incentives with shareholders’ interests will exacerbate the shareholder-debtholder conflict in leveraged firms. In particular, managers who are aligned with shareholders will have the risk-shifting incentives i.e. the incentive to undertake excessive risk at the expense of debtholders. This thesis does not seek to investigate the level of compensation nor the performance measurement related to this, although literature abounds. Instead, the existence (or lack) of incentive programs as an indication of risk-alignment between the board of directors and management is the object for the study.
Jensen and Murphy (1990) predict theoretically that CEOs are only motivated to act in their shareholders’ best interest if they are offered incentive contracts that pay for ‘performance’. Milbourn (2003) describes this as the (or one of the) first studies to examine that phenomenon. This implies that CEOs with incentive payment packages will act (increasingly) in accordance with shareholders’ wishes.
65 As the CEO’s assumed risk-averseness is a central assumption, his pay-based incentives can be explored through the use of the elegant representation by Agrawal and Mandelker (1987), who offer an algebraic outline of the misalignment of incentives 24 .
The manager’s total wealth is represented by W, which is comprised of three elements: a) The wealth he derives from his human capital in the principal’s company (his salary): WH b) The wealth he derives from his stockholdings or –options (if any) in that company: WS c) The wealth he derives from holding assets unrelated to the firm: W0 Thus, the manager’s total wealth is summarized in the equation: W = WH + WS + W0, with W being variable with σ2, which depends on the volatility of WS and W0. Since W0 is assumed to be completely uncorrelated to his actions in the focal firm, the volatility of the manager’s total wealth is equal to the volatility on the stock of the company, because the others are constant. The resulting behavior - ceteris paribus - rests on the manager’s assumed rationality: If he holds none of the company’s stocks or options, his W is maximized by keeping WH as high as possible, which is best done by making sure the volatility on the income is as low as possible, thus improving the certainty equivalent in future income stream: the smaller the risk of bankruptcy, the higher the likelihood of deriving pay from the company in the future. If the manager, on the other hand, holds shares, his incentives become less obvious. On one hand, WH is still maximized when keeping default at bay. This conflicts with WS, which is maximized at relatively higher levels of risk. Thus, awarding the manager stocks or options will shift his incentives through the increased risk he bears, but the amount of risk is in a trade-off for the manager with the inversely related movements in WH 25 . This is somewhat similar to the pay-off proposition to the shareholders, of course, as they too should prefer the company in any solvent state over the bankrupt state. Agrawal et al. (ibid) thus find the implementation of incentive programs will reduce the type- 1 agency problem as the CEO adopts a more risk-seeking behavior.
Therefore, the thesis hypothesizes the following:
24 They assume that the principal is risk-neutral as well and that the manager acts rationally. 25 I.e.: when WS goes up, WH goes down.
66
Ho: The existence of stock-option payment schemes has no relation to risk- taking in Danish banks H8: The existence of stock-option payment schemes is positively related to risk- taking in Danish banks
Ho: The existence of bonus payment schemes has no relation to risk-taking in Danish banks H9: The existence of bonus payment schemes is positively related to risk-taking in Danish banks
5.3.3 The CEO’s tenure versus the board’s tenure While the board of directors officially is the representative of the owners of the company, multiple studies conclude that CEOs have actual power in the organization, among these Reinganum (1985), Smith and White (1987) and Thomas (1988), who all find that CEOs have strong effects on organizations. The research on the relation between the board’s tenure and the CEO’s tenure is relatively scarce and the studies that do exist point in diverging directions. In relation to agency theory, it could be implied that CEOs with longer tenure have stronger effects on the organization as a whole (due to an increased advantage in asymmetrical information, see section 4.3.5). Brickley et al. (1997) and Coles (2001) find that when the CEO has long tenure, he has earned the trust of the shareholders and thus requires less monitoring to act in the interest of them, because he is assumed to be knowledgeable and committed to the company. They argue that the fact that he has held on to his position for a relatively long period implies shareholders alignment – otherwise he would not have held his seat for so long. Schwenk (Schwenk 1993) finds that tenured CEOs formulate more efficient strategies and policies that will enhance the company’s performance, thereby decreasing the type-1 agency problem, as his actions are wealth creating. On the other hand, Pathan (2009) finds that bank risk-taking is positively related to strong bank boards and negatively related to CEO power 26 . Walters et al. (2007) find that when the board is weak and/or new, then CEO tenure is negatively associated with performance and
26 The term “a strong board” is defined in this hypothesis as a tenured board.
67 risk-taking. In the study, the researchers find that the longer the tenure of the board compared to that of the CEO, the better the shareholder alignment of the CEO. Shakir (2009) finds that CEOs who sit in their position for a long time may become complacent. Also, Shaker suggests that the tenured CEO facing a new board may act self- interested and entrench himself, which is not in alignment with shareholders and which is increasing the type-1 agency problem.
Thus, a hypothesis emerges of this paragraph leaning in the direction of the self-interested behavior from CEOs with longer tenure than the board, as this corresponds best to the agency theory outlined in section 4.6.3 The management.
Ho: The tenure of the CEO versus the tenure of the board does not influence risk-taking in Danish banks H10: CEOs with longer tenure relative to the board have more power than CEOs with shorter tenure and thus, having a CEO with longer tenure is negatively related to risk-taking in Danish banks.
5.4 Partial conclusion In this section, the hypotheses supporting the research question were built. On the board members’ individual characteristics, six hypotheses were constructed on: independence, board experience, gender, the holding of multiple directorships, tenure and on financial education. On the board level, four hypotheses were built on: board size, stock and bonus programs and on the CEOs tenure relative to that of the board.
68 6 SAMPLE CONSTRUCTION
The main purpose of this section is to identify the indicators that will represent the characteristics hypothesized upon in board members and on the board as a whole. In order to test the outlined hypotheses, the data collection and the selection criteria employed are described in detail, explaining the time period, the population and the sample. This is further done to increase the external validity of the study and to guide the reader when going into the statistical part of the thesis.
6.1 The timeframe First and foremost, the research period 2003 through 2008 is chosen as these years embody what can be termed the booming years and the following bust. Arguments for including earlier years could be made, but for the purpose of being able to obtain the strongest and most accurate pool of data, 2003 was picked as the cut-off year when going backwards. At the time of writing, not all data for 2009 were obtainable and were thus excluded. It is not the assumption that this represents a validity issue as many reactions to the financial instability are included in the 2008 data pool 27 . By investigating a finite time period it is possible to account for all board members and monitor all entries and exits. This allows for a more accurate research, as it is possible to delineate the influence of the individual board member’s characteristics to the actual time period on the board. The weighted influence of the respective board members (see section 6.4) further omits holding incumbent directors, who for example entered in 2008, accountable for erroneous decisions made by existing board members in 2003.
6.2 The population and sample The Danish retail banking industry comprises this thesis’ research population. A complete list was retrieved from DFSA, in which all Danish banks are ranked according to capital-at-work at the end of to 2008 28 (Finanstilsynet 2010). The study includes all Danish banks with a capital-at-work of more than DKK 1 bn. in 2008. This threshold was chosen as it fulfills the requirements for a solid sample by representing more than 95 % of capital-at-work in the
27 To avoid confusion: in the descriptive statistics, all members are included. However, as the regression analysis uses as its risk-measure the 2007 data, the board members who entered the boards in 2008 have been excluded from this particular analysis, so as to not hold those board members accountable for the risk-taking behavior leading up to 2007. 28 Two banks which were not on the 2008 list, but were in exisiting and fulfilling the size requirement in 2007 were included: bankTrelleborg and Bonusbanken. Both have been marked by *.
69 Danish retail banking industry. The final sample comprises the 67 largest banks in Denmark. As described in section 3.1 the industry is rather concentrated; the six largest banks have more than 80% of the market share. The following three tables show the total amount of capital at work for the respective banks and the corresponding percentage of the sample (see appendix 1 for a complete list:
Figure 6.1 Six largest Danish retail banks in the sample
1.600.000 55,98% 60,00% Capital at work 1.400.000 % of total capital at work in the sample 50,00% 1.200.000 40,00% 1.000.000 800.000 30,00% 600.000 13,62% 20,00% 400.000 6,61% 4,14% 10,00% 200.000 3,00% 1,91% - 0,00% Danske Bank A/S Nordea Bank Jyske Bank A/S Sydbank A/S Nykredit Bank A/S Spar Nord Bank Danmark A/S A/S
Source: (Finanstilsynet 2010)
Figure 6.2 The medium-sized retail banks in the sample
30.000 1,20% Capital at work 25.000 % of total capital at work in the sample 1,00% 20.000 0,80%
15.000 0,60%
10.000 0,40%
5.000 0,20%
- 0,00% … … … ebh bank a/s bank ebh Sparbank A/S Sparbank Max Bank A/S Bank Max DiBa Bank A/S Bank DiBa Fionia Bank A/S Bank Fionia Thy, Sparekassen Thy, Vestjysk Bank A/S Bank Vestjysk Nordjyske Bank A/S Bank Nordjyske Djurslands Bank A/S Bank Djurslands bankTrelleborg A/S* bankTrelleborg Alm. Brand Bank A/S Bank Brand Alm. Lån og Spar Bank A/S Bank Spar og Lån Den Jyske Sparekasse Jyske Den Sjælland, Sparekassen Sjælland, Morsø Sparekasse A/S Sparekasse Morsø EIK Bank Danmark A/S Danmark Bank EIK Middelfart Sparekasse Middelfart Nørresundby Bank A/S Bank Nørresundby Sparekassen Østjylland Sparekassen Forstædernes Bank A/S Bank Forstædernes Sparekassen Vendsyssel Sparekassen Arbejdernes Landsbank, Landsbank, Arbejdernes Lolland A/S, Sparekassen A/S, Lolland Kronjylland, Sparekassen Kronjylland, Ringkjøbing Landbobank, Landbobank, Ringkjøbing Sparekassen Faaborg A/S Faaborg Sparekassen Sammenslutningen Danske Danske Sammenslutningen Amagerbanken Aktieselskab Amagerbanken Himmerland A/S, Sparekassen A/S, Himmerland Lokalbanken i Nordsjælland a/s i Nordsjælland Lokalbanken
Source: (Finanstilsynet 2010)
70 Figure 6.3 The smallest Danish retail banks included in the sample
4.500 0,18% Capital at work 4.000 0,16% % of total capital at work in the sample 3.500 0,14% 3.000 0,12% 2.500 0,10% 2.000 0,08% 1.500 0,06% 1.000 0,04% 500 0,02% - 0,00% … … … Basisbank A/S Basisbank Møns Bank, A/S Bank, Møns Salling Bank A/S Bank Salling Totalbanken A/S Totalbanken Tønder Bank A/S Bank Tønder Kreditbanken A/S Kreditbanken Østjydsk Bank A/S Bank Østjydsk A/S Bank Vestfyns Brørup Sparekasse Brørup Løkken Sparekasse Løkken Bonusbanken A/S* Bonusbanken Farsø, Sparekassen Farsø, Skals, Sparekassen i Sparekassen Skals, Hobro, Sparekassen Hobro, Nr. Nebel Omegn,og Nebel Nr. Vordingborg Bank A/S Bank Vordingborg Svendborg Sparekasse Svendborg Spar Salling Sparekasse Salling Spar Sparekassen Limfjorden Sparekassen Sparekassen Hvetbo A/S Hvetbo Sparekassen Frøs Herreds Sparekasse Herreds Frøs Dronninglund Sparekasse Dronninglund Merkur, Den Almennyttige Almennyttige Den Merkur, Lollands Bank, Aktieselskab Bank, Lollands Skjern Bank, Aktieselskabet Bank, Skjern Skælskør Bank Aktieselskab Bank Skælskør Roskilde Bank, Aktieselskab Aktieselskab Bank, Roskilde Morsø Bank, Aktieselskabet Bank, Morsø Nordfyns Bank, Aktieselskabet Bank, Nordfyns Aarhus Lokalbank Aktieselskab Lokalbank Aarhus Grønlandsbanken, Aktieselskab Grønlandsbanken,
Source: (Finanstilsynet 2010)
6.2.1 Excluded banks 12 banks have been excluded from the sample although having a capital-at-work above 1 bn. DKK. Six banks are excluded as they are deemed to be primarily investment banks and not universal retail banks, which have been outlined as the research object. Second, reduced- service banks have been omitted as they are not accessible to the general population. Finally, three banks have been excluded on the following grounds: Danske Andelskasser Bank, because it is a bank for banks, not consumers. Next, Svenska Eskilda Banken (SEB) because it does not have a Danish board of directors. Finally, BRF, as it is a bank whose sole purpose is to finance the part of the home purchase which cannot be financed by taking out a mortgage (max. 80 %)
Table 6.1: Excluded banks EXCLUDED BANKS Investment banks Reduced-service banks Miscellaneous Carnegie PenSam Danske Andelskassers Bank Capinordic Lægernes Pensionsbank SEB Saxo Bank Finansbanken BRF DNB FIH FIH Capital Source: own contribution
71 6.3 The board members The data collection includes all Danish board members who entered, exited, entered/exited or who held a seat throughout the period 2003-2008 in the banks of the sample. A few board members have been omitted, as their time served on the board (cut-off at six months or less) was concluded to be insignificant. Employee-elected board members have also been included in the sample. It is noted, however, that their influential characteristics in the sample are not a direct result of shareholder election and as a consequence all data testing will be analyzed with and without their presence to provide the greatest amount of insight into the data. The sample includes 749 unique directors and 67 different banks. In total, 4.829 different data points have been collected manually in the research process. On top of this, risk measurement data (see section 7.7)) have been obtained from already-assembled lists.
6.4 Weighing the influence When collecting data on the board of directors, all years 2003-2008 have been investigated and the sample thus includes directors who no longer serve on the focal bank’s board and, conversely, it does not include current directors who did not serve in any of the focal years. The individual contribution of the directors has been weighed (from 0 to 1) according to the time served on the bank’s board. For example, a director serving in 2003 and 2004, but not 2005-2008 has been assigned the weight 0.333 in the statistical hypothesis testing. A director serving in all years 2003-2008 has been assigned the weight 1.
6.5 Individual level variables When investigating directors’ characteristics (independence, board experience, gender, multiple directorships, tenure and education) several sources have been utilized. Sources include the banks’ annual reports, the online directories Greens and BIQ, news articles, Linkedin profiles, Facebook profiles and, in rare cases, e-mail and telephonic contact.
6.5.1 Independence An independent director is defined as a “non-management director free of any family, material business or professional relationship (other than stock ownership and the directorship (the board directorship, ed.) ) with the corporation or its management . (Corporate Director's Guidebook 2001). It is assumed that a director is either dependent or independent and therefore, a dummy variable has been assigned in the analysis; 0 = dependent, 1 = independent.
72 6.5.2 Board experience A board is characterized as experienced when having served five years or more on any board prior to entering the bank’s board. This variable was computed as a dummy variable as well. Five years’ board experience prior to entering the bank’s board was assigned 1, less than five years’ (or no) board experience has been assigned a 0. One may argue that board experience should be a gradually increasing variable, but experience may come in the form of twenty served on one board, or six years served on four boards simultaneously (prior to entering the bank’s board). These two scenarios would be difficult to place on the same scale, as the latter example may in fact be more experienced than the former, although having served less than a third on a board, measured in years. The purpose of the investigation of board experience is not to determine the degree of experience between experienced board members, but to determine whether or not the board member is experienced. Because of the either-or nature of this perspective on board experience, a dummy variable is found to deliver a stronger measurement 29 .
6.5.3 Gender Gender has, surprisingly, not been deemed a scalable variable. Therefore, a dummy variable has been assigned the sample. 0 = male, 1 = female 30 . Gender was inferred from the names of the board directors. All directors’ names have been identifiable as either male or female.
6.5.4 Multiple directorships The definition of ‘many’ simultaneous directorships follows Shivdasani’s (1999) as described in section 5.2.4: the director is busy when holding more than three simultaneous board directorships. The distinction in the data analysis is again a dummy variable, because of the either-or nature of the empirical research leading to the hypothesis – although a director is probably marginally more busy for each directorship attained, the level of busyness is not important; whether a director is too busy or not too busy is important, though. Therefore, a director holding three or less seats has been assigned the value 1, a director holding more than three seats has been assigned the value 0. This information has been extracted primarily from the banks’ own Annual Reports and from the online directory BIQ. Directorships have been weighed as well according to how much time these simultaneous directorships have been held. They have been rounded to whole years
29 Further research might find it appropriate to use a spectrum or to copy this approach; either way seems appropriate.
30 The value of 0 for males and 1 for females were assigned randomly. By the female author of this thesis.
73 however, as the data does not in all cases provide exact dates for the beginning and the end of the directorship. The differences are deemed so incremental that this does not in any case compromise neither the validity nor the reliability of the data.
6.5.5 Tenure As tenure is a direct function of the years served on the board, it has been scaled. A dummy variable would not accurately reflect the increase in tenure above the cut-off point and it is the assumption that knowledge roughly increases linearly with time. The information has been extracted primarily from the directory BIQ and cross-referenced with the annual reports when the BIQ data seemed ambiguous.
6.5.6 Financial education Financial education has been characterized and collected as having a five-year education in the fields of economics, business economics, finance or accounting. Financial education as a variable is chosen to signal understanding of the lending and borrowing practices of the bank. Relevant work experience could have been used an indicator of financial understanding as well, yet it is found to be less precise, as the data is first of all difficult to obtain across the whole sample, and secondly because work experience in a financial institution is not the same as relevant work experience. The reason for setting the bar so relatively high is that to understand the risk-taking practices of the bank reasonably well, candidates are assumed to require a master’s level or equivalent education in the relevant field 31 . Financial education is analyzed as a dummy variable, too, as it is the assumption of the thesis that a director either is or is not educated. The variable is = 0 for no education on the cut-off level and = 1 for a five- year education in economics, business economics, finance or accounting.
6.6 Board level variables When investigating the board’s characteristics (size, incentive programs and CEO vs. Board) several sources have been utilized. Sources include the banks’ annual reports, the online directories Greens and BIQ, news articles, Linkedin profiles, Facebook profiles and, in rare cases, e-mail and telephonic contact.
31 The other reason for making a five-year education the cut-off is that this paper is concerned with observable characteristics and signals of the (potential) board members, thus making a degree in a finance-related discipline an easily recognizable measurement parameter that will be transferable to future shareholders’ meetings and to the general assembly when electing board members.
74 6.6.1 Board size The structural information (board size) has been retrieved from investigating the assigned weights given to each board member within the board. By the adding the assigned weights, the average size of the board over the period is found. For example, in a board with four members who have all served the entire period, the calculation is 4 x 1 = 4 seats. In a board with twelve members serving each one year and four members serving each three years, the calculation becomes 12 x 0.1667 + 4 x 0.5 = 4 seats on the whole board. Some of the investigated boards are not of equal size throughout the period, which is the reason why some board sizes do not compute as a whole number.
6.6.2 Incentives The existence of stock options and bonus programs were assigned dummy variables as it is the existence in itself, not the size and scale, which is the focus of this thesis. For bonus and stock options, the value 0 was assigned to banks that did not use such programs, the value 1 for banks that did. The presence of incentive programs has been collected primarily from the banks’ annual reports.
6.6.3 The CEO’s tenure vs. the board’s tenure In the case of CEO power, the years spent in the executive chair versus the average years the director has spent on the board were used in a ratio of CEO years/board years. Ratios > 1 indicate that the CEO has spent more years in the top management than the board has on average in the directorship; a ratio < 1 indicates the opposite. The CEO tenure was primarily found on BIQ, but in some cases supported by annual reports and news articles. Board tenure was calculated by summing the multiplications of the individual board members’ assigned weights in the researched period with the total years that each board member has served on the board32 .
6.7 Partial conclusion This part summarized first that the study includes 67 banks and 749 board members. Of these, 225 were found to be employee-elected representatives. The banks are studied in the years 2003-2008. Then, the ten hypothesis variables were described in terms of how they are measured in this thesis and the collection method for each was outlined.
32 Also including the years served prior to 2003
75 7 RISK MEASURES
The purpose of this section is to define the dependent variable. As multiple options exist, the main choices are outlined and evaluated. The section ends with the choice of the dependent variable; the risk measure used in the data analysis.
7.1 Assembling risk in one measure As described in the introductory part, the claim against the Danish banks in general is excessive risk-taking. To test the risk-taking in Danish banks against board composition and structure, a proper risk measure has to be selected, as any measure will be an estimation signal that implies, but does not directly and completely signal, risk-taking. Multiple options exist, each with their own advantages and shortcomings, which will be evaluated in the following before settling on a risk-measuring method. The choice will depend on the trade-off between accuracy in measuring the individual bank’s risk-taking and the possibility to generally use a measure to infer risk across the sample. In other words, the trade-off will be one between validity (is the measurement actually testing what should be tested) and (internal consistency-) reliability (can the measurement be appropriately used on all items in the sample) (Bryman, Bell 2003) General criteria for determining whether a measure is reliable and valid will in this case be that it accurately reflects risk. Therefore, the bank’s liabilities are revisited (fully described in section 3.4): simplistically stated; a bank with more loans than deposits needs to finance this gap in the interbank market. If it cannot, then the bank may raise capital in the stock market, but if that proves unsuccessful then the bank will almost certainly cease to exist. This risk is what the thesis is aimed at describing some of the dynamics behind and therefore, a foundation for choosing a risk measure is that it somehow encapsulates the described mechanisms. It is acknowledged that other samples may very well yield the need for a different risk measure than the one chosen in this study.
7.2 Stock volatility While the term ‘risk’ might have different meanings to different groups of people, it is commonly understood as (the possibility of) losing for example an investment. Modern portfolio theorists do not, however, define risk as a likelihood of loss, but as volatility to make use of the market’s combined information and responses to changes in forecast outlooks for a particular company. Volatility, it is argued, translates as shifting outlooks for the business
76 environment, the business’ risks (credit, market, operational etc.) (Keppler 1990). The finance literature generally supports this claim, and Bertsimas et al. (2004) state that the standard deviation of the return of a portfolio is the predominant measure of risk in finance. Therefore, this paper would prefer the standard deviation on the individual bank’s stock as its risk measure. However, only 41 of the 67 banks in the sample are listed and traded. Using only those 41 banks would leave the sample less valid; not only because fewer banks would be in the sample, but also because the listed status of the bank may convey information on the bank that would lead to selection bias. For example, if listed banks have more financial directors on the boards than do non-listed banks, the results of the data analysis would suffer from being extrapolated from a smaller sample and because it would have been taken from a biased sample. Therefore, the volatility of the banks’ stocks as measured by standard deviation is not used as this study’s risk measure.
7.3 Absolute growth in loans Another approach to define risk is to measure risk as the absolute, numeric growth in loans in a given time period. This measure would be deployable for all banks in the sample and thus fulfill the reliability criteria. Also, it is a well-known risk measure: the media frequently cites the absolute growth in loans as an example of ‘reckless’ behavior on the banks’ part, as this number is generally the more extreme when employing risk measures in banking (examples: (TV2 2008) and (Politikken 2008). The issue with using this risk measure is that it does not account for the absolute risk-level in the bank, because it does not consider deposits at all and because the numeric values can be misleading (not counting inflation, for example). Therefore, the absolute growth in loans is not used as a risk measure, either, as it is neither a valid description of the actual risk of going into financial distress nor a particularly reliable variable.
7.4 Annual relative increase in loans Risk-taking could also be measured as the arithmetic mean of the annual percentage increases in loans given by each bank. This measure is used by the Danish Financial Supervisory Authority (Finanstilsynet 2010) (among other parameters) to describe a bank’s riskiness. It therefore presents an obvious choice to pick, but does not solve the issue of not accounting for deposits, which this thesis wants to incorporate. The benefit of using this risk measure is that it accurately depicts the organizational dynamics which occur in the bank when the amount of loans increases, in some banks, rapidly. The circumstantial evidence point in the direction that this has been a contributor to the failure of some Danish banks in the period 2003-2008: The
77 lawyers commissioned to investigate Roskilde Bank criticize in their report the fact that the credit evaluation on new clients and projects has been lax and sub-standard and attribute this to the aggressive growth strategy of this particular bank. The same scenario is outlined by independent investigators for e.g. Løkken Sparekasse (Skipper-Pedersen, Stenbjerre 2008)
Addressing the dynamic issue of whether growth in loans leads to overburdened case workers in the banks: the research design deployed in this thesis does not yield room for qualitative investigation of the number of credit assessors in each bank in the sample, which is why it is argued that while using the annual percentage growth might be a reliable and valid method, it still does not guarantee on a higher-than-circumstantial basis that annual percentage growth in loans on the short term (6 years in this thesis) is a valid measure of risk-taking. It may very well be, but it need not be. The issue with using this risk measure is also that it still does not account for the absolute risk-level in the bank, because it too does not consider deposits. A suitable example of this is the investigation report on Fionia Bank, which states that: “ The Bank’s overall growth in loans has not been particularly high when comparing with banks of the same size ”(translated)(Skipper-Pedersen, Stenbjerre 2009) . Yet Fionia Bank’s loan/deposit ratio was 138.2 in 2007, well above average. To exemplify further, consider two banks: one banks lends out ten percent more in year 2 than in year 1, the other lends out fifty percent more. It is impossible to determine which bank has the highest risk profile, because the bank that lend out the most may also be the one which attracted many new depositors and thus had its loans covered by the new deposits, decreasing the risk that its funding would erode. This does not account for the risk-level from which the increases start – even without new depositors, the bank might already have a huge surplus in deposits. Therefore, the annual relative growth in loans is not seen as the best risk measure, either, as it is neither an accurate description of the actual risk of going into financial distress nor a valid variable for this thesis. To be certain that an appropriate measure is not rejected, the independent variables are tested on this risk measure in the data analysis section as a control variable similar but less significant results were obtained.
7.5 Growth in the loan/deposit ratio Accounting for the deposits, yet another risk measure is the percentage-wise growth of loans to deposits. This risk-measure takes into consideration the possible simultaneous increase in deposits and thus does not characterize banks which experience increases in loans as well as
78 deposits as ‘risky’. The measure is reliable as it is a relative measure – large banks and smaller banks can be indexed together – which counts in its favor. However, it is not particularly valid, as it does not account for the absolute level of loans to deposits. As a theoretical example, a bank that increases its loan to deposit ratio from 60 to 80 33 will be counted as having experienced a 33 % increase in this particular risk measure. Another bank, which raises its loan to deposit ratio from 160 to 200 will be counted as having experienced a 25 % increase in ‘risk’. This is not an accurate depiction of the risk experienced by the bank, because the second bank – deemed less risky by the measure – is much less liquid than the former example and its funding is much more exposed, all other things equal, to market risk than its competitor in the example. To further exemplify: the average increase in loans/deposits 2003-2007 34 is 34.28 %. However, employing this risk measure seems to place relatively safe banks well above the mean, as witnessed by Lån & Spar Bank, whose growth in the loan/deposit ratio is more than twice the average at 71.86 %. However, their absolute loan-to-deposit ratio remains well under 100 throughout the entire period, which basically classifies the banks as one of the least likely to go into financial distress (Børsen 2010b). It should be noted that some of the percentages correspond well to the reality, as witnessed by Aarhus Lokalbank (121.09 %, 139.56), Amagerbanken (66.40 %, 127.16) and bankTrelleborg (62.60 %, 125.82). Therefore, this risk measure presents some advantages, but unfortunately some significant drawbacks as well. While accurately depicting the development of the growth in loans relative to deposits, the lack of consideration for the absolute level of the loan to deposit ratio severely limits the applicability of this risk measure.
7.6 The absolute level of loans to deposits Finally, the absolute level of loans to deposits can be taken as a risk measure. As described above, other researchers in the field have done so recently (Bechmann, Raaballe 2009). The benefit of doing so is - perhaps not surprisingly - that the absolute level of outstanding loans is taken into account and therefore, this measure reflects the bank’s potential exposure to changing market conditions and, subsequently, its liquidity and solvency. This improves the measure’s accuracy. However, the dynamic feature of the relative growth ratio is somewhat lost as the number is inherently an absolute, not a relative, one.
33 Understood as “60 % of the deposits are lend out to 80 % of the deposits are lend out” 34 See section 7.7 Choice of risk measure for a justification of using 2007 and not 2008, the end of the surveyed period
79 The measure is reliable as it is equal for larger and small banks and all retail banks have a loan/deposit ratio. Moreover, the examples from the researched period seem to correspond well to the suggestion that the absolute level of loans is a relatively accurate description of bank risk. In order to make the measure increasingly valid, the mean of the loans in the research years can be replaced by the loan/deposit ratio of the end of the boom period. While intuitively less accurate than the mean of all years, the application is in fact well suited to summarize the development in risk-taking in the researched period: when using the peak year of the boom, the risk measure reflects the (absolute) level of loans resulting from the governing bodies’ actions throughout the boom period, which brings with it its own considerations: when did the boom end? Bechmann and Raaballe (2009) use 2008 in their study on bank management pay. It is argued in this thesis, however, that 2008 is not the most accurate year to capture the result of the boom years: House prices started stagnating/falling in late 2006 (see section 1.3), stock prices (OMXC20) started falling from the fall 2007 and the default of Bear Stearns and Lehmann Brothers, which sparked an international bank liquidity crisis, happened in 2008. Thus, the loan/deposit ratio at the end of 2007 could be argued to best represent the result of the actions in the boom period – increasing the accuracy of this variable – because the loan/deposit rates at the end of 2008 already account for drastic changes following the liquidity crises as well as new regulations and guarantees for the banking industry by the Danish government, enacted in November 2008. To further exemplify the potential inaccuracy of deploying the loan-deposit ratio at the end of 2008, the case of Roskilde Bank is visited: because the bank’s deposits were already been sold off, the remaining loan-deposit ratio was a result artificially inflated at around 1300; a result of political interfering and not of risk-taking behavior (more than already experienced) on the part of management or the board of directors. All banks except one that have faced either bankruptcy, been taken over, have entered financial distress or have been publicly speculated to be on the verge of going into distress show loan to deposit ratios at the end of the boom above the average, which in 2007 was a loan/deposit ratio of 123.35:
80 Table 7.1: Loan/Deposit ratio for selected banks in 2007
BANK L/D 2007 Bonusbanken 111,1 Lokal Banken Nordsjælland 119,2 Average 123,17 Løkken Sparekasse 126,43 Skælskør Bank 129,5 Morsø Sparekasse 129,9 Sparekassen Faaborg 136,5 Danske Bank 138,2 Fionia Bank 151,3 Forstædernes Bank 151,7 Max Bank 155,7 Forstædernes Bank A/S 163,1 Amagerbanken 165,4 bankTrelleborg 166,5 ebh Bank 183,2 Roskilde Bank 190,2 Aarhus Lokalbank 199,2 EIK Bank *653,5 Source: {{374 Finanstilsynet 2010}} * Estimate based on 2006. EIK Banks Loan/Deposit ratio decreased significantly in 2007due to inclusion of a junior loan as a deposit
7.7 Choice of risk measure The volatility is rejected as it does not apply to all banks. The growth in absolute loans is rejected as it does not account for deposits and thus, does not represent risk as an appropriate measure. The annual percentage increase in loans is considered as it accounts for the organization dynamics that contributed to the failure of banks in the researched period, but it is found that these banks would be measured as relatively risky under the (other) chosen risk measure in any case and it is therefore rejected, because it too is slightly less valid than the final measure. (2009) contemplate using this risk measure, too, in their paper on bank management’s pay. They decide to utilize the absolute loan/deposit ratio, while stating their results would be just about similar with either measure. The relative growth in loans/deposits is also acknowledged to be accurate in describing some banks’ development in the boom years, but not as a reliable risk measure that can be used generally across the sample. The absolute loan/deposit ratio has its drawbacks in describing the dynamics of the loan-giving (which the annual increase in loans does account for), but this is somewhat circumvented by utilizing the 2007 measure, which is suggested to be the most accurate summary of the actions taken by the banks from the beginning of the research period.
81 7.8 Partial conclusion This section first defined that choosing a risk measure should be one that mitigates the trade- off between (internal consistency) reliability and validity the best way possible. Then, five different risk parameters were evaluated: stock volatility, the absolute growth in loans, the annual relative increase in loans, the growth in the loan/deposit ratio and finally, the absolute level of loans to deposits. The latter of the five was argued to best serve this particular study’s purpose, as it incorporates the deposits to the bank as well. The year 2007 was chosen to reflect some of the dynamics behind the economic boom up until that year.
82 8 DESCRIPTIVE STATISTICS
The purpose of this section is to provide an overview over the gathered data in order to enhance the reader’s understanding of the governance structure of the bank boards in Denmark. Each variable that is hypothesized upon and subsequently analyzed will be presented in the following.
8.1 The sample The sample taken includes 67 Danish banks (see table 6.1, 6.2, 6.3, and appendix 1). Of these, 41 are listed for public trading. In total, 749 people have served at least a year on the board of the 67 banks in the chosen research period. Of the 749 directors, 524 are outside directors, 223 are employee-elected representatives (see appendix 3 for a complete list of all 749 board members).
8.2 The risk measure Risk is measured in this paper by the loan/deposit rate (see section 7.7):
Table 8.1 Loan/Deposit ratios for the period 2003-2008
LOAN/DEPOSIT Year Lowest Highest Mean Median 2003 42,5 316,4 94,71 89,9 2004 52,7 374,4 99,52 97,8 2005 53,8 **616,9 110,31 104,95 2006 63,7 **653,5 125,22 116,9 2007 68,1 199,2 123,17 119,2 2008 71,4 *1337,8 138,04 117,4 *This inflated value a result of Roskilde Banks bankruptcy in 2008 **These inflated values are both from EIK Bank, but in 2007 they receive a capital injection, which is why the number in 2007 is low The mean loan/deposit rate is increasing though all years, but the median decreases from 2007 to 2008, indicating a larger spread in 2008, all other things equal. The extremes range from a loan/deposit rate of 42.5, found in Bonusbanken in 2003 to 1337.80 in Roskilde Bank in 2008. The significant value-decrease from 2006 to 2007 can mainly be attributed to Eik Bank, which until 2007 by far had the largest loan/deposit rate, but as a result of a large equity transfer from headquarters dramatically decreased its rate.
Measuring from the mean loan/deposit ratio in the period, the banks with the highest average loan/deposit ratios are (in descending order): Roskilde Bank (363.63), EIK Bank (361.40), Ringkjøbing Landbobank (156.55), Aarhus Lokalbank (147.90), Forstædernes Bank (141.93), ebh bank (141.53) – for a full, sorted list, see Appendix 4.
83 Of the 67 banks in the sample, 40 have a mean loan/deposit ratio > 100. To put this into perspective: in 2003, 21 banks had a loan/deposit ratio < 100, while in 2007 this number had increased to 53 banks of 67 in the sample.
8.3 Individual variables The individual variables are described in the order they are hypothesized upon.
8.3.1 Independence Hypothesis 1 summarizes the thesis’ predictions on the impact of directors being independent:
Table 8.2 Independence INDEPENDENCE Type of director Independent % of directors Including employees 496 66,22 Excluding employees 496 94,66
Source: the information is derived from the data collection see appendix 3 for a complete overview
In the data set, no employee-elected representatives are independent, while 496 out of 524 outside directors are labeled independent. The dependent, outside directors amount to almost only one-in-twenty. Six banks have boards which are completely independent in the entire period: Møns Bank, Sammenslutningen Danske Andelskasser, Kreditbanken, Sparekassen Limfjorden, Vordingborg Bank, Brørup Sparekasse, which indicates that no employee-elected board members served on these boards throughout the period. Two banks boards have only dependent directors; Nordea Danmark and Nykredit Bank. Both are subsidiaries to larger financial holding corporations. Aside from these two, the bank with the lowest average number of independent directors in the period 2003-2008 is Nørresundby Bank, whose board is deemed 50 % independent. For a complete list please see appendix 5.
8.3.2 Board experience In hypothesis 2, the predicting value of having board experience prior to entry on the board is examined:
Table 8.3 Board Experience BOARD EXPERIENCE Type of director Experienced (> 5 Years) % of directors Including Employees 390 52,06 Excluding Employees 361 68,89 Source: the information is derived from the data collection see appendix 3 for a complete overview
84 In total, a little more than half of the board directors enter the board with more than five years of board experience. When excluding the employee-elected board members this number covers increases to almost seven-in-ten of outside directors are experienced above the threshold level of this study, while barely one-in-eight of the employee-elected representatives are. The bank with the most ‘experienced’ board is Basisbanken, whose directors in the period all had at least five years’ board experience prior to entering the board. The least experienced boards are those of (in ascending order): Sparekassen i Skals (15.6 % experienced directors), Andelskassen Merkur (19 %), Frøs Herreds Sparekasse (20 %), Sparekassen Faaborg (21,4 %) and Dronninglund Sparekasse (24 %). In 45 banks, more than half the board members could be deemed experienced upon entering the bank’s board. See Appendix 6 for a full list.
8.3.3 Gender Hypothesis 3 uses gender as a proxy for diversity on the board. The boards’ gender composition is as follows:
Table 8.4 Gender GENDER Type of director Women % of directors Including employees 122 16,29 Excluding employees 46 8,78 Source: the information is derived from the data collection see appendix 3 for a complete overview
In total, 16.29 % of the directors on the boards of Danish banks in the sample are female. Of the outside directors, only half of that are female; 8.78%. Of the employee-elected representatives, almost exactly one-in-three is female, indicating a higher concentration in woman amongst the employee-elected. The banks with the highest proportion of female representation are Møns Bank (40 % women), Lån & Spar Bank (38,6 %), Danske Bank (35,7 %). 16 banks of 67 do not have any women on their board at any point in the period – among these EIK Bank, Aarhus Lokalbank and Nykredit Bank. See Appendix 7 for full list.
8.3.4 Multiple directorships Hypothesis 4 is concerned with the number of seats an individual director holds simultaneously:
85 Table 8.5 multiple directorship MULTIPLE DIRECTORSHIP Type of director 3 seats or less % of directors Including employees 531 70,89 Excluding employees 310 59,16 MULTIPLE DIRECTORSHIP Type of director 1 Seat Highest # of seats Mean Median Including employees 370 81 4,46 2 Excluding employees 175 81 5,8 3 Source: the information is derived from the data collection see appendix 3 for a complete overview.
The mean including employee representatives is holding 4.46 board seats in total, while the median is lower, at 2 when excluding the employee-elected representatives, the mean is 5.80 and the median increases to 3. Both sets of data indicate that relatively many directors hold few seats, while a group of directors hold many board seats. To shed further light on this, the number of directors holding just the one seat they have on the board has been examined. It turns out that of the 225 employee representatives, a mere 8 hold board seats other than the one in their bank. In total, 370 directors hold just one seat (of 749), while just 175 of the 524 directors have only the board position in the bank. The range of board seats held goes from 1 (a large group of directors) to 81, held by Michael Kaa Andersen from Basisbank. On the aggregate board level, Basisbank tops the list with an average of 53.08 directorships per board member (Michael Kaa Andersen may increase the average, but the rest of the board is not shy of directorships either). Tallying an average of 17.32 directorships, Amagerbanken’s board is a distant second and in EBH Bank, the average number of simultaneously held directorship is 11.29. At the other end of the spectrum, the directors in Sparekassen i Skals on average have 1.09 directorships which covers the fact that of the 15 directors who have served on the bank’s board in the period from 2003-2008, only one director (Leif Gade) has other directorships, and that is merely one additional directorship. In total, only 25 banks on board level average comply with the Danish Corporate Governance Recommendations’ advice that board members should hold three seats or less. Those that fall into the recommended category of three board seats or less amount to 531, of which 220 are
86 employee representatives. Only 5 employee representatives hold more than 3 simultaneous board seats. See appendix 8 for a full list.
8.3.5 Tenure Hypothesis 5 concerns the level of tenure among Danish bank board directors:
Table 8.6 Tenure
TENURE Type of director Lowest Highest Mean Median Including employees 1 28 6,75 6 Excluding employees 1 28 7,57 7 Source: the information is derived from the data collection see appendix 3 for a complete overview
The mean of average time served on the board increases, when employee-elected directors are excluded. This indicates that employee-elected board member serve shorter periods of time on the board. The array of tenure in the Danish boardrooms range from 1 to 28 years on a specific board, held by Leif Bertnsen in Morsø Sparekasse.
In Kreditbanken, board members have served (at the end of 2008) on average 16.92 years on the board, making it the board with the highest average tenure. Following in the second place is Østjydsk Bank, whose board members on average hold their directorship 14.77 years. At the other end of the list, Basisbanken’s directors have held on for 5.00 years on average and in Ringkjøbing Landbobank, board members have had their seats for 6.56 years. In Vestjysk Bank, board members have held their seats for an average of 6.70 years, but this number covers three newly elected board members who joined the board following the merger with Ringkøbing Bank. See Appendix 9 for full list.
8.3.6 Financial education In hypothesis 6, the relation between financial education of the individual board member and risk is predicted:
Table 8.7 Financial education FINANCIAL EDUCATION Type of director Educatated % of directors Including employees 115 15,36 Excluding employees 84 16,03 Source: the information is derived from the data collection see appendix 3 for a complete overview
87 Of the total sample, 115 hold a financial education; of these 31 are employee-elected representatives. While 16.03 % of outside directors are financially educated, slightly fewer employee-elected representatives are, tallying in at 13.78 %. While this might seem contradictory – the employees are employed at a bank – the relatively high barriers to achieve the label “financially educated” (see section 6.5.6) exclude some diploma-educated bank employees. On the bank level, EIK Bank only has financially educated directors serving on their board. The second-‘most’ educated bank is Nordea, in which 87.5 % are financially educated as measured in this thesis. Nykredit Bank has 67.9 % financially educated board members. These three are the only banks which on average have more than 50 % financially educated board members. In twenty banks, no director at any point in the six-year research period has been able to claim a longer financial educational background. Included in this group is Amagerbanken, Lokalbanken i Nordsjælland and several smaller regional/local banks. See appendix 10 for a complete list.
8.4 Board level variables The board level variable will be described in the order they are hypothesized on:
8.4.1 Board size In hypothesis 7 the relation between size of the board and risk-taking behavior was outlined:
Table 8.8 Board size
BOARD SIZE Type of director Smallest Largest Mean Median Including employees 4 16,5 7,76 7,5 Excluding employees 3,5 10,83 5,62 5,33 Source: the information is derived from the data collection see appendix 3 for a complete overview
The smallest board in the sample consists of four directors, Eik Bank. It is followed by four banks, whose boards are comprised of five members: Vordingborg Bank, Tønder Bank, Møns Bank, Brørup Sparekasse. The largest board in the six year period is Danske Bank, which on average held 16.5 board seats. The second largest board is found in Sparekassen Vendsyssel, holding 13.5 seats throughout the research period. The means of 7.79 with employee-elected representatives and 5.62 without reveals that Danish bank board, on average, have 2.17 employees represented on their boards. The median lies relatively close to the mean in both
88 cases and the distribution does seem to be fairly smooth with few extremes. It seems that 6 seats or 9 seats are the most common size for a Danish bank board; eleven banks have six seats, ten banks have nine seats. See appendix 11 for a complete list
8.4.2 Incentive programs; bonus and stocks Section 5.2.2 hypothesizes on the impact of incentive programs, stock and bonus payment schemes. Of the 67 banks, their usage can be summarized as follows:
Table 8.9 Incentive programs
INCENTIVE PROGRAMS Banks Bonus Stocks (Option) Both None Total 18 22 11 38 Source: the information is derived from the data collection see appendix 3 for a complete overview
A total of 38 banks do not use incentive programs at all. 22, a third, use stocks or stock options, while 17 use bonus programs. These overlap somewhat, as 11 banks – a sixth – use both. Thus, only 6 banks use a bonus scheme without a stock plan.
8.4.3 CEO vs. board This variable is hypothesized upon in section 5.2.3. The ratio measures the tenure of the CEO versus that of the board, increasing with the CEO’s time on the board relative to that of the board’s.
Table 8.10 Board vs. CEO
BOARD VS. CEO Type of director Smallest Largest Mean Median Including employees 0,41 4,71 1,93 1,75 Excluding employees 0,39 4,04 1,79 1,66 Source: the information is derived from the data collection see appendix 3 for a complete overview
Both when including and excluding the time spent by the employee-elected representatives, the values approximate 0.4 for the boards which have served comparatively longer than the CEO. On average the CEO of Danish banks have served almost twice as long as the average board in the period 2003-2008. Nordfyns bank claims the longest board time versus CEO time when employees are included, while Max Bank (0.39) has the longest-serving board relative to the CEO’s tenure when employees are excluded. Conversely, Lån & Spar Bank has the board with the relatively
89 shortest average time served relative to the CEO’s with a ratio of 4.71 (both when employee- elected representatives are included and excluded, the ratio then being 4.04). The mean is 1.94 and 1.79, respectively, which are close to the medians of 1.81 and 1.66. This means that the average CEO has served in his position almost twice as long as the board. See appendix 12 for a complete list. When looking at the CEO alone, the longest top manager tenure is found in Sparekassen Sjælland, where Flemming Hansen at the end of 2008 has held his job for 31 years. In 28 banks, the CEO has held onto the top position for 15 years or longer. Indeed, a CEO in the sample has been in his position on average 13.8 years. For a complete list please see appendix 13.
8.5 Partial conclusion This section outlined first the characteristics of the sample and then evaluated the risk measure chosen for the study. Then, the six hypotheses on board composition’s descriptive statistics were presented, as were the four hypotheses on board structure’s.
90 9 DATA ANALYSIS
The purpose of the following section is to test the hypotheses on the chosen risk measure. First, the four test models are presented. Then, the results of the backward elimination model (the statistical analysis chosen for this thesis) are summarized to provide an overview for the reader. Then, each variable’s impact on the model (and thus on risk-taking) is thoroughly analyzed, before a correlation analysis is conducted. Finally, all significant variables in the four respective models are presented.
9.1 Regression analysis A linear multiple regression analysis is performed on the independent variables as described at length above (see section 6 and 8) to test the hypotheses outlined in section 5. Selecting a multiple regression approach allows for a calculation of a significance level for the degree to which one numerical value predicts the values of a separate numerical value ((Canavos, Miller 1999) and thus fits the purpose of this data analysis well. More specifically, the significance of the independent variables in relation to the dependent variable are tested via a partial F-statistic: the reason for not applying a full-fitted model (a regular multiple linear regression) is because the null hypothesis tested in such a model states that that none of the variables, combined, affect Y. These are not the null hypotheses in this paper. Instead, the null hypothesis for each variable is that one independent variable (each at a time) does not contribute to the variance of Y and thus, they are tested as individual contributors but in a combined model. The model best suited to fulfill this purpose is seen as a backward elimination (Kemp, Kemp 2004), which can be expressed in the following full model type to be tested:
Υ=+ + +… + ε ββ0 1Χ1 β 2 Χ 2 β n Χ n
9.2 Models for analysis Considering the division of variables on group (board) level and the variables relating to the individual director (see section 5.1), as well as the two scenarios including/excluding employee-elected representatives (see section 6.3), four models emerge for analysis (for full regression output, see Appendix 14)
91 Model 1a
L/D t =++α ββINDP BRDEX + β GENDER + ββ MULT + TENURE + β FINED + ε 12 3 45 6 Model 1b
L/D t =++α ββINDP BRDEX + β GENDER + ββ MULT + TENURE + β FINED + ε 12 3 45 6 Model 2a
L/D =+α BRDSIZE + SHARES + BONUS + CEOvBRD+ ε t β1 β 2 β 3 β 4
Model 2b
L/D t =+α βBRDSIZE + β SHARES + β BONUS + β CEOvBRD+ ε 1 2 3 4 where:
VARIABLE DESCRIPTION L/D : Is the Loan/Deposit rate t: Year 2007 INDP : Independence “1” if independent, otherwise “0” BRDEX : Board experience “1” if experience, otherwise “0” GENDER : Female “1” male “0” MULT : Number of seats “1” if ≤ three, otherwise “0” TENURE : Number of years served on the board FINED : Financially educated “1” if educated, otherwise “0” BRDSIZE : Average number of seats in the board from 2003-2007 SHARES : Stock (option) incentive program “1” if given, otherwise “0” BONUS : Bonus incentive program “1” if given, otherwise “0” CEOvBRD CEO tenure divided average board tenure ultimo 2007
92 9.3 Statistical results Through backwards elimination, the following significant models are returned 35 :
Table 9.1 Model statistics
PARAMETER MODEL 1A MODEL 1B MODEL 2A MODEL 2B PROB A > F PROB B > F 117,96 104,09 - - Intercept ***<.0001 ***<.0001 (1771,57) (392,24) - 14,1 -- INDP 0,306 ***0,0013 (1,04) (10,52) -5,11 -5,03 -- BRDEX **0,0129 **0,0423 (6,21) (4,14) -- -- GENDER 0,3903 0,3635 (0,74) (0,83) -3,59 -4 -- MULTDIR *0,0944 *0,0737 (2,80) (3,21) 0,31 0,33 -- TENURE **0,0412 *0,0619 (4,18) (3,50) 5,39 8,15 -- FINED **0,0213 ***0,0044 (5,32) (8,20)
-- 113,68 102,59 Intercept ***<.0001 ***<.0001 (878,47) (258,39) -- -- BRDSIZE **0,47 *0,7685 (0,53) 0,09 -- 16,77 18,35 SHARES **0,0189 ***0,0076 (5,81) (7,63) -- 15,87 14,82 BONUS **0,0384 **0,046 (4,48) (4,15) -- - 4,78 CEOvBRD 0,3925 *0,0944 0,74 (2,89) * = significant at the 90 % confidence level ** = significant at the 95 % level *** = significant at the 99 % level
To each variable, the prediction is stated with the F-statistic in parenthesis underneath. The higher the F-statistic, the more significant the variable. This is reflected at Prob > F, the probability that the null hypothesis holds. Other statistical models generate R-square statistics, but these are not calculated in this particular type of test model for the variables that remain in the model. When using a stepwise regression model like the backwards elimination model, the F-statistic is the explanatory variable as F-statistics are used when including more than two variables in a model (if there are just two variables, the t-statistic is used). The excluded variables do not return a parameter estimate, but do return (low) F-statistics.
9.3 Reference categories The reference categories describe the situation in which the significant predicting independent variables are assigned the value = 0. This situation is used as a ‘base case’ from which to
35 The model output is that commonly used for stepwise, backward elimination regressions. The standard error is not included, but is considered if important to the result. The full output is found in Appendix 14.
93 describe the impact of an assigned value of the independent variable studied. Relating to the models, the reference category is not when the null hypotheses are confirmed, β = 0 rather it is when the measure of the independent variables is zero:
L/D =α + ε t
The reference variables are described from the variable’s view, thus including both model 1a and 1b on the individual level regarding the board composition and both model 2a and 2b regarding the board structure.
9.4.1 Individual level, including employee-elected representatives The reference category for model 1a includes the following significant independent variables: financial education, board experience, number of multiple simultaneous directorships, and number of years served on the board . When the variables are held at zero, the intercept yields a loan/deposit rate of 117.96. This translates, in model 1a, to a director without financial education, without board experience, with more than three simultaneous directorships and with zero years served on the board.
9.4.2 Individual level, excluding employee-elected representatives The reference category for model 1b includes the following significant independent variables: Independence, financial education, board experience, number of multiple simultaneous directorships, and number of years served on the board . When the variables are held at zero, the intercept yields a loan/deposit rate of 104.09. This translates, in model 1b, to a director who is dependent, without financial education, without board experience, with more than three simultaneous directorships and with zero years served on the board.
9.4.3 Board level, including employee-elected representatives The reference category for model 2a includes the following significant independent variables: bonus and shares. When the variables are held at zero, the intercept yields a loan/deposit rate of 113.68. This translates, in model 2a, to a board which has not granted the top management either of those incentives payment programs.
9.4.4 Board level, excluding employee-elected representatives The reference category for model 2b includes the following significant independent variables: bonus, shares and CEO/board. When the variables are held at zero, the intercept yields a
94 loan/deposit rate of 102.59. This translates, in model 2b, to a board which has not granted the top management either of those incentives payment programs and which has a board with (much) longer tenure than the CEO 36 .
9.5 Results Having established the reference categories, the analysis moves on to investigate the impact of each independent variable, assuming the rest are held constant (as in the reference category scenario) to evaluate their individual impact when assigned a value. As described in section 5, the variables have been assigned each their null hypothesis which will be either confirmed or rejected and in the latter case, if the null hypothesis can be rejected, the variable’s significance will be examined.
9.5.1 Individual independent variables The results of the individual independent variables will be summarized one-by-one in the following:
9.5.2. Independence In model 1a, the independence variable is excluded in the backward elimination and the null hypothesis cannot be rejected (see section 5.2.1). Thus, independence in model 1a is not a significant predictor of risk taken as measured by the loan/deposit rate. In model 1b, the independence variable is included in the backward elimination and the null hypothesis is in this case rejected (see section 5.2.1). Hence, independence becomes a significant predictor of risk at the 95 % confidence level. More specifically, an independent board member will add 14.10 to the loan/deposit rate, all other things equal. This means that hypothesis H1 is confirmed; there is a positive relation (in model 1b) between independence and risk-taking.
9.5.3 Board experience In model 1a, the board experience variable is included in the backward elimination and the null hypothesis is rejected (see section 5.2.2) while the alternative hypothesis H2 is also rejected, and is reversed . Thus, board experience in model 1a is a significant predictor of risk-
36 To avoid any confusion regarding the value ”0” in a fraction: the fraction is CEO/Board, which means that either could, in theory, be zero and yield a ”0” result. However, if the board is “0”, the fraction does not compute and this value is thus not double-directional. Rather, holding the fraction at “0” is at best an approximation going towards zero , because there is always a CEO and there is always a board and both have some tenure. However, with a board of e.g. ten years mean experience and a CEO on his first day, the fraction will be infinitesimally small, approximately “0”.
95 taking at the 95 % confidence level, the relation is however negative. A board director with previous board experience will decrease the loan/deposit rate by -5.11, all other things equal. In model 1b, the board experience variable is also included in the backward elimination and the null hypothesis is rejected (see section 5.2.2) while the alternative hypothesis H2 is also rejected, and is again reversed . Thus, board experience in model 1b is a significant predictor of risk-taking, too, and the exclusion of employee-elected representatives does not alter the direction of the causal relation between board experience and risk-taking. This variable is also significant at the 95 % confidence level. The degree alters slightly though, as a board director with previous board experience in model 1b will decrease the loan/deposit rate by -5.03.
9.5.4 Gender In model 1a as well as in model 1b, gender is excluded from the backward elimination model. The null hypothesis (see section 5.2.3) can therefore not be rejected and as a consequence, gender is not a significant predictor variable in this study.
9.5.5 Multiple directorships held by the board member In model 1a, the multiple directorships variable is included in the backward elimination and the null hypothesis is rejected (see section 5.2.4), while the alternative hypothesis H4 is rejected and reversed . Hence, holding three or less directorships is a significant predictor of risk, though at the 90 % confidence level 37 . The relation is negative. A board director with three or less directorships will, ceteris paribus, decrease the loan/deposit rate by -3.59 units. In model 1b, the multiple directorships variable is included in the backward elimination and the null hypothesis is again rejected, while the alternative hypothesis H4 is rejected and reversed . As in model 1a, holding three or less directorships is a significant predictor of risk, again at the 90 % confidence level, and the relation is negative and steeper than in model 1a. A board director with three or less directorships will decrease the loan/deposit rate by -4.00 units.
9.5.6 Tenure (time spent on the board) In contrast to the previously examined variables, tenure is not a binomial variable, but a scaled variable.
37 The 90 % confidence level is acknowledged to be less strong than the 95 % confidence level usually used as a cut-off in studies like this. However, since the sample size is very large compared to the population (see appendix 1), the variables at 90-94,99 % are included as well, though a certain level of caution should be exercised when extrapolating to (another) general population in these variables.
96 In model 1a, the tenure variable is included in the backward elimination and the null hypothesis is rejected (see section 5.2.5), while the alternative hypothesis H5 is confirmed. Hence, the years spent by a director on a board are a significant predictor of risk at the 95 % confidence level, and the relation is positive. An incremental year served on the board will increase the loan/deposit rate by 0.31 units, all other things equal. In model 1b, the tenure variable is also included in the backward elimination and consequently, the null hypothesis is rejected and subsequently the hypothesis H5 is confirmed. At the 90 % (93.8 to be exact) level tenure is a significant predictor of risk taking behavior, the relation being positive.
9.5.7 Financial education In model 1a, the financial education variable is left in the backward elimination model and the null hypothesis is rejected (see section 5.2.6). The alternative hypothesis H6 is confirmed and financial education emerges as a significant predictor of risk at the 95 % confidence level with a positive causal relation. A board director with financial education will increase the loan/deposit rate by 5.39. In model 1b, the variable is again left in the backward elimination model. The null hypothesis is rejected and the alternative hypothesis H6 is confirmed, which is even at the 99 % confidence level. The relation is positive. A board director with financial education will in model 1b – without employee-elected representatives – increase the loan/deposit rate by 8.15 all other things being equal.
9.6 Board level independent variables The following variables have been tested on the whole board, thus reducing the sample size in absolute numbers, while keeping the percentage of the total population sampled.
9.6.1 Board size In model 2a, the board size variable is excluded in the backward elimination and the null hypothesis cannot be rejected (see section 5.3.1). Thus, board size in model 2a cannot be said to be conclusive in relation to the board’s risk-taking as measured by the loan/deposit rate. In model 2b, the same image emerges: board size is excluded from the backward elimination model and thus, the null hypothesis still stands.
9.6.2 Stock payment / stock options In model 2a, the stocks variable is included in the backward elimination. This rejects the null hypothesis and confirms the alternative hypothesis H8 (see section 5.3.2); the presence of
97 stock payment plans is a significant predictor of risk-taking in Danish banks. Stock payment plans increase the loan/deposit ratio by 16.76 and is significant at the 95 % confidence level. In model 2b, the stocks variable is also included in the backward elimination. Again, the null hypothesis is rejected and the alternative hypothesis H8 is confirmed. In model 2b, this causal relationship is significant at the 99 % level. The presence of stock payment plans increases the loan/deposit ratio by 18.35.
9.6.3 Bonus schemes In model 2a, the bonus variable is left in the backward elimination model. The null hypothesis is rejected; the alternative hypothesis H9 is confirmed (see section 5.3.2). Like stock options, bonus schemes are a significant predictor of risk-taking behavior, significant at the 95 % confidence level. A bonus scheme – in model 2a – increases the loan/deposit ratio by 15.87. In model 2b, the bonus variable is also left in the backward elimination model. The null hypothesis is rejected while the alternative hypothesis H9 is confirmed. Bonus schemes in model 2b emerge as a significant predictor of risk at the 95 % confidence level and increase the loan/deposit ratio – ceteris paribus - by 14.81.
9.6.4 CEO vs. the board In model 2a, the ratio CEO tenure vs. board tenure does not yield a significant result and is therefore excluded from the backwards elimination model. The null hypothesis (see section 5.3.3) can thus not be rejected in model 2a. In model 2b, the CEO/board variable is left in the backward elimination model. The null hypothesis is rejected and the alternative hypothesis H10 is rejected as well, but is reversed with 90 % statistical confidence. Hence, when the CEO/board ratio increases, risk increases as well – each unit increases the loan/deposit rate by 4.78.
9.7 Correlations 38 In using a multiple regression method, the correlation between the independent variables can compromise the strength of the results just outlined above as predictor variables that are highly correlated will offer redundant information. In order to ensure that the results exhibit internal validity, Pearson’s correlation coefficient was tested on the significant predictor variables in all four models. See appendix for a full correlation test output. Below is an outline of the correlation test results, which will include those variables that are significant predictor variables in the four models and which display significant correlations
38 For complete correlation output on all four models please see appendix 16
98 above 0.3 or below -0.3 (on a scale from -1 to +1). The value 0.3 was chosen based on graphical displays of correlations; as such no standard cut-off rule exists to determine when a predictor variable is too closely correlated to the next 39 . Although the general model discussion is saved for section 10, this specific part will include possible explanations for correlation and should be regarded as a brief – but consciously chosen - detour from the thesis’ outline.
9.7.1 Model 1a and 1b. In model 1a and in model 1b as well, only the variables “board experience” and “multiple directorships” emerge as correlated with the negative coefficient of -0.58 in model 1a and - 0.52 in model 1b. This negative correlation is to be expected, as the value “1” in board experience represents more experience, whereas the value “1” in “multiple directorships” represents a director who holds three board seats or less. The correlation seems logical; those directors who are deemed “experienced” are experienced from sitting on a board (or several boards) which, ceteris paribus, increases the likelihood of being considered for other directorships. This argument is further supported by the reputation hypothesis outlined in section 5.2.4. Moreover, model 1a includes employee-elected representatives, who in most cases hold only the directorship in the bank they are employed in and are primarily elected in their role of being employees as opposed to the outside directors. Therefore, they can gain experience through their directorship but, as the data collection shows, have much less propensity to be sitting on multiple other boards (see section 8.3.4). It is then acknowledged that these two variables may offer some form of redundant information, as the one explains a part of what the other does as well. However, both variables are left in the models as it is the conviction that they do explain two different, clearly distinguishable characteristics of a prospective board member.
9.7.2 Model 2a and 2b The connection between the variables “bonus” and “stocks” displays itself identically in both models as those variables are not dependent on the presence of employee-elected representatives. The correlation coefficient is 0.39 and this correlation seems logical as well: both variables are a representation of the board’s decision to implement incentive programs for the management, only the execution and design of the incentive program differ. As
39 The appendix 15 offers scatterplots to illustrate different correlation coefficients.
99 described in section 8.4.2, a number of banks have both programs in order, which runs up the correlation score. Even so, the variables are kept separately in the regression models as they are not at all perfectly correlated and each on their own still hold independent, explanatory value for the 61 % that is not accounted for in the Pearson correlation analysis 40 .
9.8 Full models Model 1a
L/D =+α BRDEX + MULT + TENURE + FINED + ε t β1 β 2 β 3 β 4
Model 1b
L/D =++α INDP BRDEX + MULT + TENURE + FINED + ε t ββ12 β 3 β 4 β 5
Model 2a
L/D =+α SHARES + BONUS + ε t β1 β 2 ’ Model 2b
L/D t =+α βSHARES + β BONUS + β CEOvBRD+ ε 1 2 3
9.9 Most risk-taking director and board The most risk-seeking director in the model 1a (including employee-elected representatives) is a non-experienced, tenured, financially educated director holding more than three simultaneous seats. In model 1b the director would in addition to the above mentioned characteristics also be independent. The most risk-seeking board in model 2a is that which grants share and bonus programs. In model 2b the board would additionally be one which has relatively shorter tenure compared to the CEO.
40 For complete correlation output on all four models please see appendix 16
100 9.10 Partial conclusion In this section, it is found most suitable to use a graphical illustration of the results of the statistical analysis as the conclusion:
H NUMBER HYPOTHESIS H0 MODEL A H1 MODEL A H0 MODEL B H1 MODEL B 1 A positive relation between independence and risk Confirmed Rejected Rejected Confirmed 2 A positive relation between board experience and risk Rejected Reversed Rejected Reversed 3 A positive relation between women on the board and risk Confirmed Rejected Confirmed Rejected 4 A negative relation between multiple directorships and risk Rejected Reversed Rejected Reversed 5 A positive relation between tenure and risk Rejected Confirmed Rejected Confirmed 6 A positive relation between financial education and risk Rejected Confirmed Rejected Confirmed 7 A negative relation between board size and risk Confirmed Rejected Confirmed Rejected 8 A positive relation between stock option payment and risk Rejected Confirmed Rejected Confirmed 9 A positive relation between bonus payment schemes and risk Rejected Confirmed Rejected Confirmed 10 A negative relation between relatively tenured CEO's and risk Confirmed Rejected Rejected Reversed
101 10 DISCUSSION AND IMPLICATIONS
The purpose of this section is to put the findings of the analysis into the context of the thesis. It should be noted that the purpose of the section is not to discuss the ‘financial crisis’, but to discuss the actual findings and the origins of them. Thus, it should primarily provide the reader with a starting point for further debate. The findings of the data analysis are summarized in the same order as they were analyzed and, with a starting point in the findings 41 , the results in relation to the theory outlined in sections 9.3 through 9.6.4 of the thesis are discussed. When relevant, bank examples will be included to illustrate the topics. The sample’s influence on the findings is discussed as well in separate paragraphs; this is done to highlight the caution with which results should be interpreted and to give the interested reader suggestions for alterations (when applicable) should he wish to replicate the study. After having drawn up the discussion points emerging from the data findings, their implications for the five stakeholder groups are outlined as well. One specific assumption is highlighted before proceeding to the discussion: the agency theory perspective deployed in the paper assumes risk-averseness on the CEO’s part, but the section on alternative incentives for the CEO suggest that other risk preferences might exist in the CEO. This uncertainty about the CEO’s preferences is surely a matter for further study by other researchers interested in business psychological dynamics, but this discussion section merely incorporates the alternative possibility (that the CEO can be risk-seeking) to evaluate some of the findings as well, in order to provide the reader with a more thorough understanding of the results and to shed light on the possible different explanations for the obtained results. It does not, however, aim to resolve whether or not the CEO is risk-seeking.
10.1 Independence The hypothesis on independence (see section 5.2.1) holds that independent board members are more risk-taking than dependent board members. When analyzing this, the hypothesis is confirmed, but only in the sample excluding the employee-elected representatives.
10.1.1 Discussion of the findings Discussing this finding from a purely theoretical perspective means that while on one hand, independent directors have higher monitoring and verification costs, these are found – in this sample – to be outweighed by their ability to reject projects that are too safe. The information
41 Another reminder is given to the risk preferences of the five stakeholder groups outlined previously in the paper as they form the foundation for discussing the findings from the data analysis.
102 advantage of being dependent therefore does not seem to reduce the type-1 agency problem or detect the moral hazard problem (that top management proposes sub-optimal projects) as the alignment with top management seems to outweigh said advantage. In other words, it could be argued that shareholders do not gain from having dependent directors on the boards, because their assumed informative advantage is not greater than their alignment with the executive management. On the other hand, if the CEO’s risk preference is shifted from the risk averse agency prediction to the risk-seeking alternative prediction outlined in section 4.7.1, the discussion on the value of independent directors is turned to another angle: if Danish bank CEOs prefer risky projects, then it can be argued that independent directors are merely rubberstamping his proposals. However, this does not present an increase in the type-1 agency problem. While this may be counterintuitive – section 1.3 argues that the problem in Danish banks has been excessive loan-giving – the finding of this study is that in respect to shareholders, independent directors do what shareholders require even if that means unconditionally approving projects that are relatively risky, as the shareholders, being risk-neutral, can diversify their portfolio and thus seek risk to maximize the value of their call option held on the bank’s assets (see section 4.5). In other words, when the bankrupt state is not considered (and it can safely be concluded that it has not, since none of the actors prefer the bankrupt state), independent directors are better aligned with shareholders than dependent directors as they increase the bank’s risk-taking. The causality in this relation is less clear, however, because it depends on the CEO’s inherent risk preference, which is not the research focus of this paper.
10.1.2 The sample When discussing the impact of having independent directors on the board, it is imperative to note that nearly all outside board members have been deemed independent. Thus, the variation in risk-taking comes from two subsamples that differ considerably in size. Also, the literature and empirical research on dependent board members mostly stem from one-tier management systems in which the board is composed of executive employees. In Denmark, virtually all inside directors are not part of top management – and only few are middle-managers. The dependent outside directors present some sample issues as well, because they come nearly all from the same banks, which are parts of larger financial corporations – Nordea Bank Denmark, Alm. Brand Bank and Nykredit Bank. This may mean that the external validity of this particular variable is somewhat compromised in relation to the possible generalization of the finding, because other researchers in different corporate
103 governance areas than the Danish may yield significantly different results using the same sampling technique. In determining the degree of dependence of the individual, outside director, some sampling issues present themselves as well: unfortunately, due to banking secrecy and privacy in some business transactions as well as limitations on the investigate nature of this study, some links between the banks and the director may have gone unnoticed and will do so to the researcher contemplating to copy this research method on the particular field. For example, the management may be a distant relative to a director without this being common knowledge or surfacing in the online directories. Also, big borrowers (businesses, farmers, individuals) in banks are dependent, but will not immediately be recognized as such, as the banks’ individual outstanding loans are not available to the public 42 . Cross-directorships have been detected in some cases, but not between management and directors and vice-versa, but only in the form of directors taking seat on each other’s (non- bank) firms’ boards. These directors have been deemed independent of the bank in question, though they may owe their place on other boards to the place on the bank’s board, thus making them dependent on having the bank board seat. These types of dependencies are nearly impossible to detect in a research design like the one deployed in this thesis. It should be noted that the high percentage of independent directors is not (only) attributable to the research design. Danish companies have a strong tradition of separating ownership and control when the companies grow bigger and certainly when they reach the size of most of the banks in this sample in this study (Thomsen 2008)
10.1.3 Implications The Danish Recommendations on Corporate Governance recommend that a majority of directors be independent to ensure that special interests do not influence the running of the company – in this case, the bank. Insofar as the “special interests” refers to that of the shareholders at the expense of other stakeholders of a bank as a financial intermediary (see section 3.2), the findings of the data analysis in the previous section do not unconditionally support that the board should be as independent as possible . While perhaps controversial, having a completely independent board would – ceteris paribus – increase risk, which for other stakeholders is not necessarily desirable. The implication of this is that the bank governance system benefits the shareholders – and the shareholders alone – when following
42 Although some details of the board members’ combined loans are available in some of the annual reports, the nature of the loans is not disclosed.
104 the recommendation at the expense of the remaining stakeholders it was originally established to (also) shield. It should be noted, however, that ‘dependence’ comes in many other forms than the ones surveyed and accounted for in the analysis at hand as described just above. For example, a considerable share of directors hold just one board seat and are possibly dependent on the income derived from this.
10.2 Board experience The alternative hypothesis on board experience is that experienced board members approve more risk-taking than non-experienced board members. The hypothesis was rejected, but reversed with significance in both model 1a and 1b.
10.2.1 Discussion Experienced board members who hold five or more years of board experience when entering the board are found to reduce risk-taking in Danish banks, which can be somewhat puzzling: the research in the field points relatively unanimously in the direction that more experience results in more efficiency, which is assumed – considering agency theory – to increase alignment with the risk-neutral shareholders, who are at conflict with the risk-averse manager. Yet experience proves to reduce risk on Danish bank boards. To discuss this, alternative inferences about the directors’ skill sets and the CEO’s risk preference have to be made. As outlined in section 4.7.1, the CEO can have alternative risk- seeking preferences. In this case, the result can be viewed in the light that experienced board members recognize that while shareholders would want the risk-seeking CEO’s proposals, no one benefits if the bank enters the bankrupt state. An experienced director might be better at judging when risk moves from an optimal point seen from the shareholders’ view (point A in model 4.3) into the financial distress modes (and possibly into bankruptcy), because of his assumed longer experience in the business world and his possible better understanding of business cyclicality. This is obviously nothing more than a discussion point, as the findings as such do not display this kind of relation per se . However, continuing in the same line of thought, this would align the theoretical proposition of experience leading to efficiency with the findings of the paper – and with the actual observations of the studied period; some banks have entered financial distress and/or have gone bankrupt, which for all reasons would not be desired by any of the stakeholder groups. Therefore, experienced board members may have been better suited to recognize an ‘optimal’ risk structure, not just to find the maximal linearly increasing amount of risk.
105 On the other hand, the call option theory as seen from shareholders’ perspective (see section 4.5) does not prescribe having representatives limiting risk for them – thus implicitly diversifying their risk within the single investment as it is a standard assumption that they can better diversify this risk on their own in the capital market. In this regard, experienced directors seem to be performing a job that shareholders did not appoint them to do.
If anything, the result can be discussed from an angle that assumes less-than-perfect information about risk, meaning an angle that deviates from the standard assumption as well: if shareholders cannot obtain information on risk taken in banks, they cannot effectively diversify their portfolios and then, experienced directors and their hypothesized lower monitoring and verification costs may opt for the second-best solution; diversifying shareholders’ risk for them within the company when they are not able to themselves because of their informative disadvantage.
10.2.2 The sample The sample sizes in the subsets – inexperienced vs. experienced – are relatively large due to the distribution of experience: 51.69 % of the total sample and 68.80 % of outside directors are experienced, which leaves the opposite group large enough to infer behavior from it. Furthermore, data for experience as a variable is easily obtained as directorships in CVR- registered companies in Denmark are registered and assembled in directories. However, the quality of the experience is debatable, because it is assumed that ‘board experience’ is gained from all directorships in organizations. It might be that the experience that is necessary for sitting on a bank board is not derived in a proper sense from other organizations, because the bank is a different entity (see section 3.2) than an industrial firm, for example. This may point to a different possibility for testing, one in which only board experience from similar companies is accounted for.
10.2.3 Implications As the hypothesis is reversed, the findings of this thesis do alter the general understanding of what ‘experience’ as a characteristic in the board member contributes with to a board. If experienced directors decrease risk-taking, then the type-1 agency conflict (as outlined in section 4.4.1) is, all other things equal, exacerbated by the appointment of those. However, the type-3 conflict is reduced, as is the possibility that the society surrounding the bank will have to make good on its insurance promise to depositors. In fact, the finding corroborates the calls for better governance (and better board directors) of Danish banks, because those pleas
106 come from an angle that presumes that the banks exist to serve the whole array of stakeholders.
10.3 Gender Gender is insignificant to the loan/deposit rate in both model 1a and model 1b and thus, the null hypothesis is not rejected
10.3.1 Discussion The fact that the gender variable does not return a result is a finding in itself: First of all, few female outside directors are represented on boards, but so were dependent outside directors and they acted measurably different than their independent counterparts, which women on bank board seem not to do. The low absolute number of female directors is not sought to be explained in this thesis, but that only 8.53 % are female may spark some debate. However, the hypothesis outlined was that diversity in general, as represented by women in this study, might increase communication costs but lower verification and monitoring costs, and this trade-off cannot be said to have been resolved. On the other hand, women as a proxy for diversity might not be a sound one either. A conceivable explanation of the findings could be that females on bank boards do not get a say in the decision controlling process and hence approve and vote with the majority of the (predominantly) male directors. On the other hand, the results obtained in this extensive study of Danish bank boards can be discussed from an angle that prescribes that as a predictor of behavior on the bank board, gender is not an explanatory factor – which means directors behave on all other grounds that their gender. This cannot support a ‘discriminatory’ allegation against bank boards; rather the interpretation is that men and females act alike on bank boards and that diversity in gender representation does not, as measured in this study, influence on risk-taking.
10.3.2 Sample The sample is found to be highly valid; gender is a demographic, easily observed variable. As a proxy for diversity, however, other sample methods might yield stronger subsets to test, which in turn may yield different (and significant) results.
10.3.3 Implications The implications of the finding on gender and its influence on board director behavior should be that claims of forcing at least 40 % women on Danish bank boards (see section 5.2.3)
107 would not change the governance system or function of Danish banks 43 . If females on bank boards act as their male counterparts, then other diversity features should be considered if diversity as a knowledge enhancer is the goal. Women, it seems, are just as risk-taking/risk- reducing as men in this sample.
10.4 Multiple directorships The hypothesis was rejected as board members who returned 1 in the collection sample (and thereby hold 3 or less simultaneous seats) take less risk than those that hold more than three seats.
10.4.1 Discussion On one hand, the finding somewhat resolves the reputation vs. busyness hypotheses issue (as described in section 5.2.4). It seems, from this study, that directors who hold many board seats are more aligned with the shareholders and approve riskier projects. On the other hand, if shifting the CEO’s risk preferences, the ‘busy’ directors may return as being more risk- taking because they are faced with a risk-seeking CEO and do not have the time to carefully verify the proposed projects. Either way, the type-1 agency problem is reduced when the directors holds more than three seats – ceteris paribus – because he allows more risk to be taken, thus increasing the value of the shareholder’s call on the assets of the bank. The finding should be specified somewhat, though, to provide external validity: the finding is not that more board seats are better, the finding is that directors who hold three seats or less take less risk than the other directors.
10.4.2 The sample The findings should be taken with certain precaution, though. The sample includes a third of the outside directors who just hold one seat – even though the mean among the outside directors is 5.83 seats. Therefore, the linearity in the method might be questioned (even if it was sought remedied in this study by employing a dummy variable), because the sample includes board members with twenty, thirty and eighty-one board seats. There is certain variation between the banks that the study design does not account for; many of the board members in smaller, local banks who have not seen their loans increase much all hold few seats, while some banks are directed by a board whose aggregate simultaneous directorships are well into the three digits.
43 The gender political issue of equal representation is not addressed in this thesis, as it probably calls for (at least) a thesis on its own.
108 10.4.3 Implications From a shareholder perspective, the implication of this study in respect to whether to elect a ‘busy’ director is that a director with more than three board seats at the same time will, all things equal, be predicted to let more risk pass through. For the other stakeholders, the debt agency is reduced for the debtholders and so is the insurance possibility for the insurer when board members have three or less simultaneous seats. Management will be better aligned with a director who does not have many seats if the theoretical position of managerial risk averseness holds true. The Danish Recommendations on Corporate Governance recommend few seats, but if to ensure shareholders’ interests are taken care of, the findings of the thesis contradict this recommendation.
10.5 Tenure Hypothesis 5 was that board members with several years’ tenure approve more risk-taking in Danish banks than board members who are relatively new in the position do. The null hypothesis was rejected and the alternative hypothesis was confirmed.
10.5.1 Discussion On one hand, the expertise hypothesis seems to hold – seasoned board members allow more risk which is in alignment with the risk-seeking shareholders. It could be argued that tenured board members have lower monitoring costs as their company-specific knowledge increases, thus enabling them to ratify the projects that carry more risk. Also, the reputation hypothesis (as described in section 5.2.2 on board experience) could be at play: tenured board members may be aware that the signaling effect to the managerial/director labor market improves when the member acts in alignment with the shareholders, which would increase the odds for re- election. On the other hand, if the CEO of the bank is not relatively risk-averse, but is instead motivated by other incentives (see section 4.7.1), it could be inferred that the manager- friendly hypothesis actually holds by the findings from the data analysis. It could be suggested that after a prolonged term on the bank’s board, the director becomes complacent and acts with inertia and consequently approves the CEO’s proposals without regarding the actual NPV of them. It must be noted – again - that this suggestion comes from a radically opposite assumption on the CEO’s incentives. This complicates the applicability of the finding: if the CEO is risk- seeking, the management friendly hypothesis holds and in this case the board member’s
109 impact is, at best, minimal. Regardless which CEO risk preference is assumed though, the finding is that experienced board members take more risk.
10.5.2 The sample The data is deemed to be valid as it was easily obtained and verified.
10.5.3 Implications The finding that board members, who have spent relatively many years on the bank’s board take on more risk can be a valuable information to shareholders when electing the board. However, due to the characteristic being one that relies on that very action – the re-election – the shareholders might face a trade-off, in which the precise contribution of other board member characteristics becomes important: if a board member lacks other characteristics found to be conducive to risk-taking, but has directorship tenure – should he be re-elected? The implication is then most probably that the Standard & Poor’s suggestion holds; whether tenured board members are ‘good’ to re-elect should be evaluated on a case-by-case basis. Tenured board members seem to reduce the type-1 agency problem , but electing tenured board members will increase the type-3 agency problem . Furthermore, the re-appointment of a seasoned board member in the bank will increase the possibility that the society as insurer is held liable for the bank’s actions through the deposit insurance.
10.6 Financial education Hypothesis 6 stated that financially educated directors increase risk-taking. The finding on financial education is that directors who hold a master’s degree in finance, economics or accounting (or the equivalent thereof) do take on more risk as directors in Danish banks. The alternative hypothesis from section 5.2.6 was therefore confirmed.
10.6.1 Discussion To get around the possible explanation of why directors with education in the field choose to take on more risk, the incentives need to be revisited. Financially educated directors may be better aware that shareholders, by whom they are elected (or through the representative council, which is elected by the shareholders) prefer more risk than their otherwise-trained colleagues. Also, they may be more familiar with the CEO’s incentives and thus seek to re- align these with those of the shareholders. On the other hand, financial education may also in itself be a characteristic leading to more risk-taking because of a perceived advantage in handling risk: section 5.2.6 is revisited in which it was found that firms with financially trained directors are higher leveraged to back
110 this claim. It could be speculated that financially trained directors are more prone to give incentive payment schemes to the top management following the idea that they take on more risk (in alignment with shareholders’ wishes), but the correlation study does not display such attributes. It must be noted, though, that it does not seem to emerge from the study that financial education on the bank’s board prevents financial distress or bankruptcy – the banks which have faced loan/deposit rates that were troubling 44 (Danske Bank, Amagerbanken) or have gone virtually bankrupt (Roskilde Bank) did have financially trained directors on board. Thus, the finding should be interpreted for what it is: financially educated directors take on more risk, not for what it could be, namely that ‘financially educated directors are better at assessing risk’. The study provides no such indication of the latter, but evidence of the further.
10.6.2 Sample In Danish banks, few directors are educated while relatively many boards have no financially educated representatives. According to law, one director must be trained in accounting, but a director can be so at diploma-level and he would therefore not be counted into this sample as financially educated. Alas, the threshold for deeming a director financially educated may have been set slightly high.
10.6.3 Implications The finding on financial education should not bring around much new knowledge, as the hypothesis – built on previous studies - was confirmed. Shareholders should want financially trained directors (as long as the bank is in a solvent state); managers will find themselves at odds with a financially trained director, as will debtholders, because the director wants more risk. However, it might be beneficial to society to know that this specific characteristic of a bank board director leads to more risk: the public discussion (as outlined in section 5.2.6) has centered around general incompetence of the banks’ boards and around the alleged lack of knowledge on the boards in general. The assumption, it seems, has been that financial knowledge would have bettered the directors’ ability to detect which actions that would bring the banks into the distressed state. The findings of this paper should disentangle this
44 It is acknowledged that if all loans are of superior quality, having a high loan/deposit rate is not an issue. At “normal” rates of bad loans vs. good loans, however, a high loan/deposit rate is, all other things equal, more risky than a low. See also section 7 on risk.
111 perception a bit; financial knowledge leads to more risk , not to “more risk until a certain point and from there on, less risk (to avoid distress)”.
10.7 Board size The hypothesis from section 7 was that smaller boards will take on more risk. The null hypothesis could not be rejected for neither model 2a nor model 2b.
10.7.1 Discussion The findings of this thesis do not confirm that smaller boards are more effective, if by effective is understood improved alignment with shareholders. In fact, the p-values of 0.77 and 0.99 respectively indicate that ‘board size’ as a board-level characteristic is about as random a predictor for risk-taking as they come. On one hand, the results could indicate that in Danish banks, no generalizations can be made with regard to the trade-off between communication and coordination costs on one side and the knowledge base, which is presumably larger in boards with more directors (see section 5.3.1). Alternatively, a daring suggestion might be that the market is effective in correcting the individual board’s size to the needs of the individual banks, which might differ from bank to bank (it is described in section 5.3.1 that the reason for finding that small boards are more effective is because of market imperfections in correcting the board structure). On the other hand, the research leading to this thesis revealed that circumstance and politics seemed to be as much a predictor as anything else – in bank mergers, for example, board sizes have in some cases almost doubled (Den Jyske Sparekasse has 21 different directors in the sample period), which should at least temporarily impede efficient coordination within the board, all other things equal.
10.7.2 The sample The sample is relatively strong in the sense that board sizes are easily observed and verified by the outside researcher. The use of the average board size may be a limitation to its external validity, as single-year samples will exaggerate the results obtained (boards that increased significantly over the period count with both the larger and the previous board in this study). However, since the predicting quality of board size to Danish bank boards’ risk-taking propensity is not established, this is a highly speculative suggestion. The one pattern detected is that banks that are part of a larger financial corporation tend to have smaller boards, in part because they are solely directed by appointed insiders, whereas independent banks have outsiders as well as insider employee-elected representatives.
112 10.7.3 Implications The first implication of the finding that board size is a random variable related to risk-taking is that the Danish Corporate Governance Recommendations are right in the statement that boards should not be too large to allow a constructive debate and efficient governance. However, ‘too large’ is an elastic term in this case, as small boards as well as larger boards have taken on low levels of risk as well as higher levels of risk.
10.8 Incentive programs The hypotheses on bonus schemes as well as stock payment programs were that these increase risk-taking in Danish banks. The hypotheses are confirmed for both model 2a and 2b.
10.8.1 Discussion Incentive programs, theoretically, align shareholders with managers. This is the finding of this paper as well and stock (option) plans emerge as the most explanatory variable of all tested variables in this study. Danish bank managers seem to be motivated by having a part of their salary be dependent on performance as measured by specific goals in terms of having bonuses or by movements – upwards – in the stock price. As described in section 5.3.2, this amounts to the manager’s total wealth being less dependent on the fixed WH part of his total wealth, W, and more on the variable WS, which all other things equal lessens his interest in holding the bank as a going concern and increases his focus on generating stock returns. This is an important finding because this might connect several of the points made earlier in the paper: if the bank manager is motivated by variable pay, which it is found that he is, then his focus shifts away from keeping his job – the very tenet of the assumption that the bank manager is risk averse - as the source of income from his human capital investment amounts to less of his total income when part of his salary is variable with the annual results or the stock price. While it is not tested if this particular relation has caused risk-taking to amounts that have brought banks in distress, it is tested that incentive programs increase risk-taking quite significantly. This finding also backs one of the central theoretical assumptions of the paper, in the second order, namely that shareholders will view their stock as a call option of the firm’s assets. This is because their behavior can suddenly be studied through the manager: when the manager becomes a stockholder himself, risk-taking in the company is higher. On the other hand, one might argue that awarding the manager an incentive program will not in itself increase risk, because the board is the ratifying body of the governance, the manager is not. However, it does lend some support to the somewhat alternative suggestions that
113 ‘busy’ directors are merely rubberstamping a risk-seeking manager’s proposals (as discussed in section 5.2.4), because the likelihood that the CEO is risk-seeking increases, thereby increasing the possibility that the alternative risk preference prediction of the CEO is the actual one. If risk-seeking managers themselves initiate a stock or bonus payment program, the board itself should be equipped to monitor whether the manager is motivated by other things than what strict economic theory would predict (Merchant, Van der Stede 2006, Bechmann, Raaballe 2009) – and whether or not the manager wants stock options because he deems that the net present value of his salary is smaller than the net present value of cashing in on the stocks awarded for inflating the stock price.
10.8.2 The sample The sample suffers to some extent from the fact that the actual terms of the stock or bonus programs are not specified in the obtainable data. If options are awarded without term of deferred exercise dates, the incentive to quickly inflate the stock price (especially if the long- term franchise value of the bank as a going concern is small) will be strong. Such inferences have not been made, however, because the nature of the incentive schemes is unknown in most parts.
10.8.3 Implications The implications for the shareholders are straight-forward: if risk is desired, equip the management with incentive programs. Debtholders on the other hand can use this study as an argument to not want to deposit money in a bank that has incentive programs, which leads directly to the implications for society: as guarantors of deposits, the insurance liability becomes more likely with the use of incentive programs in banks.
10.9 The CEO versus the board The hypothesis from section 10 is that the relatively longer the tenure of the CEO, the lower the risk-taking in the banks. The related null hypothesis was not rejected for model 2a, but was rejected and reversed for model 2b.
10.9.1 Discussion This discussion relates somewhat to the discussion on board director tenure. In Danish banks, the CEO has on average almost twice as much tenure as the board on average has. On one hand, one might argue that this would reduce risk-taking if tenure is equated to power and influence; a concept of a much deeper social study which is not the aim of this thesis. It is the
114 aim to explain, however, that risk-taking is not reduced when the CEO has been sitting relatively long in his seat. On the other hand, risk-taking is increased which may reflect either of two mechanisms: on one side, a ‘young’ board will be very vigilant and keep the focus on shareholder alignment high in mind. On the other side, a seasoned CEO may have an increased preference for risk-taking, which is supported by revisiting the W=WH+WS+W0 equation from section 5.3.2: even if the CEO is not working under an incentive program (thus eliminating WS), WH decreases gradually over time as his retirement nears. Bechmann and Raaballe (2009) support this, as they find that Danish CEOs of bank boards are only fired if the company goes into serious financial distress. Thus, the CEO can rationally plan to keep his job, which makes his calculation of the value of WH more likely to be precise. The reason for wanting more risk as WH grows smaller with time are the possible reasons outlined in section 4.7.1 on alternative risk preferences of the CEO. It should be noted, of course, that this is merely a discussion of potential grounds for the observed behavior; the findings do not support such inferences in themselves. What they tell is merely that the longer the CEO has been in place relative to the mean of the board, the more risk has been taken in Danish banks.
10.9.2 The sample The data for the input of this variable were relatively easily obtained and verified. Other calculation methods may yield different results – one could assign dummy variables for which of the governing parties that has been sitting the longest, or instead of assigning the CEO- board relationship a ratio, their values could be subtracted from one another generating a range from -1 to +1 (although only nearing the extremes as both the CEO and the board always have some tenure).
10.9.3 Implications The implications of this finding are that shareholders should want the board to keep a CEO in place, should they wish risk. The debtholders are at odds with this as the type-3 agency problem increases with the CEO’s relative tenure to the board. The society faces the same conflict as the debtholders.
10.10 Partial conclusion In this section, the findings of the data analysis were discussed with a background in the theory and empirical research previously outlined. The samples, from which the variables were taken, were criticized and finally, the implications to the five stakeholder groups were evaluated as well.
115 It was discussed that independent board members are aligned with shareholders and approve more risk-taking; thus, the increased monitoring costs were argued to be outweighed by the fact that the independent members do not have an incentive to side with the CEO. The sample was however critiqued because most non-employee elected members were found to be independent. Experienced board members were found to reduce risk-taking and it was discussed if this might be a result of increased awareness of when risk moves from an ‘optimal’ point to an ‘excessive’ (for all stakeholders) point. On the other hand, it was argued that shareholders do not need the board to diversify risk on their behalf. The fact that gender did not return any results was discussed from two angles; one that assumes that the low absolute number of women on Danish boards means that the female directors do not get a say when deciding on projects, and from another angle that argued that the reason no result was obtained was because men and women act alike on bank boards. Having directors holding more than three simultaneous board seats were found to increase risk-taking in Danish banks. This was argued to be supportive of the reputation hypothesis from the hypothesis, but could also be argued to be a result of risk-seeking CEOs that went unchecked by the ‘busy’ directors. Board tenure by the individual member was found to be positively related to risk-taking. This was discussed to be supportive of the expertise hypothesis; board members with tenure on the board get better at understanding the shareholders’ needs and incentives. On the other hand, it was discussed that if the CEO is risk-seeking, it might just be that board members become complacent after many years on the same board and approve his proposals without careful consideration. Being financially educated as a board member was found to be positively related to the approval of risk-taking. It was argued that educated board members within the banking field might see themselves as better at managing (higher) levels of risk. Board size emerged as a random variable. It was discussed that markets do not determine board size, but politics and other non-economic dynamics do. The existence of incentive programs was found to significantly increase risk-taking in Danish banks. It was discussed that the higher the proportion of the CEO’s salary that comes from incentive programs, the less value the CEO will put on keeping the bank as a going concern, thus the more risk will he be comfortable with taking. The relative parameter of CEO vs. board tenure was measured as positively related to risk- .taking (when the CEO has been in his chair longer than the board on average, risk increases). This was argued from the CEO’s point of view; when the net present value of his salary
116 decreases with time to retirement, his incentives for accomplishing ‘other’ (and more risk- seeking) goals would, ceteris paribus, increase.
117 11 RECOMMENDATIONS
At this point in the thesis, the research question has been almost fully answered: the characteristics of the composition and structure of the boards of directors in Danish banks have been found to influence risk-taking and the degree to which has been outlined as well. This leaves only one issue behind: to whom is this information relevant and how can it be applied. Highlighting these issues is the purpose of the following section. The final part of the thesis aims to combine the risk-taking behavior with the regulatory and societal environment by proposing three different incentive-aligning models which incorporate the findings of the study. It should be noted that this part serves as an extension of the thesis and the models are not supposed to be detailed, ready-for-use policy initiatives. Rather, they double as this thesis’ suggestions for further research by sketching roads down which the economics/finance/social science researcher may take the findings of this thesis. First, the stakeholders and their interrelation as outlined in section 4.6 are presented graphically. Next, three proposed models for mitigating risk in Danish banks are outlined.
11.1 The bank and its environment Until this point, the study at hand has assumed that boards of directors should act solely in the interest of the shareholders, as this is what laws, regulations and soft law in general suggest that boards should do. While certainly true for most companies, the banks are special companies (see section 3.2), whose actions were argued to impact larger groups of the population (see sections 1.3 and 3.3). The assumption that banks’ boards should always act in the interest of the shareholders is relaxed and challenged a bit in the following: it has been established that the some board characteristics influence risk-taking (in sections 9.5 – 9.6.4) and it was established earlier that some banks, in the eyes of the public, have taken on too much risk, as witnessed by the bankruptcies or de-facto bankruptcies in the sector. Thus, a clear overview of the bank’s actions is in order prior to discussing whether the current corporate governance recommendations are optimal to banks:
118 Figure 11.1: The bank’s stakeholders; impact and influence
Shareholders
Stakeholders: Board Society Depositors Creditors CEO Management
Bank
Source: Own contribution The figure shows the relation between the shareholders: the blue and grey arrows symbolize influence and impact, the red barrier marks the missing relation between the non- shareholding stakeholders and the bank’s supreme governing body.
Thus, the non-shareholding stakeholders can be negatively affected by the bank’s actions. The reason for this is, as hinted in section 3.2, that the bank is not just a private company, but a financial intermediary handling a function crucial to a well-working, modern society. When this function does not run smoothly, the effects are widely felt. It is the view of this thesis that the bank’s governance model should take this into account. The banks’ actions influence the society and financial business environment three-fold: First, the bank’s risk-taking may lead to bankruptcy, which in effect exercises the put option the state has issued in the form of deposit insurance , causes uncertainty among consumers and lead to suboptimal allocation choices as argued in section 1.1 on motivation. The deposit insurance itself spurs additional risk-taking from shareholders, as argued in section 4.5, and the liability resulting from having deposit insurance should take this into account. Next, the bank’s (excessive) risk-taking may lead to contagion in the form of forcing other banks to risk-adjust their portfolios, leading to sudden write-downs, which could put the funding at risk.
119 Finally, one bank’s reckless risk-taking may lead to international uncertainty about Danish banks in general, making international interbank funding unavailable to the Danish banking sector as a whole, causing a nation-wide funding liquidity crisis. In this thesis, it is the standpoint that these externalities are not fully accounted for in the corporate governance climate surrounding the banks in the researched period and therefore, it is the view that the bank should compensate for these possible externalities to increase economic efficiency/avoid the impacts outlined in section 1.3. As bank boards’ composition and structure have been found to be an endogenous factor in determining the risk-profile of the bank in the analysis of this paper, it can be derived that the board’s inner workings can be altered by changing either the components of the board or by changing the incentive structure surrounding it. The former would entail dictating which people the shareholders would be allowed to elect to the board 45 , which is not deemed a realistic scenario 46 . Therefore, three incentive-adjusting models are proposed, which all rest upon the theory, the empirical studies and this thesis’ study in their formation 47 . The purpose of the models is as said to align the externalities of running a bank.
11.1.1 The Actuarial Model As the bank failures in the latter years of the research period have had visible economic impacts for non-shareholding stakeholders, whom the banks have most probably not compensated these non-shareholding stakeholders for, the insurance view would be that banks have not paid a (high enough) risk premium for the deposit insurance 48 and that they should do so. Knowing that the composition and structure of the board matters, the insurer (in effect, the state) could price these two factors into the actuarial evaluation of which risk premium the bank should pay. The underlying idea would then be that banks have insured themselves and that society would not stand to lose should the bank fail. However, externalities are inherently hard to price, also in this case. Even though measurable differences exist in the risk-taking behavior following the structure and composition of the
45 Not to confuse with dictating which specific people that could sit on the board. 46 Shareholders would have very little incentive to buy the bank’s shares if the board was appointed by e.g. a government agency, because they would lose all and any impact on the bank’s management system. 47 Also, this means that theory already explained would be redundant to re-iterate here. 48 Although the bank does not receive the insurance in the case of default (depositors do), the insurance is valuable to the bank, as it first of all severely limits the possibility of a bank run, leaving the bank in great funding troubles, and second of all it lets the bank take greater risks, because debtholders cease to discipline the bank.
120 board, the calculation of the possible externalities with one type of board (and governance system in general) versus the other would be extremely hard to price accurately, partly because they are dependent on international business-cycle effects, too (for example it is hard to price the cost of not being able to get funding in the interbank market at a given interest rate). Also, since contagion and uncertainty can be caused by any one bank in the pool of banks, it would be troublesome to assign the cost of the premium fairly to each bank. Therefore, two other models, which both take the view that bank failures should be avoided altogether are suggested below:
11.1.2 The soft law model – with hard law extensions As determined in the thesis, no specific soft law for the banking industry exist; instead, banks adhere (to some extent) to the overall corporate governance recommendations. Following the findings of this thesis, a specific set of corporate governance codes could be drafted to include the knowledge put forth here. These codes should include the whole array of stakeholders because of the banks’ special role in society and should give specific recommendations on the knowledge, experience and busyness level of the individual directors to ensure lower levels of risk-taking, as well as recommendations on minimizing incentive programs, as these seem without a doubt to increase risk-taking. Furthermore, a specific set of bank corporate governance codes could recommend that the CEO be elected by the general assembly at specified time intervals, as the CEO’s relative tenure matters in risk-taking and control in the bank, according to this thesis. The control function of this model would be the managerial labor market and the general populace – but also the DFSA, who would be equipped to replace boards not complying with a certain percentage of the new recommendations 49 .
11.1.3 The society model The final model could be a society model in which all banks must have a government- appointed director, who reports to the DFSA, which in this model would be equipped with extra power, too. This would secure representation of the non-shareholding stakeholders and thus mitigate the type-3 agency problem. It is a well-known solution, too, as banks previously had a government-appointed director on the board. This practice could be revived.
49 The DFSA has already had its powers increased, but it is proposed that they should be even stronger in this model.
121 The relation to the findings of the thesis are that having a responsible government representative on the board would leave the bank with more freedom to choose its board and its risk-level, as long as accordance with the appointed director’s judgment on whether the risk-level was appropriate at any given time. This appointed member should be equipped to order the CEO of the bank to reduce the risk-taking (for example, the loans) at once and before the externalities described above manifest themselves as liabilities to the society.
11.1.4 Final recommendation In summary, the thesis recommends a mix of all three models. It is the viewpoint that the bank and its supreme governing body, the board, should pay a risk premium for having deposit insurance and that this premium should reflect the risk-level of the bank. It is also recommended that financial institutions, which exist for more reasons than to create shareholder wealth, be given specific corporate governance codes, based in actual research. Finally, the re-introduction of a government-appointed director is recommended by this paper, to ensure representation of all groups that could be economically affected by the bank’s actions.
11.5 Partial conclusion The final part of the thesis was found to serve as an extension, providing ground for further research. The recommendations of the thesis were found to be that the mismatch between those who benefit from the bank’s actions and those who stand liable, should the bank fail, should be solved by applying a combination of three models: the actuarial model, which prescribes charging banks with a fair risk premium for the insurance they receive, the soft law-model, which prescribes altering the corporate governance recommendations in specific bank version and finally, the society model in which the non-shareholding stakeholders are represented on the board of the banks.
122 12. CONCLUSIONS
The thesis was motivated by the criticism directed at the Danish banks and their boards in particular in the wake of the financial crisis. This led to the research question: “Have the structure and composition of Danish bank boards affected risk-taking in the period from 2003-2008?” It was concluded that some aspects of the structure and composition have affected the risk- taking to a significant degree.
The thesis investigated the research question deductively through the construction of ten hypotheses; six hypotheses regarding the composition of Danish bank boards, four regarding the structure. The hypotheses emerged from a thorough theory review of the corporate governance field with a section dedicated to agency theory, as well as from detailed literature reviews on the theory and empirical studies within the fields. The sample was constructed from the 67 largest Danish banks, comprising more than 95 % of the total working capital in the Danish banking industry. The dependent variable best suited to reflect the research question’s “ risk-taking” was determined as the loan/deposit ratio of the Danish banks in 2007. The answer to the research question was found through the subsequent data analysis, building on 4.829 manually collected, unique data points. The thesis found that the structure and composition of Danish bank boards in the period 2003-2008 have indeed affected risk-taking in Danish banks. The basis for this result can be summarized as follows:
• Independent directors were found to allow more risk-taking than dependent directors*. • Experienced board members were found to allow less risk-taking than inexperienced ones (less than five years of board experience) • Directors with more than three simultaneous directorships were found to allow more risk-taking than directors with three or less directorships • Directors were found to allow increasingly more risk as their years on the board increases • Directors with a master’s degree in finance, economics, business economics or accounting were found to allow more risk-taking than those without such an educational background • The existence of incentive programs (bonuses and stock (option) plans) was found to be positively related to risk-taking
123 • It was found that if the CEO had been in place longer than the board on average, risk- taking had been increased relative to a situation in which the board had served longer than the CEO*.
*: Only in the models without employee-elected representatives The parameters ”gender” and ”board size” were both found to be random in relation to the risk-taking of the bank. It was discussed that independent board members do not seem to be impaired by higher monitoring costs as they do increase risk-taking, but also that the sample was flawed by its homogeneity. It was also discussed whether experienced board members might be better at recognizing a non-linear relation in risk-taking and therefore, could be risk-reducing as well. On the other hand, the experienced members might be diversifying risk unnecessarily. Furthermore, the thesis suggested that women, who make up under ten percent of outside directors, might not have a say at board meetings and therefore do not influence risk-taking. On the other hand, female directors might just have risk preferences equal to those of males. Directors holding more than three simultaneous board seats were argued to be conducive to risk-taking because of their attention to the managerial labor market and thus, to shareholders. However, it also has to be considered that directors with many simultaneous board positions might just be rubberstamping a risk-seeking CEO’s proposals. A board director with longer time on the board was argued to be good at understanding the shareholders’ needs and incentives. However, that must be weighed against the possibility that a board member with long tenure could be manager-friendly to a risk-seeking CEO. Financial education as a risk- taking trait in a director was suggested to stem from these directors’ perceived better understanding of risk. Nevertheless, there was no evidence that financially educated board members prevented hazardous levels of risk. Within the confines of the research at hand, board size was seen to be a random variable either because of smoothly functioning market forces or because board size is determined by other things than market economics, such as politics. Incentive programs emerged as the most powerful explanatory variable in risk-taking in Danish banks, which was discussed from the perspective that the more the CEOs salary that stems from performance-variable pay, the less value he places on keeping the bank going as a concern. Finally, it was discussed that CEOs with longer tenure than the average board may recognize that their salary’s NPV from keeping the bank a going concern gradually becomes smaller and therefore, they might be motivated to take more risk for reasons of prestige, fame etc.
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132 14 TABLE OF CONTENTS - APPENDICES
1 COMPLETE LIST OF THE BANKS INCLUDED IN THE SAMPLE 136
2 THE COMPLETE DATA COLLECTION OF ALL 749 BOARD MEMBERS 137
2.1 DANSKE BANK 138
2.2 NORDEA BANK DANMARK 139
2.3 JYSKE BANK 140
2.4 NYKREDIT BANK 141
2.5 SYDBANK 142
2.6 SPAR NORD BANK 143
2.7 VESTJYSK BANK 144
2.8 AMAGERBANKEN 145
2.9 ARBEJDERNES LANDSBANK 146
2.10 FORSTÆDERNES BANK 147
2.11 SPARBANK 148
2.12 ROSKILDE BANK 149
2.13 RINGKJØBING LANDBOBANK 150
2.14 ALM . BRAND BANK 151
2.15 SAMMENSLUTNINGEN DANSKE ANDELSKASSER 152
2.16 SPAREKASSEN SJÆLLAND 153
2.17 SPAREKASSEN KRONJYLLAND 154
2.18 FIONIA BANK 155
2.19 SPAREKASSEN HIMMERLAND 156
2.20 DEN JYSKE SPAREKASSE 157
2.21 EIK BANK 158
2.22 LÅN & SPAR BANK 159
2.23N ØRRESUNDBY BANK 160
2.24 SPAREKASSEN VENDSYSSEL 161
2.25 NORDJYSKE BANK 162
2.26 MORSØ SPAREKASSE 163
2.27 SPAREKASSEN LOLLAND 164
2.28 SPAREKASSEN FAABORG 165
2.29 SPAREKASSEN ØSTJYLLAND 166
2.30 DJURSLANDS BANK 167
2.31M AX BANK 168
133 2.32 DIBA 169
2.33 MIDDELFART SPAREKASSE 170
2.34 ØSTJYDSK BANK 171
2.35 AARHUS LOKALBANK 172
2.36 SPAREKASSEN THY 173
2.37 MORSØ BANK 174
2.38 SKJERN BANK 175
2.39 SPAREKASSEN HOBRO 176
2.40 FRØS HERREDS SPAREKASSE 177
2.41 GRØNLANDSBANKEN 178
2.42 SPAREKASSEN FARSØ 179
2.43EBH BANK 180
2.44 SVENDBORG SPAREKASSE 181
2.45 TOTALBANKEN 182
2.46 TØNDER BANK 183
2.47 DRONNINGLUND SPAREKASSE 184
2.48 BRØRUP SPAREKASSE 185
2.49 SKÆLSKØR BANK 186
2.50 KREDITBANKEN 187
2.51 SALLING BANK 188
2.52 BASISBANK 189
2.53 VESTFYNS BANK 190
2.54 NORDFYNS BANK 191
2.55 LOLLANDS BANK 192
2.56 SPAREKASSEN FOR NR. NEBEL OG OMEGN 193
2.57 SPAREKASSEN HVETBO 194
2.58 SPAR SALLING SPAREKASSE 195
2.59 SPAREKASSEN I SKALS 196
2.60 DEN ALMENNYTTIGE ANDELSKASSE MERKUR 197
2.61M ØNS BANK 198
2.62 SPAREKASSEN LIMFJORDEN 199
2.63 VORDINGBORG BANK 200
2.64 LOKALBANKEN I NORDSJÆLLAND 201
2.65 BANK TRELLEBORG 202
2.66 LØKKEN SPAREKASSE 203
2.67 BONUSBANKEN 204
134 3 COMPLETE LIST OF LOAN/DEPOSIT RATE FOR THE PERIOD 2003-2008 205
4 INDEPENDENCE 206
5 BOARD EXPERIENCE 207
6 GENDER / BOARD DIVERSITY 208
7 MULTIPLE DIRECTORSHIPS 209
8 TENURE 210
9 FINANCIAL EDUCATION 211
10 BOARD SIZE 212
11 CEO VS BOARD 213
12 CEO TENURE 214
13 SAS OUTPUT 215
13.1 REGRESSION OUTPUT MODEL 1A 215
13.2 REGRESSION OUTPUT MODEL 1B 218
13.3 REGRESSION OUTPUT MODEL 2A 220
13.4 REGRESSION OUTPUT MODEL 2B 222
14 CORRELATION SCATTER PLOT 224
15 CORRELATION OUTPUT 225
15.1 CORRELATION MODEL 1A 225
15.2 CORRELATION MODEL 1B 226
15.3 CORRELATION MODEL 2A 227
15.4 CORRELATION MODEL 2B 228
135 1 COMPLETE LIST OF THE BANKS INCLUDED IN THE SAMPLE
Acc. % of Capital at work Acc. % of working working (CW) in the % of CW in the capital in the Capital at work % of CW in capital in the Banks in the sample banking industry banking industry banking industry (CW) in the sample the sample sample Danske Bank A/S 1.378.964 0,5312 0,5312 1.378.964 0,5612 0,5612 Nordea Bank Danmark A/S 335.469 0,1292 0,6605 335.469 0,1365 0,6977 Jyske Bank A/S 162.864 0,0627 0,7232 162.864 0,0663 0,7639 Sydbank A/S 101.977 0,0393 0,7625 101.977 0,0415 0,8054 Nykredit Bank A/S 73.797 0,0284 0,7909 73.797 0,0300 0,8355 Spar Nord Bank A/S 47.148 0,0182 0,8091 47.148 0,0192 0,8547 Vestjysk Bank A/S 23.814 0,0092 0,8183 23.814 0,0097 0,8644 Arbejdernes Landsbank, Aktieselskab 22.755 0,0088 0,8270 22.755 0,0093 0,8736 Forstædernes Bank A/S 22.702 0,0087 0,8358 22.702 0,0092 0,8829 Amagerbanken Aktieselskab 20.715 0,0080 0,8438 20.715 0,0084 0,8913 Fionia Bank A/S 17.793 0,0069 0,8506 17.793 0,0072 0,8985 Alm. Brand Bank A/S 14.444 0,0056 0,8562 14.444 0,0059 0,9044 Sparbank A/S 13.482 0,0052 0,8614 13.482 0,0055 0,9099 Ringkjøbing Landbobank, Aktieselskab 12.027 0,0046 0,8660 12.027 0,0049 0,9148 Sammenslutningen Danske Andelskasser 12.008 0,0046 0,8706 12.008 0,0049 0,9197 Sjælland, Sparekassen 11.401 0,0044 0,8750 11.401 0,0046 0,9243 Kronjylland, Sparekassen 9.107 0,0035 0,8785 9.107 0,0037 0,9280 EIK Bank Danmark A/S 8.874 0,0034 0,8820 8.874 0,0036 0,9316 Himmerland A/S, Sparekassen 7.917 0,0030 0,8850 7.917 0,0032 0,9348 Lån og Spar Bank A/S 7.821 0,0030 0,8880 7.821 0,0032 0,9380 Nørresundby Bank A/S 7.736 0,0030 0,8910 7.736 0,0031 0,9412 Den Jyske Sparekasse 7.583 0,0029 0,8939 7.583 0,0031 0,9443 Sparekassen Østjylland 6.488 0,0025 0,8964 6.488 0,0026 0,9469 Sparekassen Vendsyssel 6.474 0,0025 0,8989 6.474 0,0026 0,9495 Morsø Sparekasse A/S 6.449 0,0025 0,9014 6.449 0,0026 0,9522 ebh bank a/s 6.320 0,0024 0,9038 6.320 0,0026 0,9547 Nordjyske Bank A/S 6.086 0,0023 0,9062 6.086 0,0025 0,9572 Lolland A/S, Sparekassen 5.985 0,0023 0,9085 5.985 0,0024 0,9596 Sparekassen Faaborg A/S 5.411 0,0021 0,9106 5.411 0,0022 0,9619 Djurslands Bank A/S 5.287 0,0020 0,9126 5.287 0,0022 0,9640 DiBa Bank A/S 4.810 0,0019 0,9145 4.810 0,0020 0,9660 Max Bank A/S 4.241 0,0016 0,9161 4.241 0,0017 0,9677 Middelfart Sparekasse 4.216 0,0016 0,9177 4.216 0,0017 0,9694 Lokalbanken i Nordsjælland a/s 4.165 0,0016 0,9193 4.165 0,0017 0,9711 Thy, Sparekassen 4.018 0,0015 0,9209 4.018 0,0016 0,9727 Østjydsk Bank A/S 4.017 0,0015 0,9224 4.017 0,0016 0,9744 Morsø Bank, Aktieselskabet 3.952 0,0015 0,9239 3.952 0,0016 0,9760 Grønlandsbanken, Aktieselskab 3.910 0,0015 0,9254 3.910 0,0016 0,9776 Skjern Bank, Aktieselskabet 3.756 0,0014 0,9269 3.756 0,0015 0,9791 Hobro, Sparekassen 3.559 0,0014 0,9283 3.559 0,0014 0,9805 Frøs Herreds Sparekasse 3.540 0,0014 0,9296 3.540 0,0014 0,9820 Farsø, Sparekassen 3.330 0,0013 0,9309 3.330 0,0014 0,9833 Aarhus Lokalbank Aktieselskab 3.178 0,0012 0,9321 3.178 0,0013 0,9846 Roskilde Bank, Aktieselskab Roskilde Bank A/S 3.139 0,0012 0,9333 3.139 0,0013 0,9859 Svendborg Sparekasse 2.580 0,0010 0,9343 2.580 0,0011 0,9870 Totalbanken A/S 2.219 0,0009 0,9352 2.219 0,0009 0,9879 Kreditbanken A/S 2.121 0,0008 0,9360 2.121 0,0009 0,9887 Brørup Sparekasse 2.051 0,0008 0,9368 2.051 0,0008 0,9896 Dronninglund Sparekasse 1.986 0,0008 0,9376 1.986 0,0008 0,9904 Skælskør Bank Aktieselskab 1.984 0,0008 0,9383 1.984 0,0008 0,9912 Salling Bank A/S 1.843 0,0007 0,9390 1.843 0,0007 0,9919 Tønder Bank A/S 1.800 0,0007 0,9397 1.800 0,0007 0,9927 Basisbank A/S 1.776 0,0007 0,9404 1.776 0,0007 0,9934 Nordfyns Bank, Aktieselskabet 1.734 0,0007 0,9411 1.734 0,0007 0,9941 Vestfyns Bank A/S 1.685 0,0006 0,9417 1.685 0,0007 0,9948 Løkken Sparekasse 1.457 0,0006 0,9423 1.457 0,0006 0,9954 Sparekassen Hvetbo A/S 1.452 0,0006 0,9429 1.452 0,0006 0,9960 Lollands Bank, Aktieselskab 1.447 0,0006 0,9434 1.447 0,0006 0,9965 Spar Salling Sparekasse 1.419 0,0005 0,9440 1.419 0,0006 0,9971 Nr. Nebel og Omegn, Sparekassen for 1.382 0,0005 0,9445 1.382 0,0006 0,9977 Skals, Sparekassen i 1.364 0,0005 0,9450 1.364 0,0006 0,9982 Møns Bank, A/S 1.233 0,0005 0,9455 1.233 0,0005 0,9987 Merkur, Den Almennyttige Andelskasse 1.060 0,0004 0,9459 1.060 0,0004 0,9992 Vordingborg Bank A/S 1.027 0,0004 0,9463 1.027 0,0004 0,9996 Sparekassen Limfjorden 1.010 0,0004 0,9467 1.010 0,0004 1,0000 Bonusbanken A/S* 1.566 bankTrelleborg A/S* 4.293
2.595.743 Capital at work in the banking industry 2.457.357 Capital at work in the sample Listed Banks * Are not included in the sample as their capital at work is from 2007
136 50 2 THE COMPLETE DATA COLLECTION OF ALL 749 BOARD MEMBERS
In order to provide the reader with an overview of the 67 banks, the 749 board members and 8429 unique data point which collectively serves as the core of this thesis’ investigation of the Danish bank boards, the following 67 appendices have been produced. Each of the 67 appendices illustrates the respective banks and the board members who served on the board in the research period. In order to maintain the structure of the paper, the appendix first presents the characteristics of the individual board member and subsequently shows the board level data. As described in section 6.4 not all board members served the entire period on the board and has therefore been weighted accordingly. In order to distinguish between the board members, who served the entire period and those who entered or exited the board in the research period, all board members have been color coded .
COLOR CODE TIME SERVED ON THE BOARD The board member served the entire period on the board The board member entered the board in the period The board member exited the board in the period The board member entered and exited the board in the period
Each individual variable is accompanied by a weighted column, in which the weight of the board member has been multiplied by the individual variable. At the weighted columns are all summed respectively and divided by average number of seats in the period for the particular board at the bottom of each column. These calculations illustrate the average value for each characteristic on the board in question in the research period.
ER indicates if the board member is an employee representative.
A few board member characteristics have been omitted and are therefore left blank, as they have either proven impossible to find or it has not been possible to validate the source.
50 The extensive research conducted for this thesis is evidently founded on an extensive pool of sources. It was found to be rather excessive should every data point be referenced. The annual reports, BIQ and Greens are therefore not sourced in the following appendices, but they have provided the information for the vast majority of the data points.
137 2.1 DANSKE BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directors Weighted Gender Weighted Independence Weighted Tenure Weighted
Ingeniør Alf Duch-Pedersen 1 00 11330 0 1 11010 Advokat Eivind Kolding 1 00116600 0088 Direktør Henning Christophersen 1 1 1 1 1 2 2 0 0 1 1 13 13 Direktør Mats Jansson 0,1667 1 0,17 1 0,1670 3 0,501 0 0 1 0,167 1 0,167 Professor Jørgen Nue Møller 0,8333 0 0 1 0,8330 2 1,666 0 0 1 0,833 8 6,664 Tidl. Direktør Peter Højland 1 11 11101000 1199 Professor Niels Christian Nielsen 1 1 1 1 1 10 10 0 0 1 1 19 19 Direktør Sten Scheibye 1 00 11880 0 1 11111 Professor Maiken Schultz 1 11113311 1199 Professor Claus Vastrup 1 11 11220 0 1 11414 Direktør Birgit Aagaard-Svendsen 1 1 1 1 1 18 18 1 1 1 1 14 14 Bank Ass. Helle Brøndum 1ER 00 001111 0077 Privat Rådgiver Charlotte Hoffman 0,50ER 0 0 0 0 1 0,5 1 0,5 0 0 3 1,5 Formand for danske kredsPer Alling Toubro 0,50ER 0 0 1 0,5 2 1 0 0 0 0 3 1,5 Ass VP Verner Usbeck 1ER 1 1 0 0 1 10 0 0 019 19 Medarbejderforeningen Solveig Ørteby 1ER 00 001111 0099 EkspeditionsmedarbejderPia Bo Pedersen 0,50ER 0 0 0 0 1 0,5 1 0,5 0 0 4 2 Fuldmægtig Peter Michaelsen 0,50ER 1 0,5 1 0,5 1 0,5 0 0 0 0 16 8 Privatrådgiver Tove Abildgaard 0,50ER 0 0 0 0 1 0,5 1 0,5 0 0 4 2 Fhv Kabinetsekretær Niels Eilschou Holm 0,3333 0 0 1 0,3333 3 0,9999 0 0 1 0,3333 18 5,9994 Bank Ass. Bolette Holmgaard 0,3333ER 0 0 0 0 1 0,3333 1 0,3333 0 0 2 0,6666 TøERermester Poul Christiansen 0,1667 0 0 0 0 1 0,1667 0 0 1 0,1667 4 0,6668 Gårdejer Hans Hansen 0,1667 0 0 0 0 1 0,1667 0 0 1 0,1667 4 0,6668
0,46 0,69 4,35 0,35 0,59 10,41
Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep Board Size excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Danske Bank A/S 16,50 10,67 1,00 1,00 20,00 7,47 8,65 2,68 2,31
138 2.2 NORDEA BANK DANMARK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Koncern direktør Christian Clausen 1 1 1 1 1 9 9 0 0 0 0 11 11 CFO Frederik Rystedt 0,1667 1 0,1667 0 0 1 0,1667 0 0 0 0 1 0,1667 Afd. Chef Carl-Johan Granvik 1 1 1 1 1 3 3 0 0 0 0 8 8 Direktør Arne Liljedahl 0,8333 1 0,8333 1 0,8333 2 1,6666 0 0 0 0 6 4,9998 Direktør Markku Pohjola 0,8333 1 0,8333 0 0 2 1,6666 0 0 0 0 7 5,8331 CEO Lars G. Nordström 0,6667 0 0 1 0,6667 3 2,0001 0 0 0 0 6 4,0002 Direktør Tom Ruud 0,6667 1 0,6667 1 0,6667 3 2,0001 0 0 0 0 5 3,3335 Direktør Kari Jordan' 0,1667 1 0,1667 0 0 1 0,1667 0 0 0 0 2 0,3334 0,87 0,78 3,69 0,00 0,00 7,06
139 2.3 JYSKE BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorshi Weighted Gender Weighted Independence Weighted Tenure Weighted
Adm Direktør /FormandSven Buhrkall 1 1 1 1 1 8 8 0 0 1 1 11 11 Direktør / NæstformandNiels Erik Carstens 1 0 0 1 1 7 7 0 0 1 1 11 11 Fiskeskipper Jens A. Borup 0,6667 0 0 1 0,6666 6 3,9996 0 0 1 0,6666 4 2,6664 Advokat Philip Baruch 0,5 0 0 1 0,5 15 7,5 0 0 1 0,5 3 1,5 Adm Direktør Kurt Brusgaard 1 0 0 1 1 5 5 0 0 1 1 9 9 Advokat Keld Norup 0,3333 0 0 1 0,3333 30 9,999 0 0 1 0,3333 2 0,6666 System Konstruktør Haggai Kunisch 1ER 0 0 0 0 2 2 0 0 0 0 7 7 Afdelingsdirektør Lars Aarup Jensen 1ER 0 0 0 0 1 1 0 0 0 0 12 12 Fuldmægtig Marianne Lillevang 0,50ER 0 0 0 0 1 0,5 1 0,5 0 0 3 1,5 Fhv. Kommunal direktørErik Rask Petersen 0,50 0 0 1 0,5 5 2,5 0 0 1 0,5 3 1,5 Kammerherre Leif Krabbe 0,50 0 0 0 0 1 0,5 0 0 1 0,5 9 4,5 Kunderådgiver Lillian Isaksen 0,50ER 0 0 0 0 0 0 1 0,5 0 0 4 2 Forstander Tage Lorentzen 0,3333 1 0,3333 0 0 1 0,3333 0 0 1 0,3333 27 8,9991 Direktør Leon Rasmussen 0,1667 0 0 0 1 0,1667 0 0 1 0,1667 17 2,8339
0,15 0,56 5,39 0,11 0,67 8,46
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Jyske Bank A/S 9,00 6,00 0,00 0,00 14,00 5,45 5,37 2,57 2,61
140 2.4 NYKREDIT BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Kocerndirektør Karsten Knudsen Chairman 0,3333 1 0,3333 1 0,3333 7 2,3331 0 0 0 0 2 0,6666 KocerndirektørSøren Holm 1 1 1 1 1 12 12 0 0 0 0 7 7 Afd. Chef Henrik K. Asmussen 0,3333ER 1 0,3333 0 0 1 0,3333 0 0 0 0 2 0,6666 KocerndirektørPer Ladegaard 1 1 1 1 1 9 9 0 0 0 0 11 11 Kontorchef Allan Kristiansen 1ER 0 0 0 0 2 2 0 0 0 0 6 6 Koncerndirektør Henning Kruse Petersen 0,6667 0 0 1 0,6667 27 18,0009 0 0 0 0 13 8,6671 Chef Dealer Søren Klitholm 0,6667ER 1 0,6667 0 0 1 0,6667 0 0 0 0 4 2,6668 Koncerndirektør Peter Engberg Jensen 0,5 1 0,5 1 0,5 3 1,5 0 0 0 0 9 4,5
5,50 0,70 0,64 8,33 0,00 0,00 7,48
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Nykredit Bank A/S 5,50 3,50 1,00 0,00 9,00 5,14 6,37 1,75 1,41
141 2.5 SYDBANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Gårdejer fhv. Amtsborgmester/Formand Kresten Phillipsen 1 0 0 1 1 13130 0 1 110 10 Direktør Anders Thoustrup 1 0 0 1 1 9 9 0 0 1 1 9 9 Direktør Otto Christensen 1 1 1 1 1 22 22 0 0 1 1 7 7 Forstander Peder Damgaard 0,50 0 0 1 0,5 11 5,5 0 0 1 0,5 3 1,5 Gårdejer Peter Gæmelke 0,3333 0 0 1 0,3333 15 4,9995 0 0 1 0,3333 2 0,6666 Direktør Hanni Toosbuy Kasprzak 0,50 0 0 1 0,5 5 2,5 1 0,5 1 0,5 3 1,5 Fuldmægtig Harry Max Friedrichsen 1ER 0 0 0 0 1 1 0 0 0 0 19 19 Salgskonsulent Jan Uldahl-Jensen 1ER 0 0 0 0 1 1 0 0 0 0 7 7 Bankassistent Margrethe Weber 1ER 0 0 0 0 1 1 1 1 0 0 16 16 Afd. Direktør Per Olesen 0,50ER 0 0 0 0 1 0,5 0 0 0 0 3 1,5 Advokat Sven Rosenmeyer Paulsen 0,50 0 0 1 0,5 9 4,5 0 0 1 0,5 3 1,5 Direktør Vagn F. Christensen 0,8333 0 0 1 0,8333 12 9,9996 0 0 1 0,8333 7 5,8331 Gårdejer Christen Jessen 0,50 0 0 1 0,5 1 0,5 0 0 1 0,5 17 8,5 Bankassistent Jytte L. Jensen 0,50ER 0 0 1 0,5 1 0,5 1 0,5 0 0 11 5,5 Gårdejer Jørgen Rud Juul Jørgensen 0,50 0 0 1 0,5 2 1 0 0 1 0,5 5 2,5 Direktør Helmuth Kirsten 0,50 0 0 1 0,5 2 1 0 0 1 0,5 17 8,5 Direktør Pernille Siesbye 0,50 0 0 1 0,5 3 1,5 1 0,5 1 0,5 5 2,5
0,09 0,70 6,81 0,21 0,66 9,26
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Sydbank A/S 11,67 7,66 0,00 0,00 19,00 6,35 5,00 2,99 3,80
142
2.6 SPAR NORD BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Adm. Direktør/FormandTorben Fristrup 1 0 0 1 1 7 7 0 0 1 1 6 6 Prof. Næstformand Per Nikolai Bukh 0,3333 1 0,3333 1 0,3333 2 0,6666 0 0 1 0,3333 2 0,6666 Adm. Direktør Carsten Normann 0,8333 1 0,8333 1 0,8333 3 2,4999 0 0 1 0,8333 5 4,1665 Gårdejer Niels K. Kirketerp 0,6667 0 0 1 0,6667 15 10,0005 0 0 1 0,6667 4 2,6668 Direktør Per Søndergaard Pedersen 1 1 1 1 1 21 21 0 0 1 1 8 8 Fællestillidsmand Ole Skov 1ER 0 0 0 0 2 2 0 0 0 0 9 9 Tillidsmand Jannie Skovsen 0,1667ER 0 0 0 0 1 0,1667 0 0 0 0 1 0,1667 Tillidsmand Jan Høholt Jensen 0,8333ER 0 0 0 0 3 2,4999 0 0 0 0 5 4,1665 Ejendomsmægler Erling Kjær 1 0 0 1 1 1 1 0 0 1 1 20 20 Kundechef Trine Bruun Haals 0,6667 0 0 0 0 1 0,6667 1 0,6667 0 0 4 2,6668 Overlærer Niels Ole Arndt 0,6667 0 0 0 0 1 0,6667 0 0 0 0 15 10,0005 Adm. Direktør Henrik Hougaard 0,3333 1 0,3333 1 0,3333 19 6,3327 0 0 1 0,3333 4 1,3332 Tidl. ManagementkonsulentPoul Lauritsen 0,1667 1 0,1667 1 0,1667 27 4,5009 0 0 1 0,1667 9 1,5003 Fuldmægtig Michael Budolfsen 0,1667 0 0 1 0,1667 5 0,8335 0 0 0 0 8 1,3336 Funktionschef Birte Kiel Jensen 0,1667 0 0 0 0 1 0,1667 1 0,1667 0 0 8 1,3336
0,30 0,61 6,67 0,09 0,59 8,11
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep)
Spar Nord Bank A/S 9 7 1 1 14 4,87 5 2,875 2,800
143 2.7 VESTJYSK BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Anders Bech 1 0 0 1 1 3 3 0 0 1 1 12 12 Direktør Poul Hjulmand 0,1667 0 0 1 0,1667 18 3,0006 0 0 1 0,1667 1 0,1667 Direktør Carl Olav Birk Jensen 0,1667 0 0 0 0 2 0,3334 0 0 1 0,1667 1 0,1667 Proprietær Kirsten Lundgaard-Karlshøj 1 0 0 1 1 1 1 1 1 0 0 11 11 Slagtermester Peter Mortensen 0,1667 0 0 0 0 1 0,1667 0 0 1 0,1667 1 0,1667 Storkundechef Peder Hesselaa Nielsen 1ER 1 1 0 0 2 2 0 0 0 0 6 6 Markedschef Peter Bækkelund Rasmussen 0,3333 ER 0 0 0 0 1 0,3333 0 0 0 0 2 0,6666 Direktør Peter Grankær 1 0 0 1 1 1 1 0 0 1 1 7 7 Fiskeskipper Søren Broe Langer 0,6667 0 0 1 0,6667 3 2,0001 0 0 1 0,6667 4 2,6668 Landmand Preben Larsen 0,6667ER 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668 Erhvervsrådgiver Gunnar Overlund Knudsen 0,6667ER 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668 Gårdejer Jens Peder Østergaard 0,5 0 0 0 0 2 1 0 0 1 0,5 3 1,5 Hvidevareforhandler Poul Sinnerup 0,3333 0 0 1 0,3333 4 1,3332 0 0 1 0,3333 10 3,333 HerreekviperingssælgerOtto Schumann 0,1667 0 0 1 0,1667 1 0,1667 0 0 1 0,1667 15 2,5005
0,13 0,55 2,13 0,13 0,53 6,71
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Vestjysk Bank A/S 7,83 5,17 0,00 0,00 7,00 3,75 4,00 1,87 1,75
144 2.8 AMAGERBANKEN
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Advokat/FormandNiels Erik Nielsen 1 0 0 1 1 42 42 0 0 1 1 13 13 Adm. Direktør Kent Madsen 0,1667 0 0 1 0,1667 28 4,6676 0 0 1 0,1667 1 0,1667 Lærer/BorgmesterHenrik Zimino 1 0 0 1 1 3 3 0 0 1 1 11 11 Konsulent John Skafte 0,6667ER 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668 Teknikum ingeniørVilly Rasmussen 1 0 0 1 1 45 45 0 0 1 1 11 11 InvesteringsrådgiverAnne Toxværd 1ER 0 0 0 0 1 1 1 1 0 0 3 3 Ingeniør Bent Müller 0,8333 0 0 1 0,8333 12 9,9996 0 0 1 0,8333 17 14,1661 Filial chef Jannik Hindsbo 0,5ER 0 0 0 0 1 0,5 0 0 1 0,5 4 2
0,00 0,65 17,32 0,16 0,73 9,24
Board Size incl. Board Size Board Years Board Years CEO/Board CEO/Board Bank Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep)
Amagerbanken 6,16 4,00 1,00 1,00 23,00 7,13 9,87 3,23 2,33
145 2.9 ARBEJDERNES LANDSBANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Forbundsformand Poul Erik Skov Christensen 1 0 0 1 15 15 0 0 1 1 12 12 Formand LO Harald Børsting 0,1667 0 0 1 0,1667 13 2,1671 0 0 1 0,1667 1 0,1667 Forbundsformand Metal Thorkild E. Jensen 0,8333 0 0 1 0,8333 16 13,3328 0 0 1 0,8333 5 4,1665 Næstformand HK Danmark Mette Kindberg 0,1667 0 0 1 0,1667 6 1,0002 1 0,1667 1 0,1667 1 0,1667 Forbundsformand NNF Ole Wehlast 0,5 0 0 1 0,5 5 2,5 0 0 1 0,5 3 1,5 Fællestillidsrep. Ulla Strøm Nordenhof 1ER 0 0 1 1 3 3 1 1 0 0 11 11 Kunderådgiver Jette Kronborg 1ER 0 0 0 0 1 1 1 1 0 0 7 7 Kundekonsulent John Markussen 1ER 0 0 0 0 1 1 0 0 0 0 11 11 Produktionschef Henrik Thagaard 0,1667ER 0 0 0 0 1 0,1667 0 0 0 0 1 0,1667 Forbundsformand John Dahl 1 0 0 1 1 19 19 0 0 1 1 11 11 Forbundsformand Arne Johansen 1 0 0 1 1 14 14 0 0 1 1 16 16 Forbundsformand Hans Jensen 0,8333 0 0 1 0,8333 29 24,1657 0 0 1 0,8333 11 9,1663 Gruppeformand Lilian Knudsen 0,8333 0 0 1 0,8333 13 10,8329 1 0,8333 1 0,8333 19 15,8327 Bankdirektør Per Lykke 0,3333ER 1 0,3333 0 0 1 0,3333 0 0 0 0 2 0,6666 Forbundsformand Henry Holt Jochumsen 0,5 0 0 1 0,5 3 1,5 0 0 1 0,5 17 8,5
0,03 0,66 10,55 0,29 0,66 10,49
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Arbejdernes Landsbank, Aktieselskab 10,33 6,83 0,00 0,00 7,00 7,22 7,85 0,97 0,89
146 2.10 FORSTÆDERNES BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Formand Jesper Andreasen 1 1 1 1 1 14 14 0 0 1 1 16 16 Erhvervskundechef Mette Viskum Kretzschmer 1 ER 1 1 0 0 1 1 1 1 0 0 7 7 Arkitek Henrik Plannthin 1ER 0 0 0 0 1 1 0 0 0 0 7 7 Kundechef Olav Brusen Barsøe 0,5ER 0 0 0 0 1 0,5 0 0 0 0 3 1,5 Vognmand Helmer Olsen 1 0 0 1 1 4 4 0 0 1 1 16 16 Materialist Lars Frederiksen 1 0 0 1 1 11 11 0 0 1 1 7 7 Advokat Steen Moesgaard 1 0 0 1 1 4 4 0 0 1 1 10 10 Bilforhandler Arne Stubbe 1 0 0 1 1 4 4 0 0 1 1 18 18 0,27 0,67 5,27 0,13 0,67 11,00
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Forstædernes Bank A/S 7,50 5,00 1,00 1,00 21,00 10,31 13,40 2,04 1,57
147 2.11 SPARBANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Alex Nielsen 1 0 0 1 1 12 12 0 0 1 1 16 16 Automobilforhandler Fritz Dahl Pedersen 0,5 0 0 1 0,5 3 1,5 0 0 1 0,5 3 1,5 Bogtrykker Asger Jensen 1 0 0 1 1 5 5 0 0 1 1 7 7 Direktør Poul Sønder 0,6667 0 0 1 0,6667 11 7,3337 0 0 1 0,6667 4 2,6668 Koncern Direktør Ove Kloch 0,1667ER 0 0 1 0,1667 25 4,1675 0 0 0 0 1 0,1667 Fuldmægtig Anna Marie Dahl 1ER 0 0 0 0 1 1 1 1 0 0 17 17 Administrationschef Anders Kristian Pugdahl Pedersen 0,1667ER 0 0 0 0 1 0,1667 0 0 0 0 1 0,1667 Direktør Per Engkrog Andersen 1 1 1 1 1 3 3 0 0 1 1 13 13 Bankass. Mette Dahl Christensen 0,8333ER 0 0 0 0 1 0,8333 1 0 ,8333 0 0 5 4,1665 Bankass. Kurth Bjerre 0,8333ER 0 0 0 0 1 0,8333 0 0 0 0 12 9,9996 Radio & Tvforhandler Ole Brøndum Jensen 0,6667 0 0 1 0,6667 14 9,3338 0 0 1 0,6667 19 12,6673 Arkitekt Per Mark 0,5 0 0 0 0 1 0,5 0 0 0 0 18 9 Direktør Svend Larsen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 11 3,6 663 Assistent Bente Mikkelsen 0,1667ER 0 0 0 0 1 0,1667 1 0,1667 0 0 1 0,1667 0,1715266 0,8576501 7,9190909 0,34305317 0,88622642 16,666655
Board Size Board Years Board CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) Years (ex (incl rep) (excl rep) Sparbank A/S 7,83 4,67 0 0 12 6,01 6,56 1,997 1,829
148 2.12 ROSKILDE BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Peter Müller 1 1 1 1 1 3 3 0 0 1 1 17 17 Advokat Niels Krüger 1 0 0 1 1 24 24 0 0 1 1 9 9 Direktør Peter Holm 1 0 0 1 1 17 17 0 0 1 1 11 11 Kocernchef Asger Ib Mardahl-Hansen 0,3333 1 0,3333 1 0,3333 13 4,3329 0 0 1 0,3333 2 0,6666 KunderådgiverOve Holm 1ER 0 0 0 0 1 1 0 0 0 0 5 5 KunderådgiverLinda Charlotte Larsen 0,2ER 0 0 0 0 1 0,2 1 0,2 0 0 1 0,2 Bankass Irene Nielsen 0,8ER 0 0 0 0 1 0,8 1 0,8 0 0 4 3,2 AutoforhandlerJens Winther 0,6 0 0 1 0,6 1 0,6 0 0 1 0,6 3 1,8
0,22 0,66 8,49 0,17 0,66 7,98
Board Size Board Years Board CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) Years (ex (incl rep) (excl rep) Roskilde Bank, 5,93 4,00 1,00 1,00 21,00 5,98 7,89 3,51 2,66
149 2.13 RINGKJØBING LANDBOBANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
It/Marketing chef Jens Lykke Kjeldsen 1 0 0 1 1 9 9 0 0 1 1 14 14 Gårdejer Gravers Larsen Kjærgaard 1 0 0 0 0 1 1 0 0 1 1 7 7 Bogtrykker Gert Asmussen 1 0 0 1 1 7 7 0 0 1 1 7 7 Købmand Keld Hansen 1 0 0 1 1 8 8 0 0 1 1 7 7 It Konsulent Bo Bennedsgaard 0,3333ER 0 0 0 0 1 0,3333 0 0 0 0 2 0,6666 Kunderådgiver Søren Nielsen 1ER 0 0 0 0 1 1 0 0 0 0 6 6 Kunderådgiver Mogens Andersen 0,6667ER 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668 Kunderådgiver Vibeke Ballegaard 0,6667ER 0 0 0 0 1 0,6667 1 0,6667 0 0 4 2,6668 Investeringsrådgiver Jørgen H. Pedersen 0,5 0 0 0 0 1 0,5 0 0 1 0,5 3 1,5 Kartoffelavler Villy Rosendahl Christensen 0,3333 0 0 1 0,3333 1 0,3333 0 0 1 0,3333 2 0,6666
0,00 0,44 3,80 0,09 0,64 6,56
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep)
150 2.14 ALM . BRAND BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Formand/Gårdejer Jørgen Hesselbjerg Mikkelsen 1 0 0 1 1 17 17 0 0 1 115 15 Kammerherre Chrstian N.B. Ulrich 1 0 0 1 1 4 4 0 0 1 1 19 19 Adm. Direktør Søren Boe Mortensen 1 1 1 1 1 4 4 0 0 1 1 8 8 Professor Christian Hjorth-Andersen 1 1 1 0 0 1 1 0 0 1 1 13 13 Kunderådgiver Ole Bach 1ER 0 0 0 0 1 1 0 0 0 0 20 20 Regionsdirektør Mark Oswald 0,6667ER 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668 Adm Direktør Ole Joakim Jensen 0,3333 1 0,3333 1 0,3333 4 1,3332 0 0 1 0,3333 2 0,6666 Kunderådgiver Per Hansen 0,3333ER 0 0 0 0 1 0,3333 0 0 0 0 2 0,6666
0,37 0,53 4,63 0,00 0,68 12,48 Board Board Size Board Years Years (ex CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) rep.) (incl rep) (excl rep) Alm. Brand Bank A/S 6,33 4,33 1,00 0,00 20,00 9,88 11,13 2,02 1,80
151 2.15 SAMMENSLUTNINGEN DANSKE ANDELSKASSER
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted Advokat Jakob Fastrup 0,5 0 0 1 0,5 17 8,5 0 0 1 0,5 3 1,5 Direktør Gert Hansen 1 1 1 1 1 2 2 0 0 1 1 10 10 Gårdejer Jens Jørgensen Hald 1 0 0 0 0 1 1 0 0 1 1 6 6 Skoleinspektør Peder A Josefsen 1 0 0 1 1 2 2 0 0 1 1 16 16 Læge Keld Lamberts 1 0 0 1 1 2 2 0 0 1 1 8 8 Direktør Hans Jørn Madsen 0,5 0 0 1 0,5 4 2 0 0 1 0,5 3 1,5 Gårdejer Visti Pedersen 0,5 0 0 1 0,5 3 1,5 0 0 1 0,5 3 1,5 Tømrermester Herluf Lund 0,8333 0 0 1 0,8333 6 4,9998 0 0 1 0,8333 1 0,8333 Gårdejer Asger Pedersen 1 0 0 1 1 8 8 0 0 1 1 7 7 Læge Jens Peder Kaalund 0,8333 0 0 1 0,8333 3 2,4999 0 0 1 0,8333 14 11,6662 Investeringsrådgiver Knud Larsen 0,5 0 0 1 0,5 3 1,5 0 0 1 0,5 5 2,5
0,12 0,88 4,15 0,00 1,00 7,67
Board Size Board Years Board CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) Years (ex (incl rep) (excl rep) Sammenslutningen Danske Andelskasser 6,33 4,33 1,00 0,00 20,00 9,88 11,13 2,02 1,80
152 2.16 SPAREKASSEN SJÆLLAND
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Rektor Niels Arne Uglebjerg 1 0 0 1 1 2 2 0 0 1 1 20 20 Direktør Jess Jehl 0,1667 0 0 1 0,1667 3 0,5001 0 0 1 0,1667 1 0,1667 Entreprenør John Ravn Christensen 0,6667 0 0 1 0,6667 3 2,0001 0 0 1 0,6667 4 2,6668 Direktør Kjeld Ilsøe 1 0 0 1 1 4 4 0 0 1 1 14 14 Autoforhandler Peter Klarskov Larsen 0,1667 0 0 0 0 1 0,1667 0 0 1 0,1667 1 0,1667 Stabsmedarbejder Hanne Friese- Christiansen 0,1667 ER 0 0 0 0 1 0,1667 1 0,1667 0 0 1 0,1667 Afd. Direktør Per Olsen 1ER 0 0 0 0 1 1 0 0 0 0 15 15 Prokurist Peter Woldbye 0,8333ER 0 0 0 0 1 0,8333 0 0 0 0 5 4,1665 Civilingeniør Claus Henningsen 1 0 0 1 1 14 14 0 0 1 1 17 17 El instl. Erik Vang Larsen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6666 Fotohandler Jørgen Olsen 0,8333 0 0 0 0 1 0,8333 0 0 1 0,8333 14 11,6662 Bank ass. Åse Pedersen 0,8333ER 0 0 0 0 1 0,8333 1 0,8333 0 0 11 9,1663 Bank ass. Frede Larsen 0,5ER 0 0 0 0 1 0,5 0 0 0 0 15 7,5 Ejendomsmægler Jørgen Frederiksen 0,3333 0 0 1 0,3333 4 1,3332 0 0 1 0,3333 9 2,9997 Rådgiver Bjarne Rasmussen 0,1667ER 0 0 1 0,1667 2 0,3334 0 0 1 0,1667 4 0,6668
0,00 0,48 3,20 0,11 0,63 11,78 Board Board Size Board Years Years (ex CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) rep.) (incl rep) (excl rep) Sjælland, Sparekassen 9,00 5,50 1,00 0,00 31,00 7,07 7,70 4,38 4,03
153 2.17 SPAREKASSEN KRONJYLLAND
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Jørgen B. Nielsen 0,8333 0 0 1 0,8333 2 1,6666 0 0 1 0,8333 5 4,1665 Konsulent Ove Knudsen 1 0 0 0 0 1 1 0 0 1 1 12 12 Adjunkt, Cand. Jur Anne Gleerup 0,8333 0 0 0 0 1 0,8333 1 0,8333 1 0,8333 5 4,1665 Fhv, Kriminalkommisær Jørn Hougaard 1 0 0 1 1 2 2 0 0 1 1 9 9 Entreprenør Tommy Pedersen 1 0 0 1 1 4 4 0 0 1 1 13 13 Advokat Ole Møller Sørensen 0,3333ER 0 0 0 0 1 0,3333 0 0 0 0 2 0,6666 Investeringsrådgiver Jan Kjeldahl 1ER 0 0 0 0 1 1 0 0 0 0 6 6 Afdelingsdirektør Jan Nyvang 1ER 0 0 0 0 1 1 0 0 0 0 10 10 Gårdejer Herluf Skjøtt 1 0 0 1 1 3 3 0 0 1 1 16 16 Rådgiver Berit Meidal 0,6667ER 0 0 0 0 1 0,6667 1 0,6667 0 0 4 2,6668 Direktør Carl Damgaard Nielsen 0,1667 0 0 1 0,1667 9 1,5003 0 0 1 0,1667 24 4,0008 Politiass Torben Stenrøjl 0,1667 0 0 0 0 1 0,1667 0 0 1 0,1667 12 2,0004
0,00 0,44 1,91 0,17 0,67 9,30
Board Size Board Years Board CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) Years (ex (incl rep) (excl rep) Kronjylland, Sparekassen 9,00 6,00 0,00 0,00 22,00 5,09 8,00 4,32 2,75
154 2.18 FIONIA BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Palle Bo Stærmose 1 0 0 1 1 10 10 0 0 1 1 13 13 Professor Børge Obel 1 1 1 1 1 16 16 0 0 1 1 9 9 Borgmester Knud Gether 1 0 0 1 1 3 3 0 0 1 1 13 13 Gårdejer Tom Foged-Pedersen 0,8333 0 0 0 0 1 0,8333 0 0 1 0,8333 5 4,1665 Jurist Nina Dietz Legind 0,5 1 0,5 0 0 2 1 1 0,5 1 0,5 3 1,5 Direktør Ole Madsen 0,5 1 0,5 1 0,5 8 4 0 0 0 0 3 1,5 Obligationschef Erik Granhøj Hansen 0,8333ER. 1 0,8333 1 0,8333 1 0,8333 0 0 0 0 5 4,1665 ErhvervsrådgiverPia Lærke Petersen 0,8333ER. 0 0 0 0 1 0,8333 1 0,8333 0 0 5 4,1665 BankrådgiverOle Rasmussen 1ER. 0 0 0 0 1 1 0 0 0 0 18 18 Borgmester Claus Hansen 0,5 0 0 1 0,5 5 2,5 0 0 1 0,5 15 7,5 Major Ib Spanggaard 0,5 0 0 1 0,5 5 2,5 0 0 1 0,5 6 3 Direktør Johannes Faghtmann 0,1667 1 0,1667 1 0,1667 5 0,8335 0 0 1 0,1667 13 2,1671 ErhvervsrådgiverPoul Bæk 0,1667ER. 0 0 0 0 1 0,1667 0 0 0 0 4 0,6668 Kunderådgiver Inge B. Larsen 0,1667ER. 0 0 0 0 1 0,1667 1 0,1667 0 0 4 0,6668
0,33 0,61 4,85 0,17 0,61 9,17 Board Board Size Board Years Years (ex CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) rep.) (incl rep) (excl rep)
Fionia Bank A/S 9,00 6,00 1,00 0,00 13,00 8,29 6,09 1,57 2,13
155 2.19 SPAREKASSEN HIMMERLAND
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Finn Hovalt Mathiassen 0,8333 0 0 1 0,8333 16 13,3328 0 0 1 0,8333 5 4,1665 Direktør Kaj Kragelund 1 0 0 1 1 9 9 0 0 1 1 17 17 Fotohandler Jesper Bo Thorup Nielsen 0,5 0 0 1 0,5 6 3 0 0 1 0,5 3 1,5 Investeringschef Jesper Søndergaard 1ER. 0 0 0 0 1 1 0 0 0 0 19 19 Afdlingsdirektør Vagn Bach 1ER. 0 0 0 0 1 1 0 0 0 0 9 9 Gårdejer Kristian Skovhus 1 0 0 1 1 8 8 0 0 1 1 20 20 Tv-forhandler Arne Nielsen 0,5 0 0 1 0,5 3 1,5 0 0 1 0,5 16 8 Adm. Direktør Ludvig Hybschmann 0,1667 0 0 1 0,1667 5 0,8335 0 0 1 0,1667 20 3,334
0,00 0,67 6,28 0,00 0,67 13,67 Board Board Size Board Years Years (ex CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) rep.) (incl rep) (excl rep) Himmerland A/S, Sparekassen 6,00 4,00 0,00 1,00 21,00 10,25 9,00 2,05 2,33
156 2.20 DEN JYSKE SPAREKASSE
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
SkolebibliotekskonsulentFinn Odegaard 1 0 0 1 1 6 6 0 0 1 1 20 2 0 Bogtrykker Connie Bæk Hansen 0,3333 0 0 1 0,3333 2 0,6666 1 0,3333 1 0,3333 2 0,6666 Gårdejer Sejer Mortensen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6666 Gartner Erik Bendixen 0,3333 0 0 1 0,3333 1 0,3333 0 0 1 0,3333 2 0,6666 Erhvervsrådgiver Anette Hundebøll Bjerregaard 0,1667 ER. 0 0 0 0 1 0,1667 1 0,1667 0 0 1 0,1667 Overlærer Knud Dupont 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6666 Kunderådgiver Karsten Westergård Hansen 0,1667ER. 0 0 0 0 1 0,1667 0 0 0 0 1 0,1667 Erhvervsrådgiver Kurt Johansen 0,3333ER. 0 0 0 0 1 0,3333 0 0 0 0 2 0,6666 Fhv uddeler Bent Jørgensen 1 0 0 0 0 1 1 0 0 1 1 20 20 Borgmester Ib Kristensen 0,5 0 0 1 0,5 4 2 0 0 1 0,5 3 1,5 Gårdejer Ejnar Lauridsen 1 0 0 0 0 1 1 0 0 1 1 10 10 Statsaut. Revisor Jakob Plum Lauridsen 1 1 1 1 1 1 1 0 0 1 1 11 1 1 Souschef Preben Nørgaard Larsen 0,1667ER. 0 0 0 0 1 0,1667 0 0 0 0 1 0,1667 Souschef Steen Louie 0,3333ER. 0 0 1 0,3333 1 0,3333 0 0 0 0 2 0,6666 Advokat Bjarne L. Petersen 0,3333 0 0 1 0,3333 8 2,6664 0 0 1 0,3333 2 0,6666 Fhv. Skoleinspektør Tage Holm 1 00001100 1188 Malermester Svend Aage Nielsen 0,1667 0 0 0 0 1 0,1667 0 0 1 0,1667 1 0,1667 Erhvervsrådgiver Erik Skoubo Poulsen 0,8333ER. 0 0 0 0 1 0,8333 0 0 0 0 10 8,333 Regnskabschef Elvin Rasmussen 0,8333ER. 0 0 0 0 1 0,8333 0 0 0 0 8 6,6664 Erhvervsrådgiver Søren Vinther 0,8333ER. 0 0 0 0 1 0,8333 0 0 0 0 8 6,6664 Advokat Ruth Hennebjerre 0,5 0 0 0 1 0,5 1 0,5 1 0,5 6 3
0,09 0,22 1,19 0,06 0,54 6,88 Board Board Size Board Years Years (ex CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) rep.) (incl rep) (excl rep) Den Jyske Sparekasse 11,50 7,83 0,00 0,00 15,00 4,93 6,00 3,04 2,50
157 2.21 EIK BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted SparekassedirektørPeter Marner Jacobsen 1 1 1 0 0 1 1 0 0 0 0 8 8 Direktør Henrik Ørsted 1 1 1 1 1 13 13 0 0 1 1 8 8 Direktør Knud Jørgen Strange 1 1 1 1 1 4 4 0 0 1 1 8 8 Professor Hans Keiding 0,6667 1 0,6667 1 0,6667 2 1,3334 0 0 1 0,6667 7 4,6669 Direktør Sigurdur Einarsson 0,3333 1 0,3333 0 0 1 0,3333 0 0 0 0 4 1,3332
1,00 0,67 4,92 0,00 0,67 7,50 Board Board Size Board Years Years (ex CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) rep.) (incl rep) (excl rep) EIK Bank Danmark A/S 4,00 4,00 1,00 1,00 8,00 6,00 6,00 1,33 1,33
158 2.22 LÅN & SPAR BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Lærer Anders Bondo Christensen 1 0 0 0 0 7 7 0 0 1 1 6 6 Forbundsformand Peter Ibsen 0,6667 0 0 0 0 5 3,3335 0 0 1 0,666 7 4 2,6668 Lærer Jan Hjort 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6666 Direktør Sine Sunesen 0,8333 0 0 1 0,8333 3 2,4999 1 0,8333 1 0 ,8333 5 4,1665 Sygeplejerske Connie Kruckow 1 0 0 0 0 5 5 1 1 1 1 8 8 Forbundsformand Ulrik Salmonsen 0,8333 0 0 1 0,8333 5 4,1665 0 0 1 0,8333 5 4,1665 Forbundsformand Bente Sorgenfrey 0,8333 0 0 1 0,8333 9 7,4997 1 0,8333 1 0,8333 5 4,1665 Fuldmægt Helle Bagge Britze 1 ER. 0 0 0 0 1 1 1 1 0 0 9 9 Økonomimedarbejder Peter Chrstian Sommer 0,3333ER. 0 0 0 0 1 0,3333 1 0,3333 0 0 2 0,6666 Bankbetjent Palle Tipsmark 0,5ER. 0 0 0 0 1 0,5 0 0 0 0 3 1,5 Kunderådgiver Preben Dessau 0,5ER. 0 0 0 0 1 0,5 0 0 0 0 3 1,5 Direktør Flemming Skov Jensen 0,8333 1 0,8333 1 0,8333 26 21,6658 0 0 1 0,8333 18 14,9994 Forbundsformand Tommy Agerskov Thomsen 0,6667 1 0,6667 1 0,6667 4 2,6668 0 0 1 0,6667 18 12,0006 ØkonomimedarbejderLars Weber Andersen 0,1667ER. 0 0 0 0 1 0,1667 0 0 0 0 1 0,1667 Souschef Lisa Seehuusen 0,5ER. 1 0,5 0 0 1 0,5 1 0,5 0 0 8 4 Områdedirektør Mikkel Eriksen 0,5ER. 0 0 0 0 1 0,5 0 0 0 0 4 2 Investeringsrådgiver Thomas Jørgen Kruse 0,5 0 0 0 0 1 0,5 0 0 1 0,5 8 4 Projektleder Svend Erik Christensen 0,1667 0 0 1 0,1667 2 0,3334 0 0 1 0,1667 6 1,0002 Redaktør Torben Hansen 0,1667 0 0 1 0,1667 3 0,5001 0 0 1 0,166 7 3 0,5001 Læge Svend M. Christensen 0,1667 0 0 1 0,1667 1 0,1667 0 0 1 0,1667 6 1,0002 Forbundsformand Anker Christoffersen 0,1667 0 0 1 0,1667 6 1,0002 0 0 1 0,1667 15 2,5005
0,17 0,40 5,16 0,39 0,70 7,26
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Lån og Spar Bank A/S 11,67 7,17 0,00 1,00 19,00 4,03 4,70 4,71 4,04
159 2.23NØRRESUNDBY BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Kjeld Kolind Jensen 1 0 0 1 1 3 3 0 0 1 1 25 25 Landinspektør Mads Hvolby 0,5 0 0 0 0 2 1 0 0 1 0,5 3 1,5 Vicedirektør Poul Søe Jeppesen 0,3333 0 0 0 0 1 0,3333 0 0 1 0 ,3333 2 0,6666 Direktør Kresten Skjødt 1 1 1 1 1 3 3 0 0 0 0 6 6 Formue og PensioschefHelle Juul Lynge 0,5ER. 1 0,5 0 0 1 0,5 1 0,5 0 0 3 1,5 Afdelingsdirektør Allan Nielsen 1ER. 0 0 0 0 1 1 0 0 0 0 11 11 Adm. Direktør Hans Christian Dybvad Jensen 0,6667 1 0,6667 1 0,6667 6 4,0002 0 0 1 0,6667 15 10,0005 Direktør Villy Jensen 0,5 0 0 1 0,5 6 3 0 0 1 0,5 8 4 Fuldmægtig Marian June Andreasen 0,5ER. 0 0 0 0 1 0,5 1 0,5 0 0 4 2
0,36 0,53 2,72 0,17 0,50 10,28
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Nørresundby Bank A/S 6,00 4,00 0,00 0,00 11,00 6,80 7,86 1,62 1,40
160 2.24 SPAREKASSEN VENDSYSSEL
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Fabrikant Svend Vestergaard Pedersen 1 0 0 1 1 7 7 0 0 0 0 8 8 Vildtforvaltningskonsulent Peter Have 1 00 11 660 0 0 01818 tømrer- og snedkermester Arne Andersen 1 0 0 1 1 6 6 0 0 1 1 10 10 elektronikmekaniker Louis Holdt Christensen 1 0 0 1 1 3 3 0 0 1 1 8 8 El installatør Aage H. Christensen 0,1667 0 0 1 0,1667 8 1,3336 0 0 1 0,1667 1 0,1667 El installatør Poul Dahlgaard 0,5 0 0 1 0,5 8 4 0 0 1 0,5 3 1,5 Advokat Birte Dyrberg 0,6667 0 0 1 0,6667 9 6,0003 1 0,6667 1 0,6667 4 2,6668 Kommunaldirktør Evald Haven 1 0 0 0 0 1 1 0 0 1 1 8 8 Adm Direktør Peter Larsen 0,1667 1 0,1667 1 0,1667 2 0,3334 0 0 1 0,1667 1 0,1667 Gårdejer, Inseminør Mogens Nedergaard 0,3333 0 0 0 0 2 0,6666 0 0 1 0,3333 2 0,6666 Kontorass. Dorte Folden Skole 0,5 0 0 1 0,5 2 1 1 0,5 1 0,5 3 1,5 Lærer Mona L. Thomsen 0,3333 0 0 1 0,3333 1 0,3333 1 0,3333 1 0,3333 2 0,6666 sparekassebetjent Regnar Bering 0,1667ER 0 0 1 0,1667 1 0,1667 0 0 0 0 1 0,1667 Souschef Hans Henrik Sørensen 0,1667ER 0 0 0 0 1 0,1667 0 0 0 0 1 0,1667 Fuldmægtig Marketing og IT Helle S. Sørensen 1 ER 0 0 0 0 1 1 1 1 0 0 7 7 Vagtmester Hans Jørgen Jensen 1 0 0 0 0 1 1 0 0 1 1 8 8 Chauffør Christian Engberg Christensen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6666 Butiksleder Johannes Hovaldt 0,5 0 0 1 0,5 4 2 0 0 1 0,5 3 1,5 Gårdejer Kristian Bastholm Jensen 1 0 0 0 0 1 1 0 0 1 1 11 11 Tømrermester Vang Lundegaard 0,3333 0 0 1 0,3333 1 0,3333 0 0 1 0,3333 2 0,6666 Kunderådgiver Inge Schaft 0,3333ER 0 0 0 0 1 0,3333 1 0,3333 0 0 2 0,6666 Fuldmægtig Svend Holmgaard 1ER 0 0 0 0 1 1 0 0 0 0 7 7
0,01 0,54 3,26 0,21 0,65 7,12
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Sparekassen Vendsyssel 13,50 10,83 0,00 0,00 11,00 4,37 4,77 2,52 2,31
161 2.25 NORDJYSKE BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Advokat/Formand Hans Jørgen Kaptain 1 0 0 1 1 60 60 0 0 1 1 16 16 Gårdejer/NæstformandErik Broholm Andersen 1 0 0 1 1 3 3 0 0 1 1 8 8 Gårdejer Per Lykkegaard Christensen 0,1667 0 0 1 0,1667 4 0,6668 0 0 1 0,1667 1 0,1667 Apoteker Henrik Lintner 0,3333 0 0 1 0,3333 7 2,3331 0 0 1 0,3333 2 0,6666 Autoforhandler Sten Uggerhøj 0,6667 0 0 1 0,6667 17 11,3339 0 0 1 0,6667 4 2,6668 Boligchef Tina Hansen 0,5ER 0 0 0 0 1 0,5 1 0,5 0 0 3 1,5 Kunderådgiver Hanne Karlshøj 1ER 0 0 0 0 1 1 1 1 0 0 7 7 Afdelingsleder Arne Ugilt 0,5 ER 0 0 0 0 2 1 0 0 0 0 3 1,5 Materialist Oluf Andersen 1 0 0 1 1 2 2 0 0 1 1 17 17 Fiskeskipper Peter Cold 0,6667 0 0 1 0,6667 2 1,3334 0 0 1 0,6667 5 3,3335 Bankfuldmægtig Henning Severinsen 0,5ER 0 0 1 0,5 2 1 0 0 0 0 4 2 Kundechef Pia Sørensen 0,5ER 0 0 0 0 1 0,5 1 0,5 0 0 8 4 Kunderådgiver Helle Thomsen 0,5 ER 0 0 0 0 1 0,5 1 0,5 0 0 3 1,5 Bygningsingeniør. Karl Ehlern 0,3333 0 0 1 0,3333 12 3,9996 0 0 1 0,3333 8 2,6664 Gårdejer Knud Thorkil Beck 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 3 0,9999 Minkavler Henning Ewall Jensen 0,8333 0 0 1 0,8333 4 3,3332 0 0 1 0,8333 11 9,1663
0,00 0,66 9,44 0,25 0,64 7,95
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Nordjyske Bank A/S 9,83 6,33 0,00 0,00 22,00 4,89 6,06 4,50 3,63
162 2.26 MORSØ SPAREKASSE
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Adm Dir. Peter Jessen Hansen 1 1 1 1 1 2 2 0 0 1 1 6 6 Skibsbygger Ralf Priess Sørensen 1 0 0 1 1 2 2 0 0 1 1 24 24 Frisørmester Ole Møller Madsen 1 0 0 1 1 2 2 0 0 1 1 9 9 ØkonomidirektørLeif Berntsen 1 1 1 1 1 13 13 0 0 1 1 28 28 Landmand Søren Søndergaard Nielsen 1 0 0 1 1 1 1 0 0 1 1 10 10 Adm Dir. Carsten Christensen 0,5 0 0 0 0 1 0,5 0 0 1 0,5 3 1,5 Kunderådgiver Torben Tranberg Stavtrup 1ER 0 0 1 1 1 1 0 0 0 0 1 0 10 Projektchef Bent Magnussen 1ER 1 1 1 1 3 3 0 0 0 0 6 6 Kunderådgiver Gerda Kusk 0,3333ER 0 0 0 0 1 0,3333 1 0,3333 0 0 2 0,6666 Gårdejer Aksel Sund Brusgaard 0,5 0 0 1 0,5 1 0,5 0 0 1 0,5 3 1,5 Direktør Søren Hansen 0,6667ER 1 0,6667 1 0,6667 3 2,0001 0 0 0 0 20 13,334
0,41 0,91 3,04 0,04 0,67 12,22
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Morsø Sparekasse 9,00 6,00 0,00 1,00 11,00 10,00 11,43 1,10 0,96
163 2.27 SPAREKASSEN LOLLAND
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Advokat Ellen Bredal Nielsen 1 0 0 1 1 10 10 1 1 1 1 20 20 Gårdejer Flemming Boye Clausen 1 0 0 1 1 3 3 0 0 1 1 11 11 Branchesekretær Kurt O. S. Hansen 1 0 0 1 1 3 3 0 0 1 1 6 6 Lektor Bo Rasmussen 0,6667 1 0,6667 0 0 2 1,3334 0 0 1 0,6667 4 2,6668 Filialdirektør Jan Nielsen 1ER. 1 1 0 0 1 1 0 0 0 0 7 7 Kunderådgiver Finn Christensen 0,5ER. 0 0 0 0 1 0,5 0 0 0 0 3 1,5 Politikommissær Kaj Verner Larsen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 15 4,9995 Kunderådgiver Inger Eriksen 0,5ER. 0 0 0 0 1 0,5 1 0,5 0 0 4 2
0,28 0,50 3,28 0,25 0,67 9,19
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Lolland A/S, Sparekassen 6,00 4,00 0,00 0,00 15,00 8,75 9,00 1,71 1,67
164 2.28 SPAREKASSEN FAABORG
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Forstander Christian Ermose 1 0 0 1 1 8 8 0 0 1 1 19 19 Apoteker Sten Grønved Nielsen 1 0 0 0 0 3 3 0 0 1 1 6 6 Tekstilhandler Helge Rosendahl Hansen 1 0 0 0 0 1 1 0 0 1 1 19 19 Gårdejer Hugo Skov Jakobsen 0,5 0 0 1 0,5 5 2,5 0 0 1 0,5 3 1,5 Projektleder Ole Harding Madsen 1 0 0 0 0 2 2 0 0 1 1 8 8 Kaptajn Søren Westerskov 1 0 0 0 0 1 1 0 0 1 1 8 8 Områdeleder Steen Staffeldt 0,5 ER. 0 0 0 0 1 0,5 0 0 0 0 3 1,5 Fuldmægtig Niels Jørgen Ellegaard 1ER. 1 1 0 0 2 2 0 0 0 0 19 19 Filialbestyrer Henrik Falden 0,3333ER. 1 0,3333 0 0 1 0,3333 0 0 0 0 2 0,6666 Fuldmægtig Helle Hindgavl 0,6667 1 0,6667 0 0 1 0,6667 1 0,6667 1 0,6667 5 3,3335 distriktssekretær Knud Paustian 0,5 0 0 1 0,5 5 2,5 1 0,5 1 0,5 3 1,5 Fuldmægtig Lars Bjørn Christiansen 0,5ER. 0 0 0 0 1 0,5 0 0 1 0,5 5 2,5 Account Manager Jakob Dons 0,3333ER. 1 0,3333 0 0 1 0,3333 0 0 0 0 3 0,9999
0,25 0,21 2,61 0,13 0,77 9,75
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Sparekassen Faaborg 9,33 6,67 1,00 1,00 19,00 7,00 8,30 2,71 2,29
165 2.29 SPAREKASSEN ØSTJYLLAND
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Regnskabschef Pernille Dejgaard 0,5 1 0,5 1 0,5 2 1 1 0,5 1 0,5 3 1,5 Kriminalass. Tage Lundgaard 0,5 0 0 1 0,5 1 0,5 0 0 1 0,5 3 1,5 Gårdejer Ernst Bilde 1 0 0 0 0 2 2 0 0 1 1 16 16 Konsulent Svend Thestrup 0,8333 0 0 0 0 1 0,8333 0 0 1 0,8333 5 4,1665 Fhv Borgmester Niels Erik Nielsen 1 0 0 1 1 2 2 0 0 1 1 16 16 Ejd. Adm. Ole Christoffersen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6666 Souschef Anders Østergaard 0,1667ER. 0 0 0 0 1 0,1667 0 0 0 0 1 0,1667 Fuldmægtig Ole Bundgaard 1ER. 1 1 0 0 1 1 0 0 0 0 13 13 Investeringsrådgiver René Bjørkmann 0,1667ER. 1 0,1667 0 0 2 0,3334 0 0 0 0 1 0,1667 Boligchef Peter Lorentzen 0,8333ER. 0 0 0 0 1 0,8333 0 0 0 0 5 4,1665 Borgmester Niels Borring 0,6667 0 0 0 0 1 0,6667 0 0 1 0,6667 8 5,3336 Produktionsassistent Lene Skouborg 0,1667 0 0 0 0 1 0,1667 1 0,1667 1 0,1667 1 0,1667 afdelingsdirektør Jan Olssen 0,6667ER. 0 0 0 1 0,6667 0 0 0 0 4 2,6668
0,21 0,26 1,34 0,09 0,64 8,37
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep)
Sparekassen Østjylland 7,83 5,00 0,00 0,00 8,00 5,04 5,60 1,59 1,43
166 2.30 DJURSLANDS BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Grosserer Erik Nymann 1 0 0 1 1 17 17 0 0 1 1 19 19 Administrerende direktør,Ole Fast 1 1 1 1 1 15 15 0 0 1 1 15 15 Gårdejer Jakob Arendt 1 0 0 1 1 1 1 0 0 1 1 14 14 Kunderådgiver Helle Quottrup 0,5ER. 0 0 0 0 1 0,5 1 0,5 0 0 3 1,5 Kunderådgiver Tina Klausen 1ER. 0 0 1 1 2 2 1 1 0 0 11 11 El installatør Ole Birk Nielsen 1 0 0 1 1 6 6 0 0 1 1 15 15 Direktør Poul Erik Sørensen 1 1 1 1 1 4 4 0 0 1 1 7 7 Forretningsfører Uffe Vithen 0,5 0 0 0 0 1 0,5 0 0 1 0,5 3 1,5
0,29 0,86 6,57 0,21 0,79 12,00
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Djurslands Bank A/S 6,50 5,00 0,00 1,00 8,00 11,78 14,00 0,68 0,57
167 2.31MAX BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Ingeniør Hans Fossing Nielsen 1 0 0 1 1 6 6 0 0 1 1 22 22 Direktør Dan Andersen 1 0 0 1 1 11 11 0 0 1 1 20 20 Systemtekniker Niels Henrik Andersen 1 0 0 0 0 1 1 0 0 1 1 9 9 Ingeniør Henrik Forssling 1 0 0 1 1 3 3 0 0 1 1 6 6 Direktør Sven Jacobsen 1 0 0 0 0 1 1 0 0 1 1 19 19 Direktør Steen Sørensen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6666 Kreditmedarbejder Mie Rahbek Hjorth 0,3333ER. 1 0,3333 0 0 1 0,3333 1 0,3333 0 0 2 0,6666 IT Konsulent Mogens Pedersen 1ER. 1 1 1 1 2 2 0 0 0 0 22 22 Direktør Kurt Aarestrup 1ER. 0 0 0 0 1 1 0 0 0 0 10 10 Glarmester Kai Nielsen 0,6667 0 0 1 0,6667 5 3,3335 0 0 1 0,6667 18 12,0006 InvesteringsrådgiverAne Hansen 0,6667ER. 1 0,6667 1 0,6667 1 0,6667 1 0,6667 0 0 9 6,0003
0,22 0,59 3,30 0,11 0,67 14,15
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Max Bank A/S 9,00 6,00 1,00 1,00 5,00 11,57 12,67 0,43 0,39
168 2.32 DIBA
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Formand Direktør Georg Knudsen 1 0 0 1 1 6 6 0 0 1 1 18 18 Næstformand AdvokatFrank Møller Nielsen 1 0 0 1 1 17 17 0 0 1 1 11 11 Direktør Poul K. Jeppesen 1 0 0 1 1 3 3 0 0 1 1 14 14 Ingeniør Hans Johansen 1 0 0 1 1 2 2 0 0 1 1 6 6 Direktør Henrik Meding 1 1 1 1 1 5 5 0 0 1 1 12 12 Direktør Claus Winther 0,8333 0 0 1 0,8333 6 4,9998 0 0 1 0,8333 5 4,1665 Kredit Konsulent Michael Frederiksen 1ER. 0 0 0 0 1 1 0 0 0 0 11 11 Erhvervskonsulent Charlotte Galvit 1ER. 1 1 0 0 1 1 1 1 0 0 7 7 Porteføljemanager Henrik Paulsen 1ER. 1 1 0 0 1 1 0 0 0 0 25 25 Direktør Jørgen Falck Henriksen 0,1667 0 0 1 0,1667 3 0,5001 0 0 1 0,1667 11 1,8337
0,33 0,67 4,61 0,11 0,67 12,22
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) DiBa Bank A/S 9,00 6,00 0,00 0,00 11,00 11,00 9,57 1,00 1,15
169 2.33 MIDDELFART SPAREKASSE
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Salgsingeniør Jørgen Eggert-Larsen 1 0 0 1 1 2 2 0 0 1 1 19 19 Advokat Steen Flemming Kjær 1 0 0 1 1 5 5 0 0 1 1 10 10 Jobkonsulent Søren Illum Nielsen 1 0 0 0 0 1 1 0 0 1 1 19 19 Civilingeniør Christian Schultz 1 0 0 1 1 2 2 0 0 1 1 16 16 Konsulent Ernst Würthrich 1 0 0 1 1 3 3 0 0 1 1 9 9 Headhunter Michaela Otto 0,3333 0 0 0 0 1 0,3333 1 0,3333 1 0,3333 2 0,6666 Souschef Michael Borum 1ER. 1 1 0 0 1 1 0 0 0 0 6 6 HR Konsulent Helle Lund Gregersen 1ER. 0 0 0 0 1 1 1 1 0 0 6 6 Udviklingskonsulent Ulrik Sørensen 0,3333ER. 1 0,3333 0 0 1 0,3333 0 0 0 0 2 0,6666 Elinstallatør Finn Henningsen 0,6667 0 0 1 0,6667 3 2,0001 0 0 1 0,6667 4 2,6668 Erhvervsrådgiver Torben Høholt Jensen 0,6667ER. 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668
0,15 0,52 2,04 0,15 0,67 10,19
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Middelfart Sparekasse 9,00 6,00 0,00 0,00 30,00 8,33 10,91 3,60 2,75
170 2.34 ØSTJYDSK BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Fabrikant Thorvald Christensen 1 0 0 1 1 7 7 0 0 1 1 22 22 Direktør Hans Jørgen Thybring Hansen 1 0 0 1 1 7 7 0 0 1 1 20 20 Murermester Einar Thygesen 1 0 0 1 1 8 8 0 0 1 1 20 20 Direktør Erik Aggerbo 0,1667 0 0 1 0,1667 1 0,1667 0 0 1 0,1667 1 0,1667 Gårdejer Jens Brøndum 0,8333 0 0 0 0 1 0,8333 0 0 1 0,8333 10 8,3 33 Privatkundechef Mogens Chortsen 0,1667ER. 0 0 0 0 1 0,1667 0 0 0 0 1 0,1667 Kreditrådgiver Axel Rønnekamp Nielsen 0,3333ER. 0 0 0 0 2 0,6666 0 0 0 0 2 0,6666 Bankfuldmægtig Kirsten Thygesen 0,3333ER. 0 0 0 0 1 0,3333 1 0,3333 0 0 7 2,3331 Landbrugschef Hans Poulsen 0,8333ER. 0 0 0 0 1 0,8333 0 0 0 0 12 9,9996
0,00 0,56 4,41 0,06 0,71 14,76
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Østjydsk Bank A/S 5,67 4,00 0,00 1,00 16,00 9,30 14,01 1,72 1,14
171 2.35 AARHUS LOKALBANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Godsejer Rasmus Juhl Rasmussen 1 0 0 1 1 16 16 0 0 1 1 17 17 Murermester Jørn Sørensen 1 0 0 1 1 5 5 0 0 1 1 9 9 Boghandler Esben Hammer 0,8333 0 0 1 0,8333 1 0,8333 0 0 1 0,8333 5 4,1665 Gårdejer Gert Lopdrup Pedersen 0,5 0 0 0 0 1 0,5 0 0 1 0,5 3 1,5 Afd. Souschef Per Enevoldsen 0,6667ER. 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668 IT Chef Preben Hansen 0,8333ER. 0 0 0 0 1 0,8333 0 0 0 0 12 9,9996 Økonomidirektør Anders Balle 0,5 1 0,5 1 0,5 4 2 0 0 1 0,5 15 7,5 Privatkundechef Svend Erik Hansen 0,333 0 0 0 0 1 0,333 0 0 1 0,333 12 3,996 Fotograf Jørn Bjørn De Place 0,1667 0 0 0 0 1 0,1667 0 0 1 0,1667 9 1,5003
0,09 0,57 4,52 0,00 0,74 9,83
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Aarhus Lokalbank Aktieselskab 5,83 4,33 0,00 1,00 21,00 6,37 6,38 3,30 3,29
172 2.36 SPAREKASSEN THY
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Advokat Jacob Schousgaard 1 0 0 1 1 17 17 0 0 1 1 6 6 Møbelhandler Søren Peter Yde 1 0 0 1 1 1 1 0 0 1 1 10 10 Økonomikonsulent Ivan Høgh Jensen 0,3333 1 0,3333 1 0,3333 1 0,3333 0 0 1 0,3333 10 3,333 Murermester Ricky Larsen 0,3333 0 0 0 0 3 0,9999 0 0 1 0,3333 2 0,6666 Malermester Finn Bjerg 1 0 0 1 1 4 4 0 0 1 1 11 11 Bogholder Mette Møller 1 0 0 0 0 2 2 1 1 1 1 16 16 Fhv. Afdelingsformand Anton Møller Thomsen 1 0 0 1 1 1 1 0 0 1 1 11 11 Fiskeeksportør Carsten Beith 0,5 0 0 1 0,5 5 2,5 0 0 1 0,5 3 1,5 Erhvervsrådgiver Finn Holst 0,333ER. 0 0 0 0 1 0,333 0 0 0 0 2 0,666 Erhvervsrådgiver Erik K. Nielsen 0,333ER. 0 0 1 0,333 3 0,999 0 0 0 0 2 0,666 Privatrådgiver Per Brink Rasmussen 1ER. 0 0 0 0 1 1 0 0 0 0 14 14 Afdelingsbestyrer Per G. Andersen 0,5ER. 0 0 0 0 1 0,5 0 0 0 0 3 1,5 Lærer Jens Hald 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6666 Kunderådgiver Rosa Irene Gasberg Vestergaard 0,3333 ER. 0 0 0 0 1 0,3333 10,3333 0 0 113,6663 Ejendomsmægler Harry Jensen Kristensen 0,6667 0 0 1 0,6667 6 4,0002 0 0 1 0,6667 4 2,6668 Lærer Preben Dahlgaard 0,5 0 0 0 0 1 0,5 0 0 1 0,5 3 1,5
0,03 0,57 3,62 0,13 0,75 8,34
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Thy, Sparekassen 10,17 7,67 0,00 0,00 15,00 5,30 5,85 2,83 2,56
173 2.37 MORSØ BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Købmand Hans Hangaard Pedersen 1 0 0 1 1 5 5 0 0 1 1 17 17 Tømrermester Kurt Justesen 1 0 0 1 1 5 5 0 0 1 1 8 8 Gårdejer Kris Thorhauge 1 0 0 0 0 1 1 0 0 1 1 9 9 Direktør Klaus Krog Hansen 0,1667 1 0,1667 1 0,1667 6 1,0002 0 0 1 0,1667 1 0,1667 Projektkoordinator Marianne Andsager 1 0 0 0 0 1 1 1 1 1 1 6 6 Direktør Mogens Ringgaard 0,5 0 0 1 0,5 3 1,5 0 0 1 0,5 3 1,5 Afd. Chef Peter Mikkelsen 1 ER. 0 0 0 0 1 1 0 0 0 0 27 27 Erhvervskundechef Benny Nielsen 0,5ER. 0 0 0 0 1 0,5 0 0 0 0 3 1,5 Marketing-/ IT KonsulentJohannes Veje 0,5ER. 0 0 0 0 1 0,5 0 0 0 0 3 1,5 Direktør Henning Aage Petersen 0,8333 0 0 1 0,8333 2 1,6666 0 0 1 0,8333 9 7,4997 Gårdejer Martin N. Klausen 0,5 0 0 1 0,5 5 2,5 0 0 1 0,5 18 9 Kunderådgiver Else Krogh 0,5ER. 0 0 0 0 0 0 1 0,5 0 0 24 12
0,02 0,47 2,43 0,18 0,71 11,78
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Morsø Bank, 8,50 6,00 0,00 0,00 7,00 6,99 7,27 1,00 0,96
174 2.38 SKJERN BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Carsten Thygesen 1 0 0 1 1 38 38 0 0 1 1 6 6 Gårdejer Jens Christian Ostersen 1 0 0 0 0 1 1 0 0 1 1 12 12 Fabrikant Børge Lund Hansen 1 0 0 1 1 3 3 0 0 1 1 8 8 Bygmester Holger Larsen 1 0 0 1 1 8 8 0 0 1 1 7 7 Souschef Lars Andresen 0,3333ER. 0 0 0 1 0,3333 0 0 0 0 2 0,6666 Landbrugsrådgiver Metha Kirstine Thomsen 0,5ER. 0 0 0 0 1 0 ,5 1 0,5 0 0 3 1,5 Gårdejer Bendt Kirkegaard Bendtsen 0,5 0 0 1 0,5 4 2 0 0 1 0,5 1 9 9,5 Fondschef Claus Christensen 0,3333ER. 1 0,3333 1 0,3333 1 0,3333 0 0 0 0 2 0,6666 Erhvervsrådgiver Allan Vad 0,6667ER. 1 0,6667 0 0 5 3,3335 0 0 0 0 4 2,6668
0,16 0,61 8,93 0,08 0,71 7,58
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Skjern Bank, 6,33 4,50 0,00 1,00 10,00 5,33 8,50 1,88 1,18
175 2.39 SPAREKASSEN HOBRO
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Radiotekniker Hans Jørgen Nielsen 1 0 0 1 1 5 5 0 0 1 1 10 10 Forretningsindehaver Bent Nielsen Bjørn 1 0 0 1 1 1 1 0 0 1 1 12 12 Gårdejer Torben Andersen 1 0 0 0 0 1 1 0 0 1 1 8 8 Gårdejer Niels Fomsgaard 1 0 0 1 1 1 1 0 0 1 1 13 13 Traktorforhandler Svend Erik Madsen 0,5 0 0 0 0 4 2 0 0 1 0,5 3 1,5 Landmand Vagn Refsgaard Olsen 0,1667 0 0 1 0,1667 1 0,1667 0 0 1 0,1667 14 2,3338 Bygmester Henning Sørensen 0,83333 0 0 1 0,83333 3 2,49999 0 0 1 0,83333 5 4,16665 Kunderådgiver Anette Møller 0,3333ER. 0 0 0 0 1 0,3333 1 0,3333 0 0 2 0,6666 Afdelingsdirektør Per Norup Olesen 0,3333ER. 0 0 0 0 1 0,3333 0 0 0 0 20,6666 Direktør Henning Munk Nielsen 0,5 0 0 1 0,5 3 1,5 0 0 1 0,5 14 7 Likviditetschef Henning Ørum Rasmussen 1ER. 1 1 0 0 1 1 0 0 0 0 10 10 Landbrugskundechef Finn Elton Sørensen 0,6667ER. 0 0 0 0 1 0,6667 0 0 0 0 14 9,3338 Privatkunderådgiver Inge Houg Jakobsen 0,6667ER. 0 0 0 1 0,6667 1 0,6667 0 0 4 2,6668
0,11 0,50 1,91 0,11 0,67 9,04
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Hobro, Sparekassen 9,00 6,00 1,00 0,00 14,00 6,26 7,25 2,24 1,93
176 2.40 FRØS HERREDS SPAREKASSE
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Fabrikschef Jørgen Kring Jensen 1 0 0 1 1 5 5 0 0 1 1 13 13 Centerleder Søren Tang Sørensen 1 0 0 0 0 1 1 0 0 1 1 12 12 Lærer Leif Bolvig 1 0 0 0 0 1 1 0 0 1 1 8 8 Centerindehaver Gerda Feddern 1 0 0 0 0 1 1 1 1 1 1 8 8 Anlægsgartner Tage Holm 1 0 0 0 0 1 1 0 0 1 1 12 12 Bogtrykker Sven Christian Ravn 1 0 0 1 1 1 1 0 0 1 1 8 8 Boligkonsulent Mai-Britt Fig 1ER. 0 0 0 0 1 1 1 1 0 0 8 8 Erhvervskundechef Ole V. B. Andersen 0,6667 ER. 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668 Gartner Nis Christian Jacobsen 1 0 0 0 0 1 1 0 0 1 1 8 8 Kunderådgiver Kirsten Cathrine Valentin Andresen 0,3333ER. 0 0 0 0 1 0,3333 1 0,3333 0 0 12 3,9996 Jette Rosenkilde Clausen 1 0 0 0 0 1 1 1 1 1 1 14 14
0,00 0,20 1,40 0,33 0,80 9,77
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Frøs Herreds Sparekasse 10,00 8,00 0,00 0,00 8,75 8,87 10,38 0,99 0,84
177 2.41 GRØNLANDSBANKEN
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Bent Højgaard Jakobsen 0,6667 1 0,6667 1 0,6667 4 2,6668 0 0 1 0,6667 4 2,6668 Direktør Frank Olsvig Bagger 0,1667 0 0 1 0,1667 4 0,6668 0 0 1 0,1667 1 0,1667 Ingeniør Kristian Lennert 1 0 0 1 1 3 3 0 0 1 1 6 6 Direktør Gunnar I Lida 0,6667 0 0 0 0 1 0,6667 0 0 1 0,6667 4 2,6668 Bank Ass. Helle Mark 0,3333ER. 0 0 0 0 1 0,3333 1 0,3333 1 0,3333 2 0,6666 Direktør Jørn Skov Nielsen 0,3333 1 0,3333 1 0,3333 3 0,9999 0 0 1 0,3333 2 0,6666 Kunderådgiver Inger Anne Marie Poulsen 1ER. 0 0 0 0 1 1 1 1 0 0 7 7 Controller Jette Radich 0,3333ER. 0 0 1 0,3333 1 0,3333 1 0,3333 0 0 8 2,6664 Forretningsindehaver Stefan Hviid 0,6667 0 0 0 0 1 0,6667 0 0 1 0,6667 4 2,6668 Vicedirektør Ejvind Christoffersen 0,6667 0 0 1 0,6667 1 0,6667 0 0 1 0,6667 25 16,6675 Filialleder Amma Knudsen 0,6667ER. 0 0 0 0 1 0,6667 1 0,6667 0 0 6 4,0002 Service supporter Niels Anton Bank Nielsen 0,6667ER. 0 0 0 0 2 1,3334 0 0 0 0 42,6668 Konsul Lars Peter Danielsen 0,5 0 0 1 0,5 2 1 0 0 1 0,5 15 7,5 Bankdirektør Ole Thomasen 0,1667 1 0,1667 0 0 1 0,1667 0 0 1 0,1667 8 1,3336 Kreditchef Jakob Brogaard 0,3333 0 0 1 0,3333 14 4,6662 0 0 1 0,3333 17 5,6661 Tidl ombudsmand Gunnar Martens 0,16667 0 0 0 0 1 0,16667 0 0 1 0,16667 1 0,16667
0,14 0,48 2,28 0,28 0,68 7,58
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Grønlandsbanken 8,33 5,33 0,00 0,00 7,00 7,13 4,20 0,98 1,67
178 2.42 SPAREKASSEN FARSØ
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Søren Øgaard 1 0 0 1 1 5 5 0 0 1 1 10 10 Tømmerhandler Frits Ebbesø 1 0 0 1 1 6 6 0 0 1 1 6 6 Gårdejer Torben Bach 0,5 0 0 0 0 1 0,5 0 0 1 0,5 3 1,5 Møbelfabriksdirektør Toft H. Kristensen 0,3333 0 0 1 0,3333 15 4,9995 0 0 1 0,3333 15 4,9995 Lærer Vagn Liltorp 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 8 2,6664 Kartoffelproducent Lars Peter Højen Justesen 0,6667 0 0 0 0 1 0,6667 0 0 1 0,6667 4 2,6668 Margit Krogh 0,5 0 0 0 1 0,5 1 0,5 1 0,5 8 4 Sygeplejerske Bente Bach Poulsen 0,5 0 0 0 0 1 0,5 1 0,5 1 0,5 3 1,5 Fuldmægtig Søren Kjær 1ER. 0 0 0 0 1 1 0 0 0 0 9 9 Kundeservice Inger Pedersen 0,1667ER. 0 0 1 0,1667 1 0,1667 1 0,1667 0 0 12 2,0004 Fuldmægtig Brian Otte 0,8333ER. 0 0 0 0 1 0,8333 0 0 0 0 5 4,1665 Købmand Aksel Pedersen 0,8333 0 0 0 0 1 0,8333 0 0 1 0,8333 1915,8327 Overassistent Bjarne Mikkelsen 0,8333ER. 0 0 0 0 1 0,8333 0 0 0 0 12 9,9996
0,00 0,29 2,61 0,14 0,67 8,74
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Farsø, Sparekassen 8,50 5,67 1,00 0,00 10,00 5,72 5,46 1,75 1,83
179 2.43EBH BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Egon Korsbæk 1 0 0 1 1 49 49 0 0 1 1 6 6 Forretningsindehaver Jens Peter Mortensen 1 0 0 1 1 12 12 0 0 1 1 16 16 Direktør Jens Belling 0,2 1 0,2 1 0,2 28 5,6 0 0 1 0,2 1 0,2 Dambrugsejer Aage S. Christophersen 1 0 0 1 1 4 4 0 0 1 1 15 15 Skoleinspektør Carl Chr. Nielsen 0,6 0 0 0 0 3 1,8 0 0 1 0,6 3 1,8 Reg. Revisor Anna Breum 0,6 1 0,6 1 0,6 4 2,4 1 0,6 1 0,6 3 1,8 Souschef Vagn Hav Christensen 1ER. 0 0 1 1 5 5 0 0 0 0 9 9 Fuldmægtig Jørn Ø. Jensen 1ER. 0 0 1 1 3 3 0 0 0 0 15 15 Projektchef Michael M. Christensen 0,8ER. 1 0,8 1 0,8 14 11,2 0 0 0 0 4 3,2 Elinstallatør Keld Aagesen 0,8 0 0 1 0,8 5 4 0 0 1 0,8 4 3,2 Gårdejer Valdemar Møller 1 0 0 1 1 11 11 0 0 1 1 12 12 Boligrådgiver Poul Hansen 0,4ER. 0 0 0 0 2 0,8 0 0 0 0 6 2,4 Forsikringskonsulent Karlo Kjær 0,4 0 0 1 0,4 2 0,8 0 0 1 0,4 9 3,6
0,16 0,90 11,25 0,06 0,67 9,07
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) ebh bank a/s 9,83 6,67 1,00 1,00 17,00 6,86 6,62 2,48 2,57
180 2.44 SVENDBORG SPAREKASSE
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Advokat Arne Knudsen 1 0 0 1 1 32 32 0 0 1 1 17 17 Lektor Jeppe Gorm Frederiksen 1 0 0 0 0 1 1 0 0 1 1 12 12 Direktør Peder Hviid 1 0 0 1 1 5 5 0 0 1 1 12 12 Adm Direktør Niels Peter Nøddeskou-Fink 0,3333ER. 0 0 0 0 2 0,6666 0 0 0 0 2 0,6666 Kunderådgiver Rasmus Stougaard Jensen 0,5ER. 0 0 0 0 1 0,5 0 0 0 0 3 1,5 Erhvervskundechef Jan Højer Kristensen 0,6667ER. 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668 Arkitekt Børge Clausen 0,6667 0 0 1 0,6667 6 4,0002 0 0 1 0,66 67 5 3,3335 Erhvervsrådgiver Jan Pilegaard 0,5ER. 0 0 0 0 1 0,5 0 0 0 0 9 4,5
0,00 0,47 7,82 0,00 0,65 9,47
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Svendborg Sparekasse 5,67 3,67 0,00 0,00 7,75 6,71 11,08 1,15 0,70
181
2.45 TOTALBANKEN
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Bygmester Poul Juhl Fischer 1 0 0 1 1 3 3 0 0 1 1 19 19 Borgmester Finn Brunse 0,8333 0 0 1 0,8333 6 4,9998 0 0 1 0,83 33 5 4,1665 Autoforhandler Gunner Lægsgaard 1 0 0 0 0 1 1 0 0 1 1 13 13 Advokat C. C. Horn Andersen 1 0 0 1 1 5 5 0 0 1 1 10 10 Fuldmægtig Gitte Stentebjerg 1 ER. 0 0 0 0 1 1 1 1 0 0 12 12 Investeringsrådgiver Claus Lyngbakke-Hellesøe 0,6667 ER. 0 0 0 0 1 0,6667 0 0 0 0 42,6668 Kunderådgiver Steen Hansen 0,3333ER. 0 0 0 0 1 0,3333 0 0 0 0 8 2 ,6664 Tidl Borgmester Knud Friborg 0,1667 0 0 1 0,1667 1 0,1667 0 0 1 0,1667 20 3,334
0,00 0,50 2,69 0,17 0,67 11,14
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep)
Totalbanken A/S 6,00 4,00 0,00 0,00 8,67 8,34 9,90 1,04 0,88
182 2.46 TØNDER BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Konsulent Carsten D. Andersen 1 1 1 1 1 3 3 0 0 1 1 17 17 Facilitator Birgit Thye-Petersen 1 0 0 1 1 4 4 1 1 1 1 10 10 Direktør Christian Frisk 1 0 0 1 1 3 3 0 0 1 1 8 8 El-Installatør Hans L. Hansen Holm 1 0 0 1 1 3 3 0 0 1 1 17 17 Gårdejer Adolf Nissen 1 0 0 1 1 4 4 0 0 1 1 15 15
0,20 1,00 3,40 0,20 1,00 13,40
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep)
Tønder Bank A/S 5,00 5,00 0,00 1,00 16,00 13,40 13,40 1,19 1,19
183 2.47 DRONNINGLUND SPAREKASSE
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Gårdejer Højer Yde Skaksen 1 0 0 1 1 2 2 0 0 1 1 20 20 fhv. Autoforhandler Tage Peter Larsen 1 0 0 1 1 3 3 0 0 1 1 20 20 Gårdejer Per Søren Uhrenholt 1 0 0 0 0 1 1 0 0 1 1 19 19 Reg. Revisor Inge Møller Ernst 0,1667 1 0,1667 0 0 1 0,1667 1 0,1667 1 0,1667 1 0,1667 Tømrermester Jens M. Kaasgaard 1 0 0 0 0 1 1 0 0 1 1 9 9 Murermester Erik Frederiksen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6666 Fuldmægtig Steen Nysum Kristensen 1ER. 0 0 0 0 1 1 0 0 0 0 6 6 Fuldmægtig Lone Ellen Vestergaard 0,3333 ER. 0 0 0 0 1 0,3333 1 0,3333 0 0 2 0,6666 Fuldmægtig Tove Schjønning Christensen 0,3333ER. 0 0 0 0 1 0,3333 1 0,3333 0 0 2 0,6666 Skolechef Arthur Corneliussen 0,8333 0 0 0 0 1 0,8333 0 0 1 0,8333 12 9,9996 Erhvervskundechef Peter Lund Nielsen 0,6667ER. 0 0 0 0 1 0,6667 0 0 0 0 8 5,3336 Murermester Peter Rasmussen 0,6667 0 0 0 0 1 0,6667 0 0 1 0,6667 19 12,6673
0,02 0,24 1,36 0,10 0,72 12,51
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Dronninglund Sparekasse 8,33 4,00 0,00 0,00 19,00 8,70 11,44 2,18 1,66
184 2.48 BRØRUP SPAREKASSE
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Dyrlæge Mogens Slotved 1 0 0 1 1 2 2 0 0 1 1 21 21 Direktør Knud Bruun 1 0 0 0 0 1 1 0 0 1 1 10 10 Falckredder Anton Attermann 0,5 0 0 0 0 1 0,5 0 0 1 0,5 3 1,5 Fhv. SkoleinspektørHenning O. Kristensen 1 0 0 0 0 1 1 0 0 1 1 15 15 Smedemester Aslak Skjøth 1 0 0 1 1 4 4 0 0 1 1 7 7 Gårdejer Hans Esbjerg 0,5 0 0 0 0 1 0,5 0 0 1 0,5 15 7,5
0,00 0,40 1,80 0,00 1,00 12,40
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Brørup Sparekasse 5,00 5,00 0,00 0,00 23,00 11,83 10,33 1,94 2,23
185 2.49 SKÆLSKØR BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Godsejer Peter Melchior 1 0 0 1 1 9 9 0 0 1 1 9 9 Direktør Søren Peter Nielsen 1 0 0 1 1 14 14 0 0 1 1 11 11 Direktør Christian Boye 0,6667 0 0 1 0,6667 2 1,3334 0 0 1 0,6667 4 2,6668 Finansdirektør Henning Skovlund 0,3333 1 0,3333 1 0,3333 10 3,333 0 0 1 0,3333 2 0,6666 Erhvervskundechef Freddy Hansen 1ER 0 0 1 1 1 1 0 0 0 0 8 8 Erhvervscenterdirektør Per Vesterholm 0,6667ER 0 0 1 0,6667 4 2,6668 0 0 0 0 4 2,6668 Gårdejer Paul Valling Andersen 0,6667 0 0 1 0,6667 5 3,3335 0 0 1 0,6667 15 10,0005 Aut. Installatør Erik Langkjær 0,3333 0 0 1 0,3333 4 1,3332 0 0 1 0,3333 15 4,9995 Økonomichef Marianne Bodil Stensby Hansen 0,3333ER 0 0 0 0 1 0,3333 1 0,3333 0 0 4 1,3332
0,06 0,94 6,06 0,06 0,67 8,39
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Skælskør Bank Aktieselskab 6,00 4,00 0,00 0,00 17,00 8,00 6,38 2,13 2,66
186 2.50 KREDITBANKEN
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Formand Ulrich Jansen 1 0 0 1 1 6 6 0 0 1 1 23 23 Elektriker Gerth L. Møller 1 0 0 1 1 7 7 0 0 1 1 23 23 Indkøbschef Heinrich C. Clausen 1 0 0 0 0 1 1 0 0 1 1 14 14 Direktør Hans B. Schlaikier 1 0 0 1 1 8 8 0 0 1 1 10 10 Direktør Peter Rudbeck 1 0 0 1 1 8 8 0 0 1 1 13 13 Skatterådgiver Henrik Meldgaard 0,1667 1 0,1667 1 0,1667 3 0,5001 0 0 1 0,1667 1 0,1667 Direktør Erik Krag 0,8333 0 0 1 0,8333 5 4,1665 0 0 1 0,8333 22 18,3326
0,03 0,83 5,78 0,00 1,00 16,92
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep)
Kreditbanken A/S 6,00 6,00 0,00 0,00 10,00 14,50 14,50 0,69 0,69
187 2.51 SALLING BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Adm Direktør Poul Østergaard Hansen 1 0 0 1 1 3 3 0 0 1 1 18 18 Gårdejer Mogens Glud Jensen 1 0 0 1 1 3 3 0 0 1 1 16 16 Adm. Direktør Per Albæk 0,6667 0 0 1 0,6667 8 5,3336 0 0 1 0,66 67 4 2,6668 Direktør Christian T. Østergaard 1 0 0 1 1 6 6 0 0 1 1 9 9 It-Chef Johnny Lindhard Jensen 0,6667 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668 Bankassistent Hanne Birgit Williams 0,6667ER 0 0 0 0 1 0,66 67 1 0,6667 0 0 4 2,6668 Direktør Sven Erik Malmberg 0,3333 0 0 1 0,3333 1 0,3333 0 0 1 0,3333 10 3,333 Marketingchef Bent Plougstrup 0,3333ER 0 0 0 0 1 0,3333 0 0 0 0 5 1,6665 Fuldmægtig Viktor Flodgaard 0,1667ER 0 0 0 0 1 0,1667 0 0 0 0 1 0 ,1667 Kreditdirektør Lene Dyhrberg Rasmussen 0,1667ER 1 0,1667 0 0 1 0,1667 1 0,1667 0 0 2 0,3334
0,03 0,67 3,28 0,14 0,67 9,42
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Salling Bank A/S 6,00 4,67 0,00 0,00 14,00 8,65 8,61 1,62 1,63
188 2.52 BASISBANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Advokat Søren Johansen 0,5 0 0 1 0,5 45 22,5 0 0 1 0,5 3 1,5 Adm Direktør Michael Kaa Andersen 1 1 1 1 1 81 81 0 0 1 1 7 7 Adm Direktør Knud-Erik Andreasen 1 0 0 1 1 68 68 0 0 1 1 7 7 Direktør Henrik Gorm Nielsen 0,5 1 0,5 1 0,5 72 36 0 0 0 0 3 1,5 Investeringsdirektør Jesper Østerhegn Jensen 1 1 1 1 1 55 55 0 0 0 0 7 7 Direktør Peter Scheuer Jensen 0,5 1 0,5 1 0,5 35 17,5 0 0 1 0,5 3 1,5 Direktør Jesper Pedersen Damgaard 0,5 0 0 1 0,5 67 33,5 0 0 1 0,5 3 1,5 Professor Bjarne Astrup Jensen 0,5 1 0,5 1 0,5 1 0,5 0 0 1 0,5 3 1,5 Bankdirektør Kim Bai Wadstrøm 0,5 1 0,5 1 0,5 9 4,5 0 0 0 0 3 1,5
0,67 1,00 53,08 0,00 0,67 5,00
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Basisbank A/S 6,00 6,00 0,00 0,00 3,00 4,30 3,33 0,70 0,90
189 2.53 VESTFYNS BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Georg Gundersen 1 0 0 1 1 10 10 0 0 0 0 22 22 Adm Direktør Bent Jensen 1 0 0 1 1 8 8 0 0 1 1 12 12 Direktør Bent Christensen 1 0 0 1 1 2 2 0 0 1 1 9 9 Malermester Vagn Kamp Larsen 1 0 0 1 1 2 2 0 0 1 1 7 7 Direktør Peter Cederfeld de Simonsen 0,1667 0 0 1 0,1667 5 0,8335 0 0 1 0,1667 1 0,1667 Rådgiver Kurt Erik Hansen 0,6667ER 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668 Kunderådgiver Helle Flensted 0,3333ER 0 0 0 0 1 0,3333 1 0,3333 0 0 2 0,6666 Souchef Jette Rosenberg 0,6667ER 0 0 0 0 1 0,6667 1 0,6667 0 0 4 2,6668 Kunderådgiver Ole Bach Jensen 0,6667ER 0 0 0 0 1 0,6667 0 0 0 0 4 2,6668 Gårdejer Anders Rasmussen 0,83333 0 0 1 0,83333 2 1,66666 0 0 1 0,83333 6 4,99998
0,00 0,68 3,66 0,14 0,55 8,71
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Vestfyns Bank A/S 7,33 5,00 1,00 1,00 8,00 8,33 9,19 0,96 0,87
190 2.54 NORDFYNS BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
AutomobilforhandlerAllan Nielsen 1 0 0 1 1 3 3 0 0 1 1 10 10 Guldsmed Per Maegaard 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6666 Entreprenør Lars Rasmussen 0,1667 0 0 0 0 1 0,1667 0 0 1 0,1667 1 0,1667 Kundechef Flemming Møllgaard Jensen 1 0 0 0 0 1 1 0 0 1 1 18 18 Bankassistent Birgit Andersen 1ER 0 0 1 1 1 1 1 1 0 0 6 6 Underdirektør Arne Jørgensen 1ER 0 0 1 1 1 1 0 0 0 0 17 17 Marketingchef Freddy Tindhof 0,8333 0 0 1 0,8333 2 1,6666 0 0 1 0,8333 14 11,6662 Skoleinspektør Jens Otto Dalhøj 0,6667 0 0 1 0,6667 9 6,0003 0 0 1 0,6667 10 6,667
0,00 0,75 2,36 0,17 0,67 11,69
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Nordfyns Bank 6,00 4,00 0,00 1,00 4,00 9,75 7,86 0,41 0,51
191 2.55 LOLLANDS BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Formand, proprietær Peter Ege Olsen 1 0 0 1 1 4 4 0 0 1 1 18 18 Næstformand, salgsdirektørMogens Bloch 1 0 0 1 1 8 8 0 0 1 1 17 17 Adm. Dir. Rune West Pedersen 0,1667 0 0 1 0,1667 2 0,3334 0 0 1 0,1667 1 0,1667 Direktør Svend Aage Sørensen 1 0 0 1 1 3 3 0 0 1 1 10 10 Kreditchef Søren Bursche 1ER 0 0 0 0 1 1 0 0 0 0 17 17 Direktør Michael Pedersen 0,5ER 0 0 0 0 1 0,5 0 0 0 0 3 1,5 Kunderådgiver Mogens Kragh Rasmussen 0,5ER 0 0 0 0 1 0,5 0 0 0 0 12 6 Direktør Børge Christensen 0,8333 0 0 1 0,8333 7 5,8331 0 0 1 0 ,8333 15 12,4995
0,00 0,67 3,86 0,00 0,67 13,69
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Lollands Bank, Aktieselskab 6,00 4,00 0,00 0,00 10,00 11,63 11,53 0,86 0,87
192 2.56 SPAREKASSEN FOR NR. NEBEL OG OMEGN
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Gårdejer Sven Andresen 1 0 0 0 0 1 1 0 0 1 1 13 13 El installatør Jens Stenberg 1 0 0 1 1 7 7 0 0 1 1 18 18 Gårdejer Flemming Johannessen 1 0 0 0 0 1 1 0 0 1 1 15 15 Gårdejer Thorkil Hansen 1 0 0 0 0 1 1 0 0 1 1 14 14 Kunderådgiver Jens Nielsen 1ER 0 0 1 1 1 1 0 0 0 0 8 8 Konstruktør Flemming Kjerkegaard 1 0 0 0 0 2 2 0 0 1 1 8 8
0,00 0,33 2,17 0,00 0,83 12,67
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Nr. Nebel og Omegn, Sparekassen for 6,00 5,00 0,00 0,00 12,00 12,67 13,60 0,95 0,88
193 2.57 SPAREKASSEN HVETBO
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Restauratør Christian Hem 0,8333 0 0 0 0 1 0,8333 0 0 1 0,8333 5 4,1665 Læge Jan Bruhn 0,8333 0 0 0 0 1 0,8333 0 0 1 0,8333 5 4,1665 Gårdejer Edel Pilgaard 1 0 0 1 1 1 1 1 1 1 1 8 8 Gårdejer Lars Christian Jensen 1 0 0 1 1 5 5 0 0 1 1 12 12 Major Jørgen Erik Lund 1 0 0 0 0 2 2 0 0 1 1 11 11 Aktiechef Michael Thomsen 0,1667ER 1 0,1667 0 0 1 0,1667 0 0 0 0 1 0,1667 Rådgiver Mona H. Christoffersen 0,1667ER 0 0 0 0 1 0,1667 1 0,1667 0 0 1 0,1667 Rådgiver Morten Pilegaard 0,1667ER 0 0 0 0 1 0,1667 0 0 0 0 1 0,1667 Sparekasseassistent Bøje Lundtoft 0,8333ER 0 0 0 0 1 0,8333 0 0 0 0 54,1665 Boligansvarlig Kaj Christensen 0,8333ER 0 0 0 0 1 0,8333 0 0 0 0 5 4,1665 Direktør Bent Honoré 0,8333 0 0 1 0,8333 16 13,3328 0 0 1 0,8333 5 4,1665 Souschef Torben Rye 0,1667 0 0 0 0 1 0,1667 0 0 0 0 8 1,3336 Gårdejer Erik Gade 0,1667 0 0 0 0 1 0,1667 0 0 1 0,1667 4 0,6668
0,02 0,35 3,19 0,15 0,71 6,79
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Sparekassen Hvetbo A/S 8,00 5,83 0,00 1,00 7,00 5,46 5,69 1,28 1,23
194 2.58 SPAR SALLING SPAREKASSE
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Formand Gårdejer Aksel Christensen 1 0 0 1 1 2 2 0 0 1 1 6 6 Næstformand GårdejerOle Kristensen 1 0 0 1 1 3 3 0 0 1 1 8 8 Gårdejer Jens Jørgensen 1 0 0 0 0 1 1 0 0 1 1 6 6 Adjunkt Niels Krawack 1 0 0 0 0 1 1 0 0 1 1 8 8 Chauffør Leif Rasmussen 0,5 0 0 1 0,5 1 0,5 0 0 1 0,5 3 1,5 Cand Merc Lars Yde Knudsen 1 1 1 0 0 1 1 0 0 1 1 8 8 Sekretariatschef May-Britt Nygård 1ER 0 0 0 0 1 1 1 1 0 0 6 6 Afdelingsleder Emil Simonsen 1 0 0 1 1 1 1 0 0 1 1 18 18 Fuldmægtig Iris Smed Hansen 1ER 0 0 0 0 1 1 1 1 0 0 6 6 Ungdomsskoleinspektør Finn Vitting Andersen 0,5 0 0 0 0 1 0,5 0 0 1 0,5 3 1,5 Direktør Arne Nielsen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6 666
0,11 0,38 1,32 0,21 0,79 7,47
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Spar Salling Sparekasse 9,33 7,33 0,00 0,00 6,00 6,73 6,41 0,89 0,94
195 2.59 SPAREKASSEN I SKALS
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Centralforvaltningschef Niels Haarbo Vasegaard 1 0 0 0 0 1 1 0 0 1 1 18 18 Direktør Leif Gade 0,6667 0 0 1 0,6667 2 1,3334 0 0 1 0,6667 4 2,6668 Regionschef Helle Flarup 1 0 0 0 0 1 1 1 1 1 1 10 10 Entrprenør Kristian Hansen 0,5 0 0 1 0,5 1 0,5 0 0 1 0,5 3 1,5 Landbrugskonsulent Anders Åge K. Laier 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 2 0,6666 Filialdirektør Arne Bech 0,3333ER 0 0 0 0 1 0,3333 0 0 0 0 2 0,6666 Vurderingsansvarlig Kjeld Højhus Jeppesen 0,3333ER 0 0 0 0 1 0,3333 0 0 0 0 2 0,6666 Investeringsrådgiver Birgitte Holm Johansen 0,3333 ER 0 0 0 0 1 0,3333 1 0,3333 0 0 2 0,6666 Ekspeditionschef Klaus Becker Edal 0,6667ER 0 0 0 0 1 0,6667 0 0 0 0 1610,6672 Fhv Købmand Erling Thorup 0,6667 0 0 0 0 1 0,6667 0 0 1 0,6667 16 10,6672 Gårdejer Jørgen Buhl Christensen 0,5 0 0 0 0 1 0,5 0 0 1 0,5 13 6,5 Erhvervsrådgiver Knud Jensen 0,3333ER 0 0 0 0 1 0,3333 0 0 0 0 3 0,9999 Kunderådgiver Doris Mikkelsen 0,5ER 0 0 0 0 1 0,5 1 0,5 0 0 3 1,5 Mekaniker Karl Erik Kristensen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 15 4,9995
0,00 0,16 1,09 0,24 0,67 9,36
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep)
Skals, Sparekassen i 7,50 5,00 0,00 0,00 16,00 7,79 6,88 2,05 2,33
196 2.60 DEN ALMENNYTTIGE ANDELSKASSE MERKUR
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Arkitek Morten Gunge 1 0 0 0 0 4 4 0 0 1 1 16 16 Landmand Henrik Tølløse 1 0 0 0 0 3 3 0 0 1 1 8 8 Projektleder Klaus Loehr-Petersen 0,5 0 0 0 0 1 0,5 0 0 1 0,5 3 1,5 Bogholder Anne-Birgitte Olsen 1 0 0 0 0 1 1 1 1 1 1 9 9 Revisor Peer Jøker 1 1 1 1 1 20 20 0 0 1 1 9 9 Civiløkonom Finn Madsen 0,3333 1 0,3333 1 0,3333 1 0,3333 0 0 1 0,3333 2 0,6666 Privatkundechef Annette Lindholt 0,3333ER 0 0 0 0 1 0,3333 1 0,3333 0 0 2 0,6666 Privatkunderådgivning Henrik Kronel 0,3333ER 0 0 0 0 1 0,3333 0 0 0 0 20,6666 Privatkundechef Carsten Ringgaard 0,3333ER 0 0 0 0 1 0,3333 0 0 0 0 20,6666 Direktør Jørn Ussing Larsen 0,5 0 0 0 0 2 1 0 0 1 0,5 10 5 Konsulent Bjarne Petersen 0,6667 0 0 0 0 1 0,6667 0 0 1 0,6667 16 10,6672
0,19 0,19 4,50 0,19 0,86 8,83
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Merkur, Den Almennyttige Andelskasse 7,00 6,00 0,00 0,00 16,00 5,62 7,48 2,85 2,14
197 2.61MØNS BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Fabrikant Karsten Sørensen 1 0 0 1 1 4 4 0 0 1 1 13 13 Proprietær Jens Ravn 1 0 0 1 1 4 4 0 0 1 1 11 11 Sygehjælper Marianne Engers 1 0 0 0 0 1 1 1 1 1 1 6 6 Gårdejer Knud Larsen 0,6667 0 0 1 0,6667 2 1,3334 0 0 1 0,6667 4 2,6668 UndervisningskonsulentAgnethe Hviid 1 0 0 0 0 3 3 1 1 1 1 6 6 Gårdejer Henning Jensen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 16 5,3328
0,00 0,53 2,73 0,40 1,00 8,80
Board Size incl. Board Size Board Years Board Years CEO/Board CEO/Board Bank Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Møns Bank, A/S 5,00 5,00 0,00 0,00 21,00 9,33 7,33 2,25 2,86
198 2.62 SPAREKASSEN LIMFJORDEN
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
El-Installatør Kaj Pedersen 0,6667 0 0 1 0,6667 2 1,3334 0 0 1 0,6667 4 2,6668 Murermester Poul Nørgård Larsen 0,6667 0 0 1 0,6667 2 1,3334 0 0 1 0,6667 4 2,6668 Revisor John Pedersen 1 1 1 1 1 3 3 0 0 1 1 7 7 Chauffør Hans Jørgen Jensen 1 0 0 0 0 1 1 0 0 1 1 14 14 Gårdejer Henrik Holm 1 0 0 1 1 1 1 0 0 1 1 14 14 Gårdejer Mads Vester Kjærgaard 0,5 0 0 1 0,5 1 0,5 0 0 1 0,5 3 1,5 Stenhugger Niels Ole Wensein 0,5 0 0 1 0,5 1 0,5 0 0 1 0,5 3 1,5 Elektromester Henning Pedersen 1 0 0 1 1 2 2 0 0 1 1 6 6 Konsulent Jens Henning Riis 0,5 0 0 0 0 2 1 0 0 1 0,5 11 5,5 Smedemester Jørgen Thing Nielsen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 10 3,333 Murermester Peder Kjeldgaard Madsen 0,3333 0 0 0 0 1 0,3333 0 0 1 0,3333 10 3,333
0,13 0,71 1,64 0,00 1,00 8,20
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Sparekassen Limfjorden 7,50 7,50 0,00 0,00 4,00 7,82 5,59 0,51 0,72
199
2.63 VORDINGBORG BANK
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Apoteker Ole Stjärnqvist 1 0 0 1 1 2 2 0 0 1 1 15 15 Advokat Jesper Popp 1 0 0 1 1 3 3 0 0 1 1 12 12 Ad. Junkt Morten Lynge Andersen 0,5 1 0,5 0 0 1 0,5 0 0 1 0,5 3 1,5 Forretningsfører Knud Rasmussen 0,1667 0 0 1 0,1667 2 0,3334 0 0 1 0,1667 1 0,1667 Farvehandler Jakob Mikkelsen 0,1667 0 0 0 0 5 0,8335 0 0 1 0,1667 1 0,1667 Frisørmester Kjeld Sørensen 0,8333 0 0 0 0 1 0,8333 0 0 1 0,8333 24 19,9992 IT Chef John Andersen 0,8333 0 0 1 0,8333 3 2,4999 0 0 1 0,8333 13 10,8329 Civiløkonom Christian Andersen 0,5 1 0,5 1 0,5 1 0,5 0 0 1 0,5 15 7,5
0,20 0,70 2,10 0,00 1,00 13,43
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep)
Vordingborg Bank A/S 5,00 5,00 0,00 0,00 10,00 10,50 8,40 0,95 1,19
200
2.64 LOKALBANKEN I NORDSJÆLLAND
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted Bankfuldmægtig Steen Brodersen 1 ER 0 0 0 0 1 1 0 0 0 0 10 10 Filialdirektør Dan Gösta-Larsen 1ER 0 0 0 0 1 1 0 0 0 0 10 10 Advokat Lone Mørch 0,5 0 0 1 0,5 2 1 1 0,5 1 0,5 3 1,5 Direktør Knud Nielsen 1 0 0 1 1 4 4 0 0 1 1 6 6 Konsulent Steen Thomsen 1 0 0 0 0 2 2 0 0 1 1 8 8 Tandlæge Erik Michael Uttenthal 1 0 0 0 0 2 2 0 0 1 1 7 7 Direktør Leif Kristensen 1 0 0 1 1 2 2 0 0 1 1 21 21 0,00 0,38 2,00 0,08 0,69 9,77
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Lokalbanken i Nordsjælland 6,50 4,50 0,00 0,00 * * * * *
201 2.65 BANK TRELLEBORG
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Investeringsrådgiver Steen Bohl 0,2ER 0 0 0 0 1 0,2 0 0 0 0 1 0,2 Advokat Thomas Christensen 0,2 0 0 1 0,2 40 8 0 0 1 0,2 1 0,2 Filialchef Hans Erik Milgaard Sonn 0,4ER 0 0 0 0 1 0,4 0 0 0 0 2 0,8 Direktør Ulrik Dahl 0,4 0 0 1 0,4 2 0,8 0 0 1 0,4 2 0,8 Gårdejer Jens Lundgård Nielsen 1 0 0 1 1 1 1 0 0 1 1 8 8 Erhvervskonsulent Vibeke Toft Müller 1 1 1 0 0 1 1 1 1 1 1 8 8 Fhv. handelsskoledirektør Flemming Robert Holm 1 1 1 1 1 1 1 0 0 1 115 15 Sikringsmontør Kim Thanning Olsen 1 0 0 0 0 1 1 0 0 1 1 10 10 Rådgiver Lars Erik Wilhardt 0,80ER 0 0 0 0 1 0,8 0 0 0 0 12 9,6 Butiksejer Poul Børge Jensen 0,80 0 0 1 0,8 2 1,6 0 0 1 0,8 17 13 ,6 Rådgiver Frank Humle Pedersen 0,60ER 0 0 0 0 1 0,6 0 0 0 0 4 2,4 Fabriksejer Preben Hald 0,60 0 0 0 0 1 0,6 0 0 1 0,6 15 9 Forretningsfører Steen Bach Nielsen 0,20 0 0 0 0 1 0,2 0 0 1 0,2 1 0,2 0,24 0,41 2,10 0,12 0,76 9,49
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) SparTrelleborg/BankTrelleborg 9,20 6,20 0,00 0,00 6,00 5,99 7,20 1,00 0,83
202 2.66 LØKKEN SPAREKASSE
Financial Board Multiple Title Name Weight Educatio Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Direktør Leo Christoffersen 1 0 0 0 0 5 50 0 1 11818 Kunderådgiver Birgitte Gaarden 0,33 ER 0 0 0 0 1 0,33 1 0,33 0 0 2 0,66 Administrationschef Kristian Larsen 0,33 ER 0 0 0 0 2 0,66 0 0 0 0 2 0,66 Forsikringsrådgiver Susanne Haastrup 0,5 ER 0 0 0 0 10,510,5 0 02 1 Fhv. gårdejer Poul Sørensen 1 00001100 1188 Fhv. borgmester Knud Rødbro 1 0 0 0 0 4 40 0 1 11414 Direktør Tom Hertel 0,5 0 0 1 0,5 3 1,5 0 0 1 0,5 3 1,5 Smedemester Arne Andreas Brogaard 0,83 0 0 1 0,83 2 1,66 0 0 1 0,83 5 4,15 Gårdejer Svend Drivsholm 0,5 0 0 1 0,5 1 0,5 0 0 1 0,5 16 8 Civiløkonom Finn Aagard 0,5 1 0,5 0 0 1 0,5 0 0 1 0,5 4 2 Kunderådgiver Gitte Irene Demant 1 ER 00001111 0066 Fhv. campingpladsejer Tommy Krogh Jensen 1 0 0 1 1 3 30 0 1 11212 0,06 0,33 2,31 0,22 0,75 8,95
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep) Løkken Sparekasse 7,50 6,33 0,00 0,00 18,00 6,36 8,46 2,83 2 ,13
203 2.67 BONUSBANKEN
Financial Board Multiple Title Name Weight Education Weighted Experience Weighted Directorship Weighted Gender Weighted Independence Weighted Tenure Weighted
Optiker Dion Møberg Eriksen 0,5 0 0 1 0,5 8 4 0 0 1 0,5 3 1,5 Direktør Jan Ole Rasmussen 1 00112200 1188 Konsulent Preben Hjort Petersen 1 00112200 1166 Prof. Dr. Jur Erik Werlauff 1 0 0 1 1 7 70 0 1 11313 Fru Sigrid Werlauff 1 0 0 1 1 3 31 1 1 12323 Direktør Peer Slipsager 0,5 0 0 1 0,5 9 4,5 0 0 1 0,5 3 1,5 Selvstændig Peter Sindet Pedersen 0,5 0 0 0 0 1 0,5 0 0 1 0,5 7 3,5 Regionsrådsmedlem Conny Marie Jensen 0,1667 0 0 1 0,1667 1 0,1667 1 0,1667 1 0,1667 8 1,3336 0 0,9117652 4,08821713 0,205887 1 10,2058694
Board Size Board Years Board Years CEO/Board CEO/Board Bank Board Size incl. Rep excl Rep Bonus Shares CEO Years (incl. Rep) (ex rep.) (incl rep) (excl rep)
Bonusbanken 5,67 5,67 1,00 0,00 9,00 10,21 10,21 0,88 0,88
204 3 COMPLETE LIST OF LOAN /D EPOSIT RATE FOR THE PERIOD 2003-2008
The Bank 2003 2004 2005 2006 2007 2008 Average Alm. Brand Bank A/S 95,8 99,1 128,2 149,5 157,0 156,2 131,0 Amagerbanken Aktieselskab 99,4 103,8 126,9 140,3 165,4 187,3 137,2 Arbejdernes Landsbank, Aktieselskab 75,5 74,9 78,9 89,9 92,2 92,8 84,0 bankTrelleborg a/s 106,6 111,4 117,4 135,9 166,5 127,6 Basisbank A/S 65,4 68,3 72,9 91,7 105,8 100,7 84,1 Bonusbanken A/S 42,5 56,9 94,9 106,8 111,1 82,4 Brørup Sparekasse 84,9 100,8 99,9 135,4 135,2 122,0 113,0 Danske Bank A/S 99,5 105,6 114,7 136,8 138,2 147,9 123,8 Den Jyske Sparekasse 94,9 101,1 120,2 122,6 122,2 128,6 114,9 DiBa Bank A/S 89,9 103,4 113,8 133,4 141,8 127,0 118,2 Djurslands Bank A/S 96,5 95,9 91,4 98,1 103,0 104,1 98,2 Dronninglund Sparekasse 103,6 103,3 101,4 117,6 123,2 122,8 112,0 EBH Bank A/S 107,6 112,1 139,4 155,4 183,5 151,2 141,5 EIK Bank Danmark A/S 316,4 374,4 616,9 653,5 108,3 98,9 361,4 Farsø, Sparekassen 112,6 104,8 100,8 125,8 122,1 121,5 114,6 Fionia Bank A/S 121,9 125,8 125,9 134,5 151,3 161,5 136,8 Forstædernes Bank A/S 120,8 129,2 143,3 143,5 151,7 163,1 141,9 Frøs Herreds Sparekasse 72,0 72,2 68,8 73,3 78,4 71,4 72,7 Grønlandsbanken, Aktieselskab 56,6 59,7 63,9 70,8 68,1 83,4 67,1 Himmerland A/S, Sparekassen 96,6 104,3 112,0 121,3 107,7 109,5 108,6 Hobro, Sparekassen 104,1 105,4 110,6 133,8 127,9 128,8 118,4 Jyske Bank A/S 82,4 90,4 96,2 103,7 107,4 102,9 97,2 Kreditbanken A/S 86,4 82,2 106,0 108,1 116,1 103,6 100,4 Kronjylland, Sparekassen 86,1 87,1 82,5 96,7 105,7 114,6 95,5 Lokalbanken i Nordsjælland a/s 83,9 83,3 84,8 99,9 119,2 116,2 97,9 Lolland A/S, Sparekassen 98,1 106,0 118,1 116,9 122,7 126,8 114,8 Lollands Bank, Aktieselskab 80,2 85,3 85,6 85,1 91,9 105,4 88,9 Løkken Sparebank A/S 70,2 62,2 66,0 109,1 130,7 118,5 92,8 Lån og Spar Bank A/S 53,3 52,7 53,8 63,7 91,6 90,0 67,5 Max Bank A/S 109,5 122,3 115,0 157,8 155,7 155,7 136,0 Merkur, Den Almennyttige Andelskasse 81,5 87,0 75,9 82,1 94,9 103,4 87,5 Middelfart Sparekasse 90,2 103,3 96,6 104,8 118,5 108,8 103,7 Morsø Bank, Aktieselskabet 87,0 108,8 109,1 130,6 115,4 108,5 109,9 Morsø Sparekasse A/S 86,3 100,7 112,0 120,7 129,9 131,2 113,5 Møns Bank, A/S 79,3 74,8 73,7 83,9 90,8 97,7 83,4 Nordea Bank Danmark A/S 97,5 92,1 105,0 113,8 112,2 118,8 106,6 Nordfyns Bank, Aktieselskabet 71,7 73,1 77,3 93,3 100,8 93,0 84,9 Nordjyske Bank A/S 72,4 76,5 87,5 104,8 114,6 116,5 95,4 Nr. Nebel og Omegn, Sparekassen for 75,7 75,0 74,0 80,8 95,1 99,5 83,4 Nykredit Bank A/S 157,8 118,4 118,7 141,7 137,6 160,8 139,2 Nørresundby Bank A/S 74,3 84,8 89,8 103,5 110,3 112,5 95,9 Ringkjøbing Landbobank, Aktieselskab 127,6 147,1 164,9 185,2 157,4 157,1 156,6 Roskilde Bank, Aktieselskab Roskilde Bank A/S 142,2 156,8 160,6 194,2 190,2 1337,8 363,6 Salling Bank A/S 80,4 79,6 81,7 92,1 98,8 92,2 87,5 Sammenslutningen Danske Andelskasser 83,3 86,7 92,0 102,5 99,7 100,2 94,1 Sjælland, Sparekassen 95,4 97,8 105,8 132,5 120,2 124,4 112,7 Skals, Sparekassen i 88,5 89,9 98,1 96,4 112,0 108,7 98,9 Skjern Bank, Aktieselskabet 102,2 100,0 109,8 165,5 149,5 126,8 125,6 Skælskør Bank Aktieselskab 80,0 89,8 105,4 112,7 129,5 129,7 107,9 Spar Nord Bank A/S 101,9 95,4 121,2 129,3 127,7 117,4 115,5 Spar Salling Sparekasse 60,2 65,6 70,3 85,8 93,9 88,9 77,5 Sparbank A/S 104,2 107,0 107,9 133,7 128,2 132,9 119,0 Sparekassen Faaborg A/S 100,1 112,9 130,3 138,2 136,5 143,7 127,0 Sparekassen Hvetbo A/S 72,1 100,7 103,0 125,0 143,5 131,7 112,7 Sparekassen Limfjorden 82,1 77,8 80,3 86,9 100,9 93,5 86,9 Sparekassen Spar Mors 94,5 90,6 96,2 117,8 142,0 108,2 Sparekassen Vendsyssel 114,2 114,2 109,0 128,8 147,8 122,8 122,8 Sparekassen Østjylland 96,9 94,5 100,9 106,4 126,7 99,9 104,2 Svendborg Sparekasse 76,6 93,5 93,7 92,0 94,1 90,4 90,1 Sydbank A/S 108,9 112,7 125,8 130,2 114,6 119,9 118,7 Thy, Sparekassen 89,7 78,0 92,8 112,5 115,2 105,7 99,0 Totalbanken A/S 83,9 94,9 106,6 101,1 116,6 121,7 104,1 Tønder Bank A/S 106,1 110,0 120,1 118,0 126,1 123,0 117,2 Vestfyns Bank A/S 78,0 83,0 88,5 103,2 101,2 89,3 90,5 Vordingborg Bank A/S 77,3 75,6 59,6 72,7 80,3 89,0 75,8 Østjydsk Bank A/S 111,6 116,7 126,5 149,4 165,0 160,3 138,3 Aarhus Lokalbank Aktieselskab 90,1 103,1 124,4 181,0 199,2 189,6 147,9 Average 94,6 99,3 109,6 124,8 123,0 119,4
205 4 INDEPENDENCE
Financial Board Multiple Bank Education Experience Directorships Gender Independence Tenure Size CEO CEO/Board
Møns Bank, A/S 0,000 0,533 2,733 0,400 1,000 8,800 5,00 21,0 2,251 Sammenslutningen Danske Andelskasser 0,115 0,885 4,154 0,000 1,000 7,673 8,66 7,0 0,986 Kreditbanken A/S 0,028 0,833 5,778 0,000 1,000 16,917 6,00 10,0 0,690 Sparekassen Limfjorden 0,133 0,711 1,644 0,000 1,000 8,200 7,50 4,0 0,512 Vordingborg Bank A/S 0,200 0,700 2,100 0,000 1,000 13,433 5,00 10,0 0,952 Brørup Sparekasse 0,000 0,400 1,800 0,000 1,000 12,400 5,00 23,0 1,944 Merkur, Den Almennyttige Andelskasse 0,190 0,190 4,500 0,190 0,857 8,833 7,00 16,0 2,847 Løkken Sparekasse 0,067 0,378 2,490 0,111 0,845 9,342 7,50 18,0 2,830 Nr. Nebel og Omegn, Sparekassen for 0,000 0,333 2,167 0,000 0,833 12,667 6,00 12,0 0,947 Tønder Bank A/S 0,091 0,727 3,015 0,182 0,818 12,167 5,00 16,0 1,194 Frøs Herreds Sparekasse 0,000 0,200 1,400 0,333 0,800 9,767 10,00 8,8 0,986 Spar Salling Sparekasse 0,107 0,375 1,321 0,214 0,786 7,464 9,33 6,0 0,892 Djurslands Bank A/S 0,308 0,923 7,000 0,231 0,769 12,692 6,50 8,0 0,679 Sparekassen Faaborg A/S 0,250 0,214 2,607 0,125 0,768 9,750 9,33 19,0 2,714 Thy, Sparekassen 0,033 0,574 3,623 0,131 0,754 8,345 10,17 15,0 2,830 Aarhus Lokalbank Aktieselskab 0,086 0,571 4,514 0,000 0,743 9,828 5,83 21,0 3,297 Amagerbanken Aktieselskab 0,000 0,649 17,324 0,162 0,730 9,243 6,16 23,0 3,226 Dronninglund Sparekasse 0,020 0,240 1,360 0,100 0,720 12,500 8,33 19,0 2,184 Skjern Bank, Aktieselskabet 0,158 0,605 8,921 0,079 0,711 7,579 6,33 10,0 1,876 Sparekassen Hvetbo A/S 0,021 0,354 3,187 0,146 0,708 6,792 8,00 7,0 1,282 Østjydsk Bank A/S 0,000 0,559 4,412 0,059 0,706 14,765 5,67 16,0 1,720 Morsø Bank, Aktieselskabet 0,020 0,471 2,431 0,176 0,706 11,784 8,50 7,0 1,001 Lån og Spar Bank A/S 0,171 0,400 5,157 0,386 0,700 7,257 11,67 19,0 4,715 Lokalbanken i Nordsjælland 0,000 0,385 2,000 0,077 0,692 9,769 6,50 0,0 0,000 Alm. Brand Bank A/S 0,368 0,526 4,632 0,000 0,684 12,474 6,33 20,0 2,024 Den Jyske Sparekasse 0,087 0,333 1,797 0,087 0,681 8,739 11,50 15,0 3,043 Grønlandsbanken, Aktieselskab 0,140 0,480 2,280 0,280 0,680 7,580 8,33 7,0 0,982 SparTrelleborg/BankTrelleborg 0,217 0,370 1,978 0,217 0,674 9,109 9,20 6,0 1,002 EBH Bank A/S 0,163 0,898 11,286 0,061 0,673 9,102 9,83 27,0 2,478 Skals, Sparekassen i 0,000 0,156 1,089 0,244 0,667 9,356 7,50 16,0 2,054 EIK Bank Danmark A/S 1,000 0,667 4,917 0,000 0,667 7,500 4,00 8,0 1,330 Hobro, Sparekassen 0,111 0,500 1,907 0,111 0,667 9,037 9,00 14,0 2,236 Totalbanken A/S 0,000 0,500 2,694 0,167 0,667 11,139 6,00 8,7 1,040 Himmerland A/S, Sparekassen 0,000 0,667 6,278 0,000 0,667 13,667 6,00 21,0 2,049 Nordfyns Bank, Aktieselskabet 0,000 0,750 2,361 0,167 0,667 11,694 6,00 4,0 0,410 Farsø, Sparekassen 0,000 0,294 2,608 0,137 0,667 8,745 8,50 10,0 1,748 Forstædernes Bank A/S 0,267 0,667 5,267 0,133 0,667 11,000 7,50 21,0 2,037 Skælskør Bank Aktieselskab 0,056 0,944 6,056 0,056 0,667 8,389 6,00 17,0 2,125 Basisbank A/S 0,667 1,000 53,083 0,000 0,667 5,000 6,00 3,0 0,698 Lolland A/S, Sparekassen 0,278 0,500 3,278 0,250 0,667 9,194 6,00 15,0 1,714 Middelfart Sparekasse 0,148 0,519 2,037 0,148 0,667 10,185 9,00 30,0 3,601 DiBa Bank A/S 0,333 0,667 4,611 0,111 0,667 12,222 9,00 11,0 1,000 Max Bank A/S 0,222 0,593 3,296 0,111 0,667 14,148 9,00 5,0 0,432 Morsø Sparekasse A/S 0,407 0,907 3,037 0,037 0,667 12,222 9,00 11,0 1,100 Lollands Bank, Aktieselskab 0,000 0,667 3,861 0,000 0,667 13,694 6,00 10,0 0,860 Kronjylland, Sparekassen 0,000 0,444 1,907 0,167 0,667 9,296 9,00 22,0 4,322 Jyske Bank 0,148 0,574 5,389 0,111 0,667 8,463 9,00 14,0 2,569 Salling Bank A/S 0,028 0,667 3,278 0,139 0,667 9,417 6,00 14,0 1,618 Roskilde Bank, Aktieselskab 0,225 0,663 8,584 0,169 0,663 8,067 5,93 21,0 3,512 Arbejdernes Landsbank, Aktieselskab 0,032 0,758 10,548 0,290 0,661 10,484 10,33 7,0 0,970 Sydbank 0,086 0,700 6,814 0,214 0,657 9,257 11,67 19,0 2,992 Sparekassen Vendsyssel 0,012 0,543 3,259 0,210 0,654 7,123 13,50 11,0 2,517 Svendborg Sparekasse 0,000 0,471 7,824 0,000 0,647 9,471 5,67 7,8 1,155 Ringkjøbing Landbobank, Aktieselskab 0,000 0,444 3,800 0,089 0,644 6,556 7,50 10,0 2,033 Nordjyske Bank A/S 0,000 0,661 9,441 0,254 0,644 7,949 9,83 22,0 4,499 Sparekassen Østjylland 0,213 0,255 1,340 0,085 0,638 8,362 7,83 8,0 1,588 Sjælland, Sparekassen 0,000 0,481 3,204 0,111 0,630 11,778 9,00 31,0 4,385 Fionia Bank A/S 0,333 0,611 4,852 0,167 0,611 9,167 9,00 13,0 1,568 Spar Nord Bank 0,296 0,611 6,667 0,093 0,593 8,111 9,00 14,0 2,875 Danske Bank 0,470 0,694 4,389 0,357 0,582 10,482 16,50 22,0 2,677 Vestfyns Bank A/S 0,000 0,682 3,659 0,136 0,545 8,704 7,33 8,0 0,960 Vestjysk Bank A/S 0,128 0,553 2,128 0,128 0,532 6,702 7,83 7,0 1,867 Sparbank A/S 0,000 0,511 5,511 0,255 0,532 10,745 7,83 12,0 1,997 Nørresundby Bank A/S 0,361 0,528 2,722 0,167 0,500 10,278 6,00 11,0 1,618 Nordea 0,875 0,781 3,687 0,000 0,000 7,062 5,33 17,0 3,617 Nykredit 0,697 0,636 8,333 0,000 0,000 7,485 5,50 9,0 1,751
206 5 BOARD EXPERIENCE
Financial Board Multiple Bank Education Experience Directorships Gender Independence Tenure Size CEO CEO/Board Basisbank A/S 0,667 1,000 53,083 0,000 0,667 5,000 6,00 3,0 0,698 Skælskør Bank Aktieselskab 0,056 0,944 6,056 0,056 0,667 8,389 6,00 17,0 2,125 Djurslands Bank A/S 0,308 0,923 7,000 0,231 0,769 12,692 6,50 8,0 0,679 Bonusbanken 0,000 0,912 4,088 0,206 1,000 10,206 5,670 9,000 0,882 Morsø Sparekasse A/S 0,407 0,907 3,037 0,037 0,667 12,222 9,00 11,0 1,100 EBH Bank A/S 0,163 0,898 11,286 0,061 0,673 9,102 9,83 27,0 2,478 Sammenslutningen Danske Andelskasser 0,115 0,885 4,154 0,000 1,000 7,673 8,66 7,0 0,986 Kreditbanken A/S 0,028 0,833 5,778 0,000 1,000 16,917 6,00 10,0 0,690 Nordea 0,875 0,781 3,687 0,000 0,000 7,062 5,33 17,0 3,617 Arbejdernes Landsbank, Aktieselskab 0,032 0,758 10,548 0,290 0,661 10,484 10,33 7,0 0,970 Nordfyns Bank, Aktieselskabet 0,000 0,750 2,361 0,167 0,667 11,694 6,00 4,0 0,410 Tønder Bank A/S 0,091 0,727 3,015 0,182 0,818 12,167 5,00 16,0 1,194 Sparekassen Limfjorden 0,133 0,711 1,644 0,000 1,000 8,200 7,50 4,0 0,512 Vordingborg Bank A/S 0,200 0,700 2,100 0,000 1,000 13,433 5,00 10,0 0,952 Sydbank 0,086 0,700 6,814 0,214 0,657 9,257 11,67 19,0 2,992 Danske Bank 0,470 0,694 4,389 0,357 0,582 10,482 16,50 22,0 2,677 Vestfyns Bank A/S 0,000 0,682 3,659 0,136 0,545 8,704 7,33 8,0 0,960 EIK Bank Danmark A/S 1,000 0,667 4,917 0,000 0,667 7,500 4,00 8,0 1,330 Himmerland A/S, Sparekassen 0,000 0,667 6,278 0,000 0,667 13,667 6,00 21,0 2,049 Forstædernes Bank A/S 0,267 0,667 5,267 0,133 0,667 11,000 7,50 21,0 2,037 DiBa Bank A/S 0,333 0,667 4,611 0,111 0,667 12,222 9,00 11,0 1,000 Lollands Bank, Aktieselskab 0,000 0,667 3,861 0,000 0,667 13,694 6,00 10,0 0,860 Salling Bank A/S 0,028 0,667 3,278 0,139 0,667 9,417 6,00 14,0 1,618 Roskilde Bank, Aktieselskab 0,225 0,663 8,584 0,169 0,663 8,067 5,93 21,0 3,512 Nordjyske Bank A/S 0,000 0,661 9,441 0,254 0,644 7,949 9,83 22,0 4,499 Amagerbanken Aktieselskab 0,000 0,649 17,324 0,162 0,730 9,243 6,16 23,0 3,226 Nykredit 0,697 0,636 8,333 0,000 0,000 7,485 5,50 9,0 1,751 Fionia Bank A/S 0,333 0,611 4,852 0,167 0,611 9,167 9,00 13,0 1,568 Spar Nord Bank 0,296 0,611 6,667 0,093 0,593 8,111 9,00 14,0 2,875 Skjern Bank, Aktieselskabet 0,158 0,605 8,921 0,079 0,711 7,579 6,33 10,0 1,876 Max Bank A/S 0,222 0,593 3,296 0,111 0,667 14,148 9,00 5,0 0,432 Jyske Bank 0,148 0,574 5,389 0,111 0,667 8,463 9,00 14,0 2,569 Thy, Sparekassen 0,033 0,574 3,623 0,131 0,754 8,345 10,17 15,0 2,830 Aarhus Lokalbank Aktieselskab 0,086 0,571 4,514 0,000 0,743 9,828 5,83 21,0 3,297 Østjydsk Bank A/S 0,000 0,559 4,412 0,059 0,706 14,765 5,67 16,0 1,720 Vestjysk Bank A/S 0,128 0,553 2,128 0,128 0,532 6,702 7,83 7,0 1,867 Sparekassen Vendsyssel 0,012 0,543 3,259 0,210 0,654 7,123 13,50 11,0 2,517 Møns Bank, A/S 0,000 0,533 2,733 0,400 1,000 8,800 5,00 21,0 2,251 Nørresundby Bank A/S 0,361 0,528 2,722 0,167 0,500 10,278 6,00 11,0 1,618 Alm. Brand Bank A/S 0,368 0,526 4,632 0,000 0,684 12,474 6,33 20,0 2,024 Middelfart Sparekasse 0,148 0,519 2,037 0,148 0,667 10,185 9,00 30,0 3,601 Sparbank A/S 0,000 0,511 5,511 0,255 0,532 10,745 7,83 12,0 1,997 Hobro, Sparekassen 0,111 0,500 1,907 0,111 0,667 9,037 9,00 14,0 2,236 Lolland A/S, Sparekassen 0,278 0,500 3,278 0,250 0,667 9,194 6,00 15,0 1,714 Totalbanken A/S 0,000 0,500 2,694 0,167 0,667 11,139 6,00 8,7 1,040 Sjælland, Sparekassen 0,000 0,481 3,204 0,111 0,630 11,778 9,00 31,0 4,385 Grønlandsbanken, Aktieselskab 0,140 0,480 2,280 0,280 0,680 7,580 8,33 7,0 0,982 Svendborg Sparekasse 0,000 0,471 7,824 0,000 0,647 9,471 5,67 7,8 1,155 Morsø Bank, Aktieselskabet 0,020 0,471 2,431 0,176 0,706 11,784 8,50 7,0 1,001 Kronjylland, Sparekassen 0,000 0,444 1,907 0,167 0,667 9,296 9,00 22,0 4,322 Ringkjøbing Landbobank, Aktieselskab 0,000 0,444 3,800 0,089 0,644 6,556 7,50 10,0 2,033 Lån og Spar Bank A/S 0,171 0,400 5,157 0,386 0,700 7,257 11,67 19,0 4,715 Brørup Sparekasse 0,000 0,400 1,800 0,000 1,000 12,400 5,00 23,0 1,944 Lokalbanken i Nordsjælland 0,000 0,385 2,000 0,077 0,692 9,769 6,50 Løkken Sparekasse 0,067 0,378 2,490 0,111 0,845 9,342 7,50 18,0 2,830 Spar Salling Sparekasse 0,107 0,375 1,321 0,214 0,786 7,464 9,33 6,0 0,892 SparTrelleborg/BankTrelleborg 0,217 0,370 1,978 0,217 0,674 9,109 9,20 6,0 1,002 Sparekassen Hvetbo A/S 0,021 0,354 3,187 0,146 0,708 6,792 8,00 7,0 1,282 Nr. Nebel og Omegn, Sparekassen for 0,000 0,333 2,167 0,000 0,833 12,667 6,00 12,0 0,947 Den Jyske Sparekasse 0,087 0,333 1,797 0,087 0,681 8,739 11,50 15,0 3,043 Farsø, Sparekassen 0,000 0,294 2,608 0,137 0,667 8,745 8,50 10,0 1,748 Sparekassen Østjylland 0,213 0,255 1,340 0,085 0,638 8,362 7,83 8,0 1,588 Dronninglund Sparekasse 0,020 0,240 1,360 0,100 0,720 12,500 8,33 19,0 2,184 Sparekassen Faaborg A/S 0,250 0,214 2,607 0,125 0,768 9,750 9,33 19,0 2,714 Frøs Herreds Sparekasse 0,000 0,200 1,400 0,333 0,800 9,767 10,00 8,8 0,986 Merkur, Den Almennyttige Andelskasse 0,190 0,190 4,500 0,190 0,857 8,833 7,00 16,0 2,847 Skals, Sparekassen i 0,000 0,156 1,089 0,244 0,667 9,356 7,50 16,0 2,054
207 6 GENDER / BOARD DIVERSITY
Financial Board Multiple Bank Education Experience Directorships Gender Independence Tenure Size CEO CEO/Board Møns Bank, A/S 0,000 0,533 2,733 0,400 1,000 8,800 5,00 21,0 2,251 Lån og Spar Bank A/S 0,171 0,400 5,157 0,386 0,700 7,257 11,67 19,0 4,715 Danske Bank 0,470 0,694 4,389 0,357 0,582 10,482 16,50 22,0 2,677 Frøs Herreds Sparekasse 0,000 0,200 1,400 0,333 0,800 9,767 10,00 8,8 0,986 Arbejdernes Landsbank, Aktieselskab 0,032 0,758 10,548 0,290 0,661 10,484 10,33 7,0 0,970 Grønlandsbanken, Aktieselskab 0,140 0,480 2,280 0,280 0,680 7,580 8,33 7,0 0,982 Sparbank A/S 0,000 0,511 5,511 0,255 0,532 10,745 7,83 12,0 1,997 Nordjyske Bank A/S 0,000 0,661 9,441 0,254 0,644 7,949 9,83 22,0 4,499 Lolland A/S, Sparekassen 0,278 0,500 3,278 0,250 0,667 9,194 6,00 15,0 1,714 Skals, Sparekassen i 0,000 0,156 1,089 0,244 0,667 9,356 7,50 16,0 2,054 Djurslands Bank A/S 0,308 0,923 7,000 0,231 0,769 12,692 6,50 8,0 0,679 SparTrelleborg/BankTrelleborg 0,217 0,370 1,978 0,217 0,674 9,109 9,20 6,0 1,002 Sydbank 0,086 0,700 6,814 0,214 0,657 9,257 11,67 19,0 2,992 Spar Salling Sparekasse 0,107 0,375 1,321 0,214 0,786 7,464 9,33 6,0 0,892 Sparekassen Vendsyssel 0,012 0,543 3,259 0,210 0,654 7,123 13,50 11,0 2,517 Bonusbanken 0,000 0,912 4,088 0,206 1,000 10,206 5,670 9,000 0,882 Merkur, Den Almennyttige Andelskasse 0,190 0,190 4,500 0,190 0,857 8,833 7,00 16,0 2,847 Tønder Bank A/S 0,091 0,727 3,015 0,182 0,818 12,167 5,00 16,0 1,194 Morsø Bank, Aktieselskabet 0,020 0,471 2,431 0,176 0,706 11,784 8,50 7,0 1,001 Roskilde Bank, Aktieselskab 0,225 0,663 8,584 0,169 0,663 8,067 5,93 21,0 3,512 Nørresundby Bank A/S 0,361 0,528 2,722 0,167 0,500 10,278 6,00 11,0 1,618 Totalbanken A/S 0,000 0,500 2,694 0,167 0,667 11,139 6,00 8,7 1,040 Nordfyns Bank, Aktieselskabet 0,000 0,750 2,361 0,167 0,667 11,694 6,00 4,0 0,410 Fionia Bank A/S 0,333 0,611 4,852 0,167 0,611 9,167 9,00 13,0 1,568 Kronjylland, Sparekassen 0,000 0,444 1,907 0,167 0,667 9,296 9,00 22,0 4,322 Amagerbanken Aktieselskab 0,000 0,649 17,324 0,162 0,730 9,243 6,16 23,0 3,226 Middelfart Sparekasse 0,148 0,519 2,037 0,148 0,667 10,185 9,00 30,0 3,601 Sparekassen Hvetbo A/S 0,021 0,354 3,187 0,146 0,708 6,792 8,00 7,0 1,282 Salling Bank A/S 0,028 0,667 3,278 0,139 0,667 9,417 6,00 14,0 1,618 Farsø, Sparekassen 0,000 0,294 2,608 0,137 0,667 8,745 8,50 10,0 1,748 Vestfyns Bank A/S 0,000 0,682 3,659 0,136 0,545 8,704 7,33 8,0 0,960 Forstædernes Bank A/S 0,267 0,667 5,267 0,133 0,667 11,000 7,50 21,0 2,037 Thy, Sparekassen 0,033 0,574 3,623 0,131 0,754 8,345 10,17 15,0 2,830 Vestjysk Bank A/S 0,128 0,553 2,128 0,128 0,532 6,702 7,83 7,0 1,867 Sparekassen Faaborg A/S 0,250 0,214 2,607 0,125 0,768 9,750 9,33 19,0 2,714 Jyske Bank 0,148 0,574 5,389 0,111 0,667 8,463 9,00 14,0 2,569 DiBa Bank A/S 0,333 0,667 4,611 0,111 0,667 12,222 9,00 11,0 1,000 Max Bank A/S 0,222 0,593 3,296 0,111 0,667 14,148 9,00 5,0 0,432 Sjælland, Sparekassen 0,000 0,481 3,204 0,111 0,630 11,778 9,00 31,0 4,385 Hobro, Sparekassen 0,111 0,500 1,907 0,111 0,667 9,037 9,00 14,0 2,236 Løkken Sparekasse 0,067 0,378 2,490 0,111 0,845 9,342 7,50 18,0 2,830 Dronninglund Sparekasse 0,020 0,240 1,360 0,100 0,720 12,500 8,33 19,0 2,184 Spar Nord Bank 0,296 0,611 6,667 0,093 0,593 8,111 9,00 14,0 2,875 Ringkjøbing Landbobank, Aktieselskab 0,000 0,444 3,800 0,089 0,644 6,556 7,50 10,0 2,033 Den Jyske Sparekasse 0,087 0,333 1,797 0,087 0,681 8,739 11,50 15,0 3,043 Sparekassen Østjylland 0,213 0,255 1,340 0,085 0,638 8,362 7,83 8,0 1,588 Skjern Bank, Aktieselskabet 0,158 0,605 8,921 0,079 0,711 7,579 6,33 10,0 1,876 Lokalbanken i Nordsjælland 0,000 0,385 2,000 0,077 0,692 9,769 6,50 EBH Bank A/S 0,163 0,898 11,286 0,061 0,673 9,102 9,83 27,0 2,478 Østjydsk Bank A/S 0,000 0,559 4,412 0,059 0,706 14,765 5,67 16,0 1,720 Skælskør Bank Aktieselskab 0,056 0,944 6,056 0,056 0,667 8,389 6,00 17,0 2,125 Morsø Sparekasse A/S 0,407 0,907 3,037 0,037 0,667 12,222 9,00 11,0 1,100 Basisbank A/S 0,667 1,000 53,083 0,000 0,667 5,000 6,00 3,0 0,698 Sammenslutningen Danske Andelskasser 0,115 0,885 4,154 0,000 1,000 7,673 8,66 7,0 0,986 Kreditbanken A/S 0,028 0,833 5,778 0,000 1,000 16,917 6,00 10,0 0,690 Nordea 0,875 0,781 3,687 0,000 0,000 7,062 5,33 17,0 3,617 Sparekassen Limfjorden 0,133 0,711 1,644 0,000 1,000 8,200 7,50 4,0 0,512 Vordingborg Bank A/S 0,200 0,700 2,100 0,000 1,000 13,433 5,00 10,0 0,952 EIK Bank Danmark A/S 1,000 0,667 4,917 0,000 0,667 7,500 4,00 8,0 1,330 Himmerland A/S, Sparekassen 0,000 0,667 6,278 0,000 0,667 13,667 6,00 21,0 2,049 Lollands Bank, Aktieselskab 0,000 0,667 3,861 0,000 0,667 13,694 6,00 10,0 0,860 Nykredit 0,697 0,636 8,333 0,000 0,000 7,485 5,50 9,0 1,751 Aarhus Lokalbank Aktieselskab 0,086 0,571 4,514 0,000 0,743 9,828 5,83 21,0 3,297 Alm. Brand Bank A/S 0,368 0,526 4,632 0,000 0,684 12,474 6,33 20,0 2,024 Svendborg Sparekasse 0,000 0,471 7,824 0,000 0,647 9,471 5,67 7,8 1,155 Brørup Sparekasse 0,000 0,400 1,800 0,000 1,000 12,400 5,00 23,0 1,944 Nr. Nebel og Omegn, Sparekassen for 0,000 0,333 2,167 0,000 0,833 12,667 6,00 12,0 0,947
208 7 MULTIPLE DIRECTORSHIPS
Financial Board Multiple Bank Education Experience Directorships Gender Independence Tenure Size CEO CEO/Board Basisbank A/S 0,667 1,000 53,083 0,000 0,667 5,000 6,00 3,0 0,698 Amagerbanken Aktieselskab 0,000 0,649 17,324 0,162 0,730 9,243 6,16 23,0 3,226 EBH Bank A/S 0,163 0,898 11,286 0,061 0,673 9,102 9,83 27,0 2,478 Arbejdernes Landsbank, Aktieselskab 0,032 0,758 10,548 0,290 0,661 10,484 10,33 7,0 0,970 Nordjyske Bank A/S 0,000 0,661 9,441 0,254 0,644 7,949 9,83 22,0 4,499 Skjern Bank, Aktieselskabet 0,158 0,605 8,921 0,079 0,711 7,579 6,33 10,0 1,876 Roskilde Bank, Aktieselskab 0,225 0,663 8,584 0,169 0,663 8,067 5,93 21,0 3,512 Nykredit 0,697 0,636 8,333 0,000 0,000 7,485 5,50 9,0 1,751 Svendborg Sparekasse 0,000 0,471 7,824 0,000 0,647 9,471 5,67 7,8 1,155 Djurslands Bank A/S 0,308 0,923 7,000 0,231 0,769 12,692 6,50 8,0 0,679 Sydbank 0,086 0,700 6,814 0,214 0,657 9,257 11,67 19,0 2,992 Spar Nord Bank 0,296 0,611 6,667 0,093 0,593 8,111 9,00 14,0 2,875 Himmerland A/S, Sparekassen 0,000 0,667 6,278 0,000 0,667 13,667 6,00 21,0 2,049 Skælskør Bank Aktieselskab 0,056 0,944 6,056 0,056 0,667 8,389 6,00 17,0 2,125 Kreditbanken A/S 0,028 0,833 5,778 0,000 1,000 16,917 6,00 10,0 0,690 Sparbank A/S 0,000 0,511 5,511 0,255 0,532 10,745 7,83 12,0 1,997 Jyske Bank 0,148 0,574 5,389 0,111 0,667 8,463 9,00 14,0 2,569 Forstædernes Bank A/S 0,267 0,667 5,267 0,133 0,667 11,000 7,50 21,0 2,037 Lån og Spar Bank A/S 0,171 0,400 5,157 0,386 0,700 7,257 11,67 19,0 4,715 EIK Bank Danmark A/S 1,000 0,667 4,917 0,000 0,667 7,500 4,00 8,0 1,330 Fionia Bank A/S 0,333 0,611 4,852 0,167 0,611 9,167 9,00 13,0 1,568 Alm. Brand Bank A/S 0,368 0,526 4,632 0,000 0,684 12,474 6,33 20,0 2,024 DiBa Bank A/S 0,333 0,667 4,611 0,111 0,667 12,222 9,00 11,0 1,000 Aarhus Lokalbank Aktieselskab 0,086 0,571 4,514 0,000 0,743 9,828 5,83 21,0 3,297 Merkur, Den Almennyttige Andelskasse 0,190 0,190 4,500 0,190 0,857 8,833 7,00 16,0 2,847 Østjydsk Bank A/S 0,000 0,559 4,412 0,059 0,706 14,765 5,67 16,0 1,720 Danske Bank 0,470 0,694 4,389 0,357 0,582 10,482 16,50 22,0 2,677 Sammenslutningen Danske Andelskasser 0,115 0,885 4,154 0,000 1,000 7,673 8,66 7,0 0,986 Bonusbanken 0,000 0,912 4,088 0,206 1,000 10,206 5,670 9,000 0,882 Lollands Bank, Aktieselskab 0,000 0,667 3,861 0,000 0,667 13,694 6,00 10,0 0,860 Ringkjøbing Landbobank, Aktieselskab 0,000 0,444 3,800 0,089 0,644 6,556 7,50 10,0 2,033 Nordea 0,875 0,781 3,687 0,000 0,000 7,062 5,33 17,0 3,617 Vestfyns Bank A/S 0,000 0,682 3,659 0,136 0,545 8,704 7,33 8,0 0,960 Thy, Sparekassen 0,033 0,574 3,623 0,131 0,754 8,345 10,17 15,0 2,830 Max Bank A/S 0,222 0,593 3,296 0,111 0,667 14,148 9,00 5,0 0,432 Lolland A/S, Sparekassen 0,278 0,500 3,278 0,250 0,667 9,194 6,00 15,0 1,714 Salling Bank A/S 0,028 0,667 3,278 0,139 0,667 9,417 6,00 14,0 1,618 Sparekassen Vendsyssel 0,012 0,543 3,259 0,210 0,654 7,123 13,50 11,0 2,517 Sjælland, Sparekassen 0,000 0,481 3,204 0,111 0,630 11,778 9,00 31,0 4,385 Sparekassen Hvetbo A/S 0,021 0,354 3,187 0,146 0,708 6,792 8,00 7,0 1,282 Morsø Sparekasse A/S 0,407 0,907 3,037 0,037 0,667 12,222 9,00 11,0 1,100 Tønder Bank A/S 0,091 0,727 3,015 0,182 0,818 12,167 5,00 16,0 1,194 Møns Bank, A/S 0,000 0,533 2,733 0,400 1,000 8,800 5,00 21,0 2,251 Nørresundby Bank A/S 0,361 0,528 2,722 0,167 0,500 10,278 6,00 11,0 1,618 Totalbanken A/S 0,000 0,500 2,694 0,167 0,667 11,139 6,00 8,7 1,040 Farsø, Sparekassen 0,000 0,294 2,608 0,137 0,667 8,745 8,50 10,0 1,748 Sparekassen Faaborg A/S 0,250 0,214 2,607 0,125 0,768 9,750 9,33 19,0 2,714 Løkken Sparekasse 0,067 0,378 2,490 0,111 0,845 9,342 7,50 18,0 2,830 Morsø Bank, Aktieselskabet 0,020 0,471 2,431 0,176 0,706 11,784 8,50 7,0 1,001 Nordfyns Bank, Aktieselskabet 0,000 0,750 2,361 0,167 0,667 11,694 6,00 4,0 0,410 Grønlandsbanken, Aktieselskab 0,140 0,480 2,280 0,280 0,680 7,580 8,33 7,0 0,982 Nr. Nebel og Omegn, Sparekassen for 0,000 0,333 2,167 0,000 0,833 12,667 6,00 12,0 0,947 Vestjysk Bank A/S 0,128 0,553 2,128 0,128 0,532 6,702 7,83 7,0 1,867 Vordingborg Bank A/S 0,200 0,700 2,100 0,000 1,000 13,433 5,00 10,0 0,952 Middelfart Sparekasse 0,148 0,519 2,037 0,148 0,667 10,185 9,00 30,0 3,601 Lokalbanken i Nordsjælland 0,000 0,385 2,000 0,077 0,692 9,769 6,50 SparTrelleborg/BankTrelleborg 0,217 0,370 1,978 0,217 0,674 9,109 9,20 6,0 1,002 Kronjylland, Sparekassen 0,000 0,444 1,907 0,167 0,667 9,296 9,00 22,0 4,322 Hobro, Sparekassen 0,111 0,500 1,907 0,111 0,667 9,037 9,00 14,0 2,236 Brørup Sparekasse 0,000 0,400 1,800 0,000 1,000 12,400 5,00 23,0 1,944 Den Jyske Sparekasse 0,087 0,333 1,797 0,087 0,681 8,739 11,50 15,0 3,043 Sparekassen Limfjorden 0,133 0,711 1,644 0,000 1,000 8,200 7,50 4,0 0,512 Frøs Herreds Sparekasse 0,000 0,200 1,400 0,333 0,800 9,767 10,00 8,8 0,986 Dronninglund Sparekasse 0,020 0,240 1,360 0,100 0,720 12,500 8,33 19,0 2,184 Sparekassen Østjylland 0,213 0,255 1,340 0,085 0,638 8,362 7,83 8,0 1,588 Spar Salling Sparekasse 0,107 0,375 1,321 0,214 0,786 7,464 9,33 6,0 0,892 Skals, Sparekassen i 0,000 0,156 1,089 0,244 0,667 9,356 7,50 16,0 2,054
209 8 TENURE
Financial Board Multiple Bank Education Experience Directorships Gender Independence Tenure Size CEO CEO/Board Kreditbanken A/S 0,028 0,833 5,778 0,000 1,000 16,917 6,00 10,0 0,690 Østjydsk Bank A/S 0,000 0,559 4,412 0,059 0,706 14,765 5,67 16,0 1,720 Max Bank A/S 0,222 0,593 3,296 0,111 0,667 14,148 9,00 5,0 0,432 Lollands Bank, Aktieselskab 0,000 0,667 3,861 0,000 0,667 13,694 6,00 10,0 0,860 Himmerland A/S, Sparekassen 0,000 0,667 6,278 0,000 0,667 13,667 6,00 21,0 2,049 Vordingborg Bank A/S 0,200 0,700 2,100 0,000 1,000 13,433 5,00 10,0 0,952 Djurslands Bank A/S 0,308 0,923 7,000 0,231 0,769 12,692 6,50 8,0 0,679 Nr. Nebel og Omegn, Sparekassen for 0,000 0,333 2,167 0,000 0,833 12,667 6,00 12,0 0,947 Dronninglund Sparekasse 0,020 0,240 1,360 0,100 0,720 12,500 8,33 19,0 2,184 Alm. Brand Bank A/S 0,368 0,526 4,632 0,000 0,684 12,474 6,33 20,0 2,024 Brørup Sparekasse 0,000 0,400 1,800 0,000 1,000 12,400 5,00 23,0 1,944 Morsø Sparekasse A/S 0,407 0,907 3,037 0,037 0,667 12,222 9,00 11,0 1,100 DiBa Bank A/S 0,333 0,667 4,611 0,111 0,667 12,222 9,00 11,0 1,000 Tønder Bank A/S 0,091 0,727 3,015 0,182 0,818 12,167 5,00 16,0 1,194 Morsø Bank, Aktieselskabet 0,020 0,471 2,431 0,176 0,706 11,784 8,50 7,0 1,001 Sjælland, Sparekassen 0,000 0,481 3,204 0,111 0,630 11,778 9,00 31,0 4,385 Nordfyns Bank, Aktieselskabet 0,000 0,750 2,361 0,167 0,667 11,694 6,00 4,0 0,410 Totalbanken A/S 0,000 0,500 2,694 0,167 0,667 11,139 6,00 8,7 1,040 Forstædernes Bank A/S 0,267 0,667 5,267 0,133 0,667 11,000 7,50 21,0 2,037 Sparbank A/S 0,000 0,511 5,511 0,255 0,532 10,745 7,83 12,0 1,997 Arbejdernes Landsbank, Aktieselskab 0,032 0,758 10,548 0,290 0,661 10,484 10,33 7,0 0,970 Danske Bank 0,470 0,694 4,389 0,357 0,582 10,482 16,50 22,0 2,677 Nørresundby Bank A/S 0,361 0,528 2,722 0,167 0,500 10,278 6,00 11,0 1,618 Bonusbanken 0,000 0,912 4,088 0,206 1,000 10,206 5,670 9,000 0,882 Middelfart Sparekasse 0,148 0,519 2,037 0,148 0,667 10,185 9,00 30,0 3,601 Aarhus Lokalbank Aktieselskab 0,086 0,571 4,514 0,000 0,743 9,828 5,83 21,0 3,297 Lokalbanken i Nordsjælland 0,000 0,385 2,000 0,077 0,692 9,769 6,50 Frøs Herreds Sparekasse 0,000 0,200 1,400 0,333 0,800 9,767 10,00 8,8 0,986 Sparekassen Faaborg A/S 0,250 0,214 2,607 0,125 0,768 9,750 9,33 19,0 2,714 Svendborg Sparekasse 0,000 0,471 7,824 0,000 0,647 9,471 5,67 7,8 1,155 Salling Bank A/S 0,028 0,667 3,278 0,139 0,667 9,417 6,00 14,0 1,618 Skals, Sparekassen i 0,000 0,156 1,089 0,244 0,667 9,356 7,50 16,0 2,054 Løkken Sparekasse 0,067 0,378 2,490 0,111 0,845 9,342 7,50 18,0 2,830 Kronjylland, Sparekassen 0,000 0,444 1,907 0,167 0,667 9,296 9,00 22,0 4,322 Sydbank 0,086 0,700 6,814 0,214 0,657 9,257 11,67 19,0 2,992 Amagerbanken Aktieselskab 0,000 0,649 17,324 0,162 0,730 9,243 6,16 23,0 3,226 Lolland A/S, Sparekassen 0,278 0,500 3,278 0,250 0,667 9,194 6,00 15,0 1,714 Fionia Bank A/S 0,333 0,611 4,852 0,167 0,611 9,167 9,00 13,0 1,568 SparTrelleborg/BankTrelleborg 0,217 0,370 1,978 0,217 0,674 9,109 9,20 6,0 1,002 EBH Bank A/S 0,163 0,898 11,286 0,061 0,673 9,102 9,83 27,0 2,478 Hobro, Sparekassen 0,111 0,500 1,907 0,111 0,667 9,037 9,00 14,0 2,236 Merkur, Den Almennyttige Andelskasse 0,190 0,190 4,500 0,190 0,857 8,833 7,00 16,0 2,847 Møns Bank, A/S 0,000 0,533 2,733 0,400 1,000 8,800 5,00 21,0 2,251 Farsø, Sparekassen 0,000 0,294 2,608 0,137 0,667 8,745 8,50 10,0 1,748 Den Jyske Sparekasse 0,087 0,333 1,797 0,087 0,681 8,739 11,50 15,0 3,043 Vestfyns Bank A/S 0,000 0,682 3,659 0,136 0,545 8,704 7,33 8,0 0,960 Jyske Bank 0,148 0,574 5,389 0,111 0,667 8,463 9,00 14,0 2,569 Skælskør Bank Aktieselskab 0,056 0,944 6,056 0,056 0,667 8,389 6,00 17,0 2,125 Sparekassen Østjylland 0,213 0,255 1,340 0,085 0,638 8,362 7,83 8,0 1,588 Thy, Sparekassen 0,033 0,574 3,623 0,131 0,754 8,345 10,17 15,0 2,830 Sparekassen Limfjorden 0,133 0,711 1,644 0,000 1,000 8,200 7,50 4,0 0,512 Spar Nord Bank 0,296 0,611 6,667 0,093 0,593 8,111 9,00 14,0 2,875 Roskilde Bank, Aktieselskab 0,225 0,663 8,584 0,169 0,663 8,067 5,93 21,0 3,512 Nordjyske Bank A/S 0,000 0,661 9,441 0,254 0,644 7,949 9,83 22,0 4,499 Sammenslutningen Danske Andelskasser 0,115 0,885 4,154 0,000 1,000 7,673 8,66 7,0 0,986 Grønlandsbanken, Aktieselskab 0,140 0,480 2,280 0,280 0,680 7,580 8,33 7,0 0,982 Skjern Bank, Aktieselskabet 0,158 0,605 8,921 0,079 0,711 7,579 6,33 10,0 1,876 EIK Bank Danmark A/S 1,000 0,667 4,917 0,000 0,667 7,500 4,00 8,0 1,330 Nykredit 0,697 0,636 8,333 0,000 0,000 7,485 5,50 9,0 1,751 Spar Salling Sparekasse 0,107 0,375 1,321 0,214 0,786 7,464 9,33 6,0 0,892 Lån og Spar Bank A/S 0,171 0,400 5,157 0,386 0,700 7,257 11,67 19,0 4,715 Sparekassen Vendsyssel 0,012 0,543 3,259 0,210 0,654 7,123 13,50 11,0 2,517 Nordea 0,875 0,781 3,687 0,000 0,000 7,062 5,33 17,0 3,617 Sparekassen Hvetbo A/S 0,021 0,354 3,187 0,146 0,708 6,792 8,00 7,0 1,282 Vestjysk Bank A/S 0,128 0,553 2,128 0,128 0,532 6,702 7,83 7,0 1,867 Ringkjøbing Landbobank, Aktieselskab 0,000 0,444 3,800 0,089 0,644 6,556 7,50 10,0 2,033 Basisbank A/S 0,667 1,000 53,083 0,000 0,667 5,000 6,00 3,0 0,698
210 9 FINANCIAL EDUCATION
Financial Board Multiple Titel Education Experience Directorships Gender Independence Tenure Size CEO CEO/Board EIK Bank Danmark A/S 1,000 0,667 4,917 0,000 0,667 7,500 4,00 8,0 1,330 Nordea 0,875 0,781 3,687 0,000 0,000 7,062 5,33 17,0 3,617 Nykredit 0,697 0,636 8,333 0,000 0,000 7,485 5,50 9,0 1,751 Basisbank A/S 0,667 1,000 53,083 0,000 0,667 5,000 6,00 3,0 0,698 Danske Bank 0,470 0,694 4,389 0,357 0,582 10,482 16,50 22,0 2,677 Morsø Sparekasse A/S 0,407 0,907 3,037 0,037 0,667 12,222 9,00 11,0 1,100 Alm. Brand Bank A/S 0,368 0,526 4,632 0,000 0,684 12,474 6,33 20,0 2,024 Nørresundby Bank A/S 0,361 0,528 2,722 0,167 0,500 10,278 6,00 11,0 1,618 Fionia Bank A/S 0,333 0,611 4,852 0,167 0,611 9,167 9,00 13,0 1,568 DiBa Bank A/S 0,333 0,667 4,611 0,111 0,667 12,222 9,00 11,0 1,000 Djurslands Bank A/S 0,308 0,923 7,000 0,231 0,769 12,692 6,50 8,0 0,679 Spar Nord Bank 0,296 0,611 6,667 0,093 0,593 8,111 9,00 14,0 2,875 Lolland A/S, Sparekassen 0,278 0,500 3,278 0,250 0,667 9,194 6,00 15,0 1,714 Forstædernes Bank A/S 0,267 0,667 5,267 0,133 0,667 11,000 7,50 21,0 2,037 Sparekassen Faaborg A/S 0,250 0,214 2,607 0,125 0,768 9,750 9,33 19,0 2,714 Roskilde Bank, Aktieselskab 0,225 0,663 8,584 0,169 0,663 8,067 5,93 21,0 3,512 Max Bank A/S 0,222 0,593 3,296 0,111 0,667 14,148 9,00 5,0 0,432 SparTrelleborg/BankTrelleborg 0,217 0,370 1,978 0,217 0,674 9,109 9,20 6,0 1,002 Sparekassen Østjylland 0,213 0,255 1,340 0,085 0,638 8,362 7,83 8,0 1,588 Vordingborg Bank A/S 0,200 0,700 2,100 0,000 1,000 13,433 5,00 10,0 0,952 Merkur, Den Almennyttige Andelskasse 0,190 0,190 4,500 0,190 0,857 8,833 7,00 16,0 2,847 Lån og Spar Bank A/S 0,171 0,400 5,157 0,386 0,700 7,257 11,67 19,0 4,715 EBH Bank A/S 0,163 0,898 11,286 0,061 0,673 9,102 9,83 27,0 2,478 Skjern Bank, Aktieselskabet 0,158 0,605 8,921 0,079 0,711 7,579 6,33 10,0 1,876 Jyske Bank 0,148 0,574 5,389 0,111 0,667 8,463 9,00 14,0 2,569 Middelfart Sparekasse 0,148 0,519 2,037 0,148 0,667 10,185 9,00 30,0 3,601 Grønlandsbanken, Aktieselskab 0,140 0,480 2,280 0,280 0,680 7,580 8,33 7,0 0,982 Sparekassen Limfjorden 0,133 0,711 1,644 0,000 1,000 8,200 7,50 4,0 0,512 Vestjysk Bank A/S 0,128 0,553 2,128 0,128 0,532 6,702 7,83 7,0 1,867 Sammenslutningen Danske Andelskasser 0,115 0,885 4,154 0,000 1,000 7,673 8,66 7,0 0,986 Hobro, Sparekassen 0,111 0,500 1,907 0,111 0,667 9,037 9,00 14,0 2,236 Spar Salling Sparekasse 0,107 0,375 1,321 0,214 0,786 7,464 9,33 6,0 0,892 Tønder Bank A/S 0,091 0,727 3,015 0,182 0,818 12,167 5,00 16,0 1,194 Den Jyske Sparekasse 0,087 0,333 1,797 0,087 0,681 8,739 11,50 15,0 3,043 Aarhus Lokalbank Aktieselskab 0,086 0,571 4,514 0,000 0,743 9,828 5,83 21,0 3,297 Sydbank 0,086 0,700 6,814 0,214 0,657 9,257 11,67 19,0 2,992 Løkken Sparekasse 0,067 0,378 2,490 0,111 0,845 9,342 7,50 18,0 2,830 Skælskør Bank Aktieselskab 0,056 0,944 6,056 0,056 0,667 8,389 6,00 17,0 2,125 Thy, Sparekassen 0,033 0,574 3,623 0,131 0,754 8,345 10,17 15,0 2,830 Arbejdernes Landsbank, Aktieselskab 0,032 0,758 10,548 0,290 0,661 10,484 10,33 7,0 0,970 Kreditbanken A/S 0,028 0,833 5,778 0,000 1,000 16,917 6,00 10,0 0,690 Salling Bank A/S 0,028 0,667 3,278 0,139 0,667 9,417 6,00 14,0 1,618 Sparekassen Hvetbo A/S 0,021 0,354 3,187 0,146 0,708 6,792 8,00 7,0 1,282 Dronninglund Sparekasse 0,020 0,240 1,360 0,100 0,720 12,500 8,33 19,0 2,184 Morsø Bank, Aktieselskabet 0,020 0,471 2,431 0,176 0,706 11,784 8,50 7,0 1,001 Sparekassen Vendsyssel 0,012 0,543 3,259 0,210 0,654 7,123 13,50 11,0 2,517 Nordjyske Bank A/S 0,000 0,661 9,441 0,254 0,644 7,949 9,83 22,0 4,499 Sjælland, Sparekassen 0,000 0,481 3,204 0,111 0,630 11,778 9,00 31,0 4,385 Kronjylland, Sparekassen 0,000 0,444 1,907 0,167 0,667 9,296 9,00 22,0 4,322 Amagerbanken Aktieselskab 0,000 0,649 17,324 0,162 0,730 9,243 6,16 23,0 3,226 Møns Bank, A/S 0,000 0,533 2,733 0,400 1,000 8,800 5,00 21,0 2,251 Skals, Sparekassen i 0,000 0,156 1,089 0,244 0,667 9,356 7,50 16,0 2,054 Himmerland A/S, Sparekassen 0,000 0,667 6,278 0,000 0,667 13,667 6,00 21,0 2,049 Ringkjøbing Landbobank, Aktieselskab 0,000 0,444 3,800 0,089 0,644 6,556 7,50 10,0 2,033 Sparbank A/S 0,000 0,511 5,511 0,255 0,532 10,745 7,83 12,0 1,997 Brørup Sparekasse 0,000 0,400 1,800 0,000 1,000 12,400 5,00 23,0 1,944 Farsø, Sparekassen 0,000 0,294 2,608 0,137 0,667 8,745 8,50 10,0 1,748 Østjydsk Bank A/S 0,000 0,559 4,412 0,059 0,706 14,765 5,67 16,0 1,720 Svendborg Sparekasse 0,000 0,471 7,824 0,000 0,647 9,471 5,67 7,8 1,155 Totalbanken A/S 0,000 0,500 2,694 0,167 0,667 11,139 6,00 8,7 1,040 Frøs Herreds Sparekasse 0,000 0,200 1,400 0,333 0,800 9,767 10,00 8,8 0,986 Vestfyns Bank A/S 0,000 0,682 3,659 0,136 0,545 8,704 7,33 8,0 0,960 Nr. Nebel og Omegn, Sparekassen for 0,000 0,333 2,167 0,000 0,833 12,667 6,00 12,0 0,947 Lollands Bank, Aktieselskab 0,000 0,667 3,861 0,000 0,667 13,694 6,00 10,0 0,860 Nordfyns Bank, Aktieselskabet 0,000 0,750 2,361 0,167 0,667 11,694 6,00 4,0 0,410 Lokalbanken i Nordsjælland 0,000 0,385 2,000 0,077 0,692 9,769 6,50 Bonusbanken 0,000 0,912 4,088 0,206 1,000 10,206 5,670 9,000 0,882
211 10 BOARD SIZE
Financial Board Multiple Bank Education Experience Directorships Gender Independence Tenure Size CEO CEO/Board
Danske Bank 0,470 0,694 4,389 0,357 0,582 10,482 16,50 22,0 2,677 Sparekassen Vendsyssel 0,012 0,543 3,259 0,210 0,654 7,123 13,50 11,0 2,517 Sydbank 0,086 0,700 6,814 0,214 0,657 9,257 11,67 19,0 2,992 Lån og Spar Bank A/S 0,171 0,400 5,157 0,386 0,700 7,257 11,67 19,0 4,715 Den Jyske Sparekasse 0,087 0,333 1,797 0,087 0,681 8,739 11,50 15,0 3,043 Arbejdernes Landsbank, Aktieselskab 0,032 0,758 10,548 0,290 0,661 10,484 10,33 7,0 0,970 Thy, Sparekassen 0,033 0,574 3,623 0,131 0,754 8,345 10,17 15,0 2,830 Frøs Herreds Sparekasse 0,000 0,200 1,400 0,333 0,800 9,767 10,00 8,8 0,986 EBH Bank A/S 0,163 0,898 11,286 0,061 0,673 9,102 9,83 27,0 2,478 Nordjyske Bank A/S 0,000 0,661 9,441 0,254 0,644 7,949 9,83 22,0 4,499 Sparekassen Faaborg A/S 0,250 0,214 2,607 0,125 0,768 9,750 9,33 19,0 2,714 Spar Salling Sparekasse 0,107 0,375 1,321 0,214 0,786 7,464 9,33 6,0 0,892 SparTrelleborg/BankTrelleborg 0,217 0,370 1,978 0,217 0,674 9,109 9,20 6,0 1,002 Max Bank A/S 0,222 0,593 3,296 0,111 0,667 14,148 9,00 5,0 0,432 Morsø Sparekasse A/S 0,407 0,907 3,037 0,037 0,667 12,222 9,00 11,0 1,100 DiBa Bank A/S 0,333 0,667 4,611 0,111 0,667 12,222 9,00 11,0 1,000 Sjælland, Sparekassen 0,000 0,481 3,204 0,111 0,630 11,778 9,00 31,0 4,385 Middelfart Sparekasse 0,148 0,519 2,037 0,148 0,667 10,185 9,00 30,0 3,601 Kronjylland, Sparekassen 0,000 0,444 1,907 0,167 0,667 9,296 9,00 22,0 4,322 Fionia Bank A/S 0,333 0,611 4,852 0,167 0,611 9,167 9,00 13,0 1,568 Hobro, Sparekassen 0,111 0,500 1,907 0,111 0,667 9,037 9,00 14,0 2,236 Jyske Bank 0,148 0,574 5,389 0,111 0,667 8,463 9,00 14,0 2,569 Spar Nord Bank 0,296 0,611 6,667 0,093 0,593 8,111 9,00 14,0 2,875 Sammenslutningen Danske Andelskasser 0,115 0,885 4,154 0,000 1,000 7,673 8,66 7,0 0,986 Morsø Bank, Aktieselskabet 0,020 0,471 2,431 0,176 0,706 11,784 8,50 7,0 1,001 Farsø, Sparekassen 0,000 0,294 2,608 0,137 0,667 8,745 8,50 10,0 1,748 Dronninglund Sparekasse 0,020 0,240 1,360 0,100 0,720 12,500 8,33 19,0 2,184 Grønlandsbanken, Aktieselskab 0,140 0,480 2,280 0,280 0,680 7,580 8,33 7,0 0,982 Sparekassen Hvetbo A/S 0,021 0,354 3,187 0,146 0,708 6,792 8,00 7,0 1,282 Sparbank A/S 0,000 0,511 5,511 0,255 0,532 10,745 7,83 12,0 1,997 Sparekassen Østjylland 0,213 0,255 1,340 0,085 0,638 8,362 7,83 8,0 1,588 Vestjysk Bank A/S 0,128 0,553 2,128 0,128 0,532 6,702 7,83 7,0 1,867 Forstædernes Bank A/S 0,267 0,667 5,267 0,133 0,667 11,000 7,50 21,0 2,037 Skals, Sparekassen i 0,000 0,156 1,089 0,244 0,667 9,356 7,50 16,0 2,054 Løkken Sparekasse 0,067 0,378 2,490 0,111 0,845 9,342 7,50 18,0 2,830 Sparekassen Limfjorden 0,133 0,711 1,644 0,000 1,000 8,200 7,50 4,0 0,512 Ringkjøbing Landbobank, Aktieselskab 0,000 0,444 3,800 0,089 0,644 6,556 7,50 10,0 2,033 Vestfyns Bank A/S 0,000 0,682 3,659 0,136 0,545 8,704 7,33 8,0 0,960 Merkur, Den Almennyttige Andelskasse 0,190 0,190 4,500 0,190 0,857 8,833 7,00 16,0 2,847 Djurslands Bank A/S 0,308 0,923 7,000 0,231 0,769 12,692 6,50 8,0 0,679 Lokalbanken i Nordsjælland 0,000 0,385 2,000 0,077 0,692 9,769 6,50 Alm. Brand Bank A/S 0,368 0,526 4,632 0,000 0,684 12,474 6,33 20,0 2,024 Skjern Bank, Aktieselskabet 0,158 0,605 8,921 0,079 0,711 7,579 6,33 10,0 1,876 Amagerbanken Aktieselskab 0,000 0,649 17,324 0,162 0,730 9,243 6,16 23,0 3,226 Kreditbanken A/S 0,028 0,833 5,778 0,000 1,000 16,917 6,00 10,0 0,690 Lollands Bank, Aktieselskab 0,000 0,667 3,861 0,000 0,667 13,694 6,00 10,0 0,860 Himmerland A/S, Sparekassen 0,000 0,667 6,278 0,000 0,667 13,667 6,00 21,0 2,049 Nr. Nebel og Omegn, Sparekassen for 0,000 0,333 2,167 0,000 0,833 12,667 6,00 12,0 0,947 Nordfyns Bank, Aktieselskabet 0,000 0,750 2,361 0,167 0,667 11,694 6,00 4,0 0,410 Totalbanken A/S 0,000 0,500 2,694 0,167 0,667 11,139 6,00 8,7 1,040 Nørresundby Bank A/S 0,361 0,528 2,722 0,167 0,500 10,278 6,00 11,0 1,618 Salling Bank A/S 0,028 0,667 3,278 0,139 0,667 9,417 6,00 14,0 1,618 Lolland A/S, Sparekassen 0,278 0,500 3,278 0,250 0,667 9,194 6,00 15,0 1,714 Skælskør Bank Aktieselskab 0,056 0,944 6,056 0,056 0,667 8,389 6,00 17,0 2,125 Basisbank A/S 0,667 1,000 53,083 0,000 0,667 5,000 6,00 3,0 0,698 Roskilde Bank, Aktieselskab 0,225 0,663 8,584 0,169 0,663 8,067 5,93 21,0 3,512 Aarhus Lokalbank Aktieselskab 0,086 0,571 4,514 0,000 0,743 9,828 5,83 21,0 3,297 Østjydsk Bank A/S 0,000 0,559 4,412 0,059 0,706 14,765 5,67 16,0 1,720 Bonusbanken 0,000 0,912 4,088 0,206 1,000 10,206 5,670 9,000 0,882 Svendborg Sparekasse 0,000 0,471 7,824 0,000 0,647 9,471 5,67 7,8 1,155 Nykredit 0,697 0,636 8,333 0,000 0,000 7,485 5,50 9,0 1,751 Nordea 0,875 0,781 3,687 0,000 0,000 7,062 5,33 17,0 3,617 Vordingborg Bank A/S 0,200 0,700 2,100 0,000 1,000 13,433 5,00 10,0 0,952 Brørup Sparekasse 0,000 0,400 1,800 0,000 1,000 12,400 5,00 23,0 1,944 Tønder Bank A/S 0,091 0,727 3,015 0,182 0,818 12,167 5,00 16,0 1,194 Møns Bank, A/S 0,000 0,533 2,733 0,400 1,000 8,800 5,00 21,0 2,251 EIK Bank Danmark A/S 1,000 0,667 4,917 0,000 0,667 7,500 4,00 8,0 1,330
212 11 CEO VS BOARD
Financial Board Multiple Titel Education Experience Directorships Gender Independence Tenure Size CEO CEO/Board Lån og Spar Bank A/S 0,171 0,400 5,157 0,386 0,700 7,257 11,67 19,0 4,715 Nordjyske Bank A/S 0,000 0,661 9,441 0,254 0,644 7,949 9,83 22,0 4,499 Sjælland, Sparekassen 0,000 0,481 3,204 0,111 0,630 11,778 9,00 31,0 4,385 Kronjylland, Sparekassen 0,000 0,444 1,907 0,167 0,667 9,296 9,00 22,0 4,322 Nordea 0,875 0,781 3,687 0,000 0,000 7,062 5,33 17,0 3,617 Middelfart Sparekasse 0,148 0,519 2,037 0,148 0,667 10,185 9,00 30,0 3,601 Roskilde Bank, Aktieselskab 0,225 0,663 8,584 0,169 0,663 8,067 5,93 21,0 3,512 Aarhus Lokalbank Aktieselskab 0,086 0,571 4,514 0,000 0,743 9,828 5,83 21,0 3,297 Amagerbanken Aktieselskab 0,000 0,649 17,324 0,162 0,730 9,243 6,16 23,0 3,226 Den Jyske Sparekasse 0,087 0,333 1,797 0,087 0,681 8,739 11,50 15,0 3,043 Sydbank 0,086 0,700 6,814 0,214 0,657 9,257 11,67 19,0 2,992 Spar Nord Bank 0,296 0,611 6,667 0,093 0,593 8,111 9,00 14,0 2,875 Merkur, Den Almennyttige Andelskasse 0,190 0,190 4,500 0,190 0,857 8,833 7,00 16,0 2,847 Løkken Sparekasse 0,067 0,378 2,490 0,111 0,845 9,342 7,50 18,0 2,830 Thy, Sparekassen 0,033 0,574 3,623 0,131 0,754 8,345 10,17 15,0 2,830 Sparekassen Faaborg A/S 0,250 0,214 2,607 0,125 0,768 9,750 9,33 19,0 2,714 Danske Bank 0,470 0,694 4,389 0,357 0,582 10,482 16,50 22,0 2,677 Jyske Bank 0,148 0,574 5,389 0,111 0,667 8,463 9,00 14,0 2,569 Sparekassen Vendsyssel 0,012 0,543 3,259 0,210 0,654 7,123 13,50 11,0 2,517 EBH Bank A/S 0,163 0,898 11,286 0,061 0,673 9,102 9,83 27,0 2,478 Møns Bank, A/S 0,000 0,533 2,733 0,400 1,000 8,800 5,00 21,0 2,251 Hobro, Sparekassen 0,111 0,500 1,907 0,111 0,667 9,037 9,00 14,0 2,236 Dronninglund Sparekasse 0,020 0,240 1,360 0,100 0,720 12,500 8,33 19,0 2,184 Skælskør Bank Aktieselskab 0,056 0,944 6,056 0,056 0,667 8,389 6,00 17,0 2,125 Skals, Sparekassen i 0,000 0,156 1,089 0,244 0,667 9,356 7,50 16,0 2,054 Himmerland A/S, Sparekassen 0,000 0,667 6,278 0,000 0,667 13,667 6,00 21,0 2,049 Forstædernes Bank A/S 0,267 0,667 5,267 0,133 0,667 11,000 7,50 21,0 2,037 Ringkjøbing Landbobank, Aktieselskab 0,000 0,444 3,800 0,089 0,644 6,556 7,50 10,0 2,033 Alm. Brand Bank A/S 0,368 0,526 4,632 0,000 0,684 12,474 6,33 20,0 2,024 Sparbank A/S 0,000 0,511 5,511 0,255 0,532 10,745 7,83 12,0 1,997 Brørup Sparekasse 0,000 0,400 1,800 0,000 1,000 12,400 5,00 23,0 1,944 Skjern Bank, Aktieselskabet 0,158 0,605 8,921 0,079 0,711 7,579 6,33 10,0 1,876 Vestjysk Bank A/S 0,128 0,553 2,128 0,128 0,532 6,702 7,83 7,0 1,867 Nykredit 0,697 0,636 8,333 0,000 0,000 7,485 5,50 9,0 1,751 Farsø, Sparekassen 0,000 0,294 2,608 0,137 0,667 8,745 8,50 10,0 1,748 Østjydsk Bank A/S 0,000 0,559 4,412 0,059 0,706 14,765 5,67 16,0 1,720 Lolland A/S, Sparekassen 0,278 0,500 3,278 0,250 0,667 9,194 6,00 15,0 1,714 Salling Bank A/S 0,028 0,667 3,278 0,139 0,667 9,417 6,00 14,0 1,618 Nørresundby Bank A/S 0,361 0,528 2,722 0,167 0,500 10,278 6,00 11,0 1,618 Sparekassen Østjylland 0,213 0,255 1,340 0,085 0,638 8,362 7,83 8,0 1,588 Fionia Bank A/S 0,333 0,611 4,852 0,167 0,611 9,167 9,00 13,0 1,568 EIK Bank Danmark A/S 1,000 0,667 4,917 0,000 0,667 7,500 4,00 8,0 1,330 Sparekassen Hvetbo A/S 0,021 0,354 3,187 0,146 0,708 6,792 8,00 7,0 1,282 Tønder Bank A/S 0,091 0,727 3,015 0,182 0,818 12,167 5,00 16,0 1,194 Svendborg Sparekasse 0,000 0,471 7,824 0,000 0,647 9,471 5,67 7,8 1,155 Morsø Sparekasse A/S 0,407 0,907 3,037 0,037 0,667 12,222 9,00 11,0 1,100 Totalbanken A/S 0,000 0,500 2,694 0,167 0,667 11,139 6,00 8,7 1,040 SparTrelleborg/BankTrelleborg 0,217 0,370 1,978 0,217 0,674 9,109 9,20 6,0 1,002 Morsø Bank, Aktieselskabet 0,020 0,471 2,431 0,176 0,706 11,784 8,50 7,0 1,001 DiBa Bank A/S 0,333 0,667 4,611 0,111 0,667 12,222 9,00 11,0 1,000 Frøs Herreds Sparekasse 0,000 0,200 1,400 0,333 0,800 9,767 10,00 8,8 0,986 Sammenslutningen Danske Andelskasser 0,115 0,885 4,154 0,000 1,000 7,673 8,66 7,0 0,986 Grønlandsbanken, Aktieselskab 0,140 0,480 2,280 0,280 0,680 7,580 8,33 7,0 0,982 Arbejdernes Landsbank, Aktieselskab 0,032 0,758 10,548 0,290 0,661 10,484 10,33 7,0 0,970 Vestfyns Bank A/S 0,000 0,682 3,659 0,136 0,545 8,704 7,33 8,0 0,960 Vordingborg Bank A/S 0,200 0,700 2,100 0,000 1,000 13,433 5,00 10,0 0,952 Nr. Nebel og Omegn, Sparekassen for 0,000 0,333 2,167 0,000 0,833 12,667 6,00 12,0 0,947 Spar Salling Sparekasse 0,107 0,375 1,321 0,214 0,786 7,464 9,33 6,0 0,892 Bonusbanken 0,000 0,912 4,088 0,206 1,000 10,206 5,670 9,000 0,882 Lollands Bank, Aktieselskab 0,000 0,667 3,861 0,000 0,667 13,694 6,00 10,0 0,860 Basisbank A/S 0,667 1,000 53,083 0,000 0,667 5,000 6,00 3,0 0,698 Kreditbanken A/S 0,028 0,833 5,778 0,000 1,000 16,917 6,00 10,0 0,690 Djurslands Bank A/S 0,308 0,923 7,000 0,231 0,769 12,692 6,50 8,0 0,679 Sparekassen Limfjorden 0,133 0,711 1,644 0,000 1,000 8,200 7,50 4,0 0,512 Max Bank A/S 0,222 0,593 3,296 0,111 0,667 14,148 9,00 5,0 0,432 Nordfyns Bank, Aktieselskabet 0,000 0,750 2,361 0,167 0,667 11,694 6,00 4,0 0,410
213 12 CEO TENURE
Financial Board Multiple Bank Education Experience Directorships Gender Independence Tenure Size CEO CEO/Board
Sjælland, Sparekassen 0,000 0,481 3,204 0,111 0,630 11,778 9,00 31,0 4,385 Middelfart Sparekasse 0,148 0,519 2,037 0,148 0,667 10,185 9,00 30,0 3,601 EBH Bank A/S 0,163 0,898 11,286 0,061 0,673 9,102 9,83 27,0 2,478 Amagerbanken Aktieselskab 0,000 0,649 17,324 0,162 0,730 9,243 6,16 23,0 3,226 Brørup Sparekasse 0,000 0,400 1,800 0,000 1,000 12,400 5,00 23,0 1,944 Danske Bank 0,470 0,694 4,389 0,357 0,582 10,482 16,50 22,0 2,677 Nordjyske Bank A/S 0,000 0,661 9,441 0,254 0,644 7,949 9,83 22,0 4,499 Kronjylland, Sparekassen 0,000 0,444 1,907 0,167 0,667 9,296 9,00 22,0 4,322 Forstædernes Bank A/S 0,267 0,667 5,267 0,133 0,667 11,000 7,50 21,0 2,037 Himmerland A/S, Sparekassen 0,000 0,667 6,278 0,000 0,667 13,667 6,00 21,0 2,049 Roskilde Bank, Aktieselskab 0,225 0,663 8,584 0,169 0,663 8,067 5,93 21,0 3,512 Aarhus Lokalbank Aktieselskab 0,086 0,571 4,514 0,000 0,743 9,828 5,83 21,0 3,297 Møns Bank, A/S 0,000 0,533 2,733 0,400 1,000 8,800 5,00 21,0 2,251 Alm. Brand Bank A/S 0,368 0,526 4,632 0,000 0,684 12,474 6,33 20,0 2,024 Sydbank 0,086 0,700 6,814 0,214 0,657 9,257 11,67 19,0 2,992 Lån og Spar Bank A/S 0,171 0,400 5,157 0,386 0,700 7,257 11,67 19,0 4,715 Sparekassen Faaborg A/S 0,250 0,214 2,607 0,125 0,768 9,750 9,33 19,0 2,714 Dronninglund Sparekasse 0,020 0,240 1,360 0,100 0,720 12,500 8,33 19,0 2,184 Løkken Sparekasse 0,067 0,378 2,490 0,111 0,845 9,342 7,50 18,0 2,830 Skælskør Bank Aktieselskab 0,056 0,944 6,056 0,056 0,667 8,389 6,00 17,0 2,125 Nordea 0,875 0,781 3,687 0,000 0,000 7,062 5,33 17,0 3,617 Skals, Sparekassen i 0,000 0,156 1,089 0,244 0,667 9,356 7,50 16,0 2,054 Merkur, Den Almennyttige Andelskasse 0,190 0,190 4,500 0,190 0,857 8,833 7,00 16,0 2,847 Østjydsk Bank A/S 0,000 0,559 4,412 0,059 0,706 14,765 5,67 16,0 1,720 Tønder Bank A/S 0,091 0,727 3,015 0,182 0,818 12,167 5,00 16,0 1,194 Den Jyske Sparekasse 0,087 0,333 1,797 0,087 0,681 8,739 11,50 15,0 3,043 Thy, Sparekassen 0,033 0,574 3,623 0,131 0,754 8,345 10,17 15,0 2,830 Lolland A/S, Sparekassen 0,278 0,500 3,278 0,250 0,667 9,194 6,00 15,0 1,714 Hobro, Sparekassen 0,111 0,500 1,907 0,111 0,667 9,037 9,00 14,0 2,236 Jyske Bank 0,148 0,574 5,389 0,111 0,667 8,463 9,00 14,0 2,569 Spar Nord Bank 0,296 0,611 6,667 0,093 0,593 8,111 9,00 14,0 2,875 Salling Bank A/S 0,028 0,667 3,278 0,139 0,667 9,417 6,00 14,0 1,618 Fionia Bank A/S 0,333 0,611 4,852 0,167 0,611 9,167 9,00 13,0 1,568 Sparbank A/S 0,000 0,511 5,511 0,255 0,532 10,745 7,83 12,0 1,997 Nr. Nebel og Omegn, Sparekassen for 0,000 0,333 2,167 0,000 0,833 12,667 6,00 12,0 0,947 Sparekassen Vendsyssel 0,012 0,543 3,259 0,210 0,654 7,123 13,50 11,0 2,517 Morsø Sparekasse A/S 0,407 0,907 3,037 0,037 0,667 12,222 9,00 11,0 1,100 DiBa Bank A/S 0,333 0,667 4,611 0,111 0,667 12,222 9,00 11,0 1,000 Nørresundby Bank A/S 0,361 0,528 2,722 0,167 0,500 10,278 6,00 11,0 1,618 Farsø, Sparekassen 0,000 0,294 2,608 0,137 0,667 8,745 8,50 10,0 1,748 Ringkjøbing Landbobank, Aktieselskab 0,000 0,444 3,800 0,089 0,644 6,556 7,50 10,0 2,033 Skjern Bank, Aktieselskabet 0,158 0,605 8,921 0,079 0,711 7,579 6,33 10,0 1,876 Kreditbanken A/S 0,028 0,833 5,778 0,000 1,000 16,917 6,00 10,0 0,690 Lollands Bank, Aktieselskab 0,000 0,667 3,861 0,000 0,667 13,694 6,00 10,0 0,860 Vordingborg Bank A/S 0,200 0,700 2,100 0,000 1,000 13,433 5,00 10,0 0,952 Bonusbanken 0,000 0,912 4,088 0,206 1,000 10,206 5,670 9,000 0,882 Nykredit 0,697 0,636 8,333 0,000 0,000 7,485 5,50 9,0 1,751 Frøs Herreds Sparekasse 0,000 0,200 1,400 0,333 0,800 9,767 10,00 8,8 0,986 Totalbanken A/S 0,000 0,500 2,694 0,167 0,667 11,139 6,00 8,7 1,040 Sparekassen Østjylland 0,213 0,255 1,340 0,085 0,638 8,362 7,83 8,0 1,588 Vestfyns Bank A/S 0,000 0,682 3,659 0,136 0,545 8,704 7,33 8,0 0,960 Djurslands Bank A/S 0,308 0,923 7,000 0,231 0,769 12,692 6,50 8,0 0,679 EIK Bank Danmark A/S 1,000 0,667 4,917 0,000 0,667 7,500 4,00 8,0 1,330 Svendborg Sparekasse 0,000 0,471 7,824 0,000 0,647 9,471 5,67 7,8 1,155 Arbejdernes Landsbank, Aktieselskab 0,032 0,758 10,548 0,290 0,661 10,484 10,33 7,0 0,970 Sammenslutningen Danske Andelskasser 0,115 0,885 4,154 0,000 1,000 7,673 8,66 7,0 0,986 Morsø Bank, Aktieselskabet 0,020 0,471 2,431 0,176 0,706 11,784 8,50 7,0 1,001 Grønlandsbanken, Aktieselskab 0,140 0,480 2,280 0,280 0,680 7,580 8,33 7,0 0,982 Sparekassen Hvetbo A/S 0,021 0,354 3,187 0,146 0,708 6,792 8,00 7,0 1,282 Vestjysk Bank A/S 0,128 0,553 2,128 0,128 0,532 6,702 7,83 7,0 1,867 Spar Salling Sparekasse 0,107 0,375 1,321 0,214 0,786 7,464 9,33 6,0 0,892 SparTrelleborg/BankTrelleborg 0,217 0,370 1,978 0,217 0,674 9,109 9,20 6,0 1,002 Max Bank A/S 0,222 0,593 3,296 0,111 0,667 14,148 9,00 5,0 0,432 Sparekassen Limfjorden 0,133 0,711 1,644 0,000 1,000 8,200 7,50 4,0 0,512 Nordfyns Bank, Aktieselskabet 0,000 0,750 2,361 0,167 0,667 11,694 6,00 4,0 0,410 Basisbank A/S 0,667 1,000 53,083 0,000 0,667 5,000 6,00 3,0 0,698 Lokalbanken i Nordsjælland 0,000 0,385 2,000 0,077 0,692 9,769 6,50 * *
214 13 SAS OUTPUT
13.1 REGRESSION OUTPUT MODEL 1A
Linear Regression Results The REG Procedure
Model: Linear_Regression_Model
Dependent Variable: 2007
Number of Observations Read 743 Number of Observations Used 743 Number of Observations with Missing Values 10
Backward Elimination: Step 0
All Variables Entered: R-Square = 0.0210 and C(p) = 7.0000
Weight: Weight
Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 6 5512.06790 918.67798 2.59 0.0171 Error 726 257197 354.26556 Corrected Total 732 262709
Parameter Standard Variable Estimate Error Type II SS F Value Pr > F In tercept 116.17460 3.12113 490826 1385.48 <.0001 Financial Education 5.75317 2.37279 2082.69233 5.88 0.0156 Board Experience -5.57599 2.19205 2292.29367 6.47 0.0112 Multiple Directorships -3.49131 2.16014 925.42692 2.61 0.1065 Gender 2.63181 2.51854 386.84911 1.09 0.2964 Independence 2.16850 2.13001 367.18555 1.04 0.3090 Tenure 0.31129 0.15205 1484.79446 4.19 0.0410
Bounds on condition number: 1.707, 47.056
215
Backward Elimination: Step 1
Variable Independence Removed: R-Square = 0.0196 and C(p) = 6.0365
Weight: Weight
Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 5 5144.88236 1028.97647 2.90 0.0132 Error 727 257564 354.28334 Corrected Total 732 262709
Parameter Stan dard Variable Estimate Error Type II SS F Value Pr > F Intercept 117.40785 2.87654 590207 1665.92 <.0001 Financial Education 5.33734 2.33743 1847.24067 5.21 0.0227 Board Experience -4.84645 2.07167 1938.90759 5.47 0.0196 Multiple Directorships -3.70873 2.14961 1054.58538 2.98 0.0849 Gender 2.12168 2.46825 261.77727 0.74 0.3903 Tenure 0.32551 0.15141 1637.37050 4.62 0.0319
Bounds on condition number: 1.5246, 30.802
Backward Elimination: Step 2
Variable Køn Removed: R-Square = 0.0186 and C(p) = 4.7754
Weight: Weight
Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 4 4883.10509 1220.77627 3.45 0.0084 Error 728 257826 354.15627 Corrected Total 732 262709
Parameter Standard Variable Estimate Error Type II SS F Value Pr > F Intercept 117.96287 2.80264 627411 1771.57 <.0001 Financial Education 5.39022 2.33620 1885.33101 5.32 0.0213 Board Experience -5.10650 2.04910 2199.46266 6.21 0.0129 Multiple Directorships -3.59237 2.14496 993.38893 2.80 0.0944 Tenure 0.30617 0.14970 1481.28476 4.18 0.0412
Bounds on condition number: 1.4921, 20.026 All variables left in the model are significant at the 0.1000 level.
216
Weight: Weight
Summary of Backward Elimination Variable Number Partial Model Step Removed Vars In R-Square R-Square C(p) F Value Pr > F 1 Independence 5 0.0014 0.0196 6.0365 1.04 0.3090 2 Gender 4 0.0010 0.0186 4.7754 0.74 0.3903
217 13.2 REGRESSION OUTPUT MODEL 1B
Linear Regression Results The REG Procedure
Model: Linear_Regression_Model
Dependent Variable: 2007
Number of Observations Read 517 Number of Observations Used 512 Number of Observations with Missing Values 5
Backward Elimination: Step 0
All Variables Entered: R-Square = 0.0437 and C(p) = 7.0000
Weight: Weight
Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 6 8145.09415 1357.51569 3.85 0.0009 Error 505 178155 352.78304 Corrected Total 511 186301
Parameter Standard Variable Estimate Error Type II SS F Value Pr > F Intercept 103.31510 5.32550 132775 376.36 <.0001 Tenure 0.34481 0.17600 1354.09612 3.84 0.0506 Board Experience -4.81896 2.48429 1327.42897 3.76 0.0530 Gender 3.34607 3.67901 291.82190 0.83 0.3635 Financial Education 7.98496 2.85417 2761.17336 7.83 0.0053 Multiple Directorships -4.07552 2.23503 1173.01849 3.33 0.0688 Independence 14.35131 4.35530 3830.49091 10.86 0.0011
Bounds on condition number: 1.3227, 41.518 Backward Elimination: Step 1
Variable Køn Removed: R-Square = 0.0422 and C(p) = 5.8272
Weight: Weight
Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 5 7853.27225 1570.65445 4.45 0.0006
218 Error 506 178447 352.66257 Corrected Total 511 186301
Parameter Standard Variable Estimate Error Type II SS F Value Pr > F Intercept 104.09118 5.25579 138328 392.24 <.0001 Tenure 0.32720 0.17490 1234.28635 3.50 0.0619 Board Experience -5.03276 2.47272 1460.90726 4.14 0.0423 Financial Education 8.15261 2.84772 2890.39355 8.20 0.0044 Multiple Directorships -4.00186 2.23319 1132.49048 3.21 0.0737 Independence 14.09564 4.34548 3710.68187 10.52 0.0013
Bounds on condition number: 1.3109, 29.194 All variables left in the model are significant at the 0.1000 level.
Weight: Vægt
Summary of Backward Elimination Variable Number Partial Model Step Removed Vars In R-Square R-Square C(p) F Value Pr > F 1 Gender 5 0.0016 0.0422 5.8272 0.83 0.3635
Generated by the SAS System ('Local', XP_PRO) on July 15, 2010 at 09:25:44 AM
Linear Regression Results The REG Procedure
Model: Linear_Regression_Model
Dependent Variable: 2007
219 13.3 REGRESSION OUTPUT MODEL 2A
Linear Regression Results The REG Procedure
Model: Linear_Regression_Model
Dependent Variable: 2007
Number of Observations Read 67 Number of Observations Used 67
Backward Elimination: Step 0
All Variables Entered: R-Square = 0.2315 and C(p) = 5.0000
Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 4 11114 2778.44997 4.59 0.0026 Error 61 36901 604.93740 Corrected Total 65 48015
Parameter Standard Variable Estimate Error Type II SS F Value Pr > F Intercept 107.27839 11.61208 51632 85.35 <.0001 Board Size I ncl. Rep -0.01818 1.45277 0.09472 0.00 0.9901 Bonus 14.03624 7.67323 2024.20808 3.35 0.0723 Shares 16.50854 7.02597 3339.75799 5.52 0.0220 CEO/Board Incl. Rep 3.67065 3.03187 886.69309 1.47 0.2307
Bounds on condition number : 1.2284, 18.822 Backward Elimination: Step 1
Variable Board Size incl. Rep Removed: R-Square = 0.2315 and C(p) = 3.0002
Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 3 11114 3704.56839 6.22 0.0009 Error 62 36901 595.18187 Corrected Total 65 48015
Parameter Standard Variable Estimate Error Type II SS F Value Pr > F
220 Intercept 107.15731 6.36789 168540 283.17 <.0001 Bonus 14.03148 7.60176 2027.81528 3.41 0.0697 Shares 16.51816 6.92723 3384.18696 5.69 0.0202 CEO/Board I ncl . Rep 3.65898 2.86174 972.99535 1.63 0.2058
Bounds on condition number: 1.2254, 10.373 Backward Elimination: Step 2
Variable CEO/Board (incl rep) Removed: R-Square = 0.2112 and C(p) = 2.6086
Analysis of Var iance Sum of Mean Source DF Squares Square F Value Pr > F Model 2 10141 5070.35491 8.43 0.0006 Error 63 37874 601.17891 Corrected Total 65 48015
Parameter Standard Variable Estimate Error Type II SS F Value Pr > F Intercept 113.67523 3.83532 528119 878.47 <.0001 Bonus 15.86997 7.50204 2690.27807 4.48 0.0384 Shares 16.76760 6.95928 3489.93644 5.81 0.0189
Bounds on condition number: 1.1816, 4.7262 All variables left in the model are significant at the 0.1000 level.
Summary of B ackward Elimination Variable Number Partial Model Step Removed Vars In R-Square R-Square C(p) F Value Pr > F 1 Board Size Incl. Rep 3 0.0000 0.2315 3.0002 0.00 0.9901 2 CEO/Board Incl. Rep 2 0.0203 0.2112 2.6086 1.63 0.2058
Generated by the SAS System ('Local', XP_PRO) on July 15, 2010 at 09:34:03 AM
221 13.4 REGRESSION OUTPUT MODEL 2B
Linear Regression Results The REG Procedure
Model: Linear_Regression_Model
Dependent Variable: 2007
Number of Observations Read 67 Number of Observation s Used 67
Backward Elimination: Step 0
All Variables Entered: R-Square = 0.2890 and C(p) = 5.0000
Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 4 13512 3377.92907 6.10 0.0003 Error 60 33243 554.04216 Corrected Total 64 46754
Parameter Standard Variable Estimate Error Type II SS F Value Pr > F Intercept 105.32506 11.27271 48367 87.30 <.0001 Bonus 14.92437 7.33735 2292.22108 4.14 0.0464 Shares 18.12760 6.73692 4011.44236 7.24 0.0092 Board siz e -0.40552 1.37176 48.41834 0.09 0.7685 CEO/Board 5.02144 2.95147 1603.69946 2.89 0.0941
Bounds on condition number: 1.2199, 18.584
Backward Elimination: Step 1
Variable Boardsize Removed: R-Square = 0.2880 and C(p) = 3.0874
Analysis of Va riance Sum of Mean Source DF Squares Square F Value Pr > F Model 3 13463 4487.76599 8.22 0.0001 Error 61 33291 545.75325 Corrected Total 64 46754
Parameter Standard Variable Estimate Error Type II SS F Value Pr > F Intercept 102.58797 6.38201 141018 258.39 <.0001 Cash Bonus 14.81705 7.27334 2264.91803 4.15 0.0460 Shares 18.34958 6.64467 4161.98975 7.63 0.0076 CEO/Board 4.77532 2.81035 1575.72799 2.89 0.0944
222 Bounds on condition number: 1.2169, 10.305 All variables left in the model are significant at the 0.1000 level.
Summary of Backward Elimination Variable Number Partial Model Step Removed Vars In R-Square R-Square C(p) F Value Pr > F 1 Boardsize 3 0.0010 0.2880 3.0874 0.09 0.7685
Generated by the SAS System ('Local', XP_PRO) on July 15, 2010 at 09:39:12 AM
Linear Regression Results The REG Procedure
Model: Linear_Regression_Model
Dependent Variable: 2007
223 14 CORRELATION SCATTER P LOT
Source: http://www.sci.sdsu.edu/class/psychol ogy/psy271/Weeks/psy271week07.htm
224 15 CORRELATION OUTPUT
15.1 CORRELATION MODEL 1A
Correlation Analysis The CORR Procedure
6 Variables: Financial Education, Board Experience, Gender, Multiple Directorship, Tenure
Pearson Correlation Coefficients Prob > |r| under H0: Rho=0 Number of Observations Dummy Finansielt antal Bestyrelses uddannet poster Køn Independence Antal År Erfaring Finansielt uddannet 1.00000 -0.06877 0.08223 -0.26804 - 0.12471 0.1213 0.0638 <.0001 0.09113 0.0049 509 509 509 509 0.0399 508
509
Dummy antal poster -0.06877 1.00000 0.09927 0.00150 - -0.51715 0.1213 0.0248 0.9730 0.09966 <.0001 509 511 511 511 0.0243 510
511
Køn 0.08223 0.09927 1.00000 -0.11400 - -0.13536 0.0638 0.0248 0.0099 0.13520 0.0022 509 511 511 511 0.0022 510
511
Independence -0.26804 0.00150 - 1.00000 0.06448 0.03715 <.0001 0.9730 0.11400 0.1455 0.4025 509 511 0.0099 511 511 510
511
Antal År -0.09113 -0.09966 - 0.06448 1.00000 0.12950 0.0399 0.0243 0.13520 0.1455 0.0034 509 511 0.0022 511 511 510
511
Bestyrelses Erfaring 0.12471 -0.51715 - 0.03715 0.12950 1.00000 0.0049 <.0001 0.13536 0.4025 0.0034 508 510 0.0022 510 510 510
510
Generated by the SAS System ('Local', XP_PRO) on July 15, 2010 at 09:46:33 AM
225 15.2 CORRELATION MODEL 1B
Correlation Analysis The CORR Procedure
6 Variables: Financial Education, Board Experience, Gender, Multiple Directorship, Tenure
Pearson Correlation Coefficients Prob > |r| under H0: Rho=0 Number of Observations Financial Board Multiple Education Experience Gender Independence Directorships Tenure Financial Education 1.00000 0.12478 0.00105 -0.08598 -0.07243 0.11195 0.0008 0.9775 0.0205 0.0511 0.0026 726 725 726 726 726 720
Board Experience 0.12478 1.00000 - 0.46399 -0.58272 - 0.0008 0.24406 <.0001 <.0001 0.46484 725 730 <.0001 730 730 <.0001
730 724
Gender 0.00105 -0.24406 1.00000 -0.31230 0.19239 0.30433 0.9775 <.0001 <.0001 <.0001 <.0001 726 730 731 731 731 725
Independence -0.08598 0.46399 - 1.00000 -0.34189 - 0.0205 <.0001 0.31230 <.0001 0.91167 726 730 <.0001 731 731 <.0001
731 725
Multiple Directorships -0.07243 -0.58272 0.19239 -0.34189 1.00000 0.34341 0.0511 <.0001 <.0001 <.0001 <.0001 726 730 731 731 731 725
Tenure 0.11195 -0.46484 0.30433 -0.91167 0.34341 1.00000 0.0026 <.0001 <.0001 <.0001 <.0001 720 724 725 725 725 725
226
15.3 CORRELATION MODEL 2A
Correlation Analysis The CORR Procedure
4 Variables: Board Size incl. Rep Bonus Shares CEO/Board incl. rep
Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum Board Size incl. Rep 67 7.79167 2.22320 514.25000 4.00000 16.50000 Bonus 67 0.25758 0.44065 17.00000 0 1.00000 Shares 67 0.33333 0.47502 22.00000 0 1.00000 CEO/Board incl . Rep 67 1.93349 1.08341 127.61058 0 4.71464
Pearson Correlation Coefficients, N = 66 Prob > |r| under H0: Rho=0 Board Size incl. Rep Bonus Shares CEO/Board (incl rep) Board Size incl. Rep 1.00000 0.07509 -0.05837 0.31137 0.5490 0.6416 0.0109
Bonus 0.07509 1.00000 0.39200 0.21608 0.5490 0.0011 0.0814
Shares -0.05837 0.39200 1.00000 0.11000 0.6416 0.0011 0.3793
CEO/Board (incl rep) 0.31137 0.21608 0.11000 1.00000 0.0109 0.0814 0.3793
227 15.4 CORRELATION MODEL 2B
Correlatio n Analysis The CORR Procedure
4 Variables: Bonus Board Size excl Rep Shares CEO/Board (iexcl rep)
Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum Bonus 67 0.25758 0.44065 17.00000 0 1.00000 Board Size excl Rep 67 5.62409 1.52267 371.19000 3.50000 10.83000 Shares 67 0.33333 0.47502 22.00000 0 1.00000 CEO/Board (iexcl rep) 67 1.78399 0.94029 117.74318 0 4.04255
Pearson Correlation Coefficients, N = 66 Prob > |r| under H0: Rho=0 Bonus Board Size excl Rep Shares CEO/Board (iexc l rep) Bonus 1.00000 -0.00618 0.39200 0.20604 0.9607 0.0011 0.0970
Board Size excl Rep -0.00618 1.00000 -0.10061 0.19442 0.9607 0.4215 0.1178
Shares 0.39200 -0.10061 1.00000 0.05389 0.0011 0.4215 0.6674
CEO/Boa rd excl rep 0.20604 0.19442 0.05389 1.00000 0.0970 0.1178 0.6674
228