Toward a Quadruple Bottom Line: Social Disclosure and Financial Performance in the Banking Sector

Abstract

The present study aims to analyze the existence of a possible significant relationship between social disclosure and financial performance in banking institutions. This phenomenon was analyzed by considering the percentage of female executives on boards, and the implementation of the equal opportunity policy when it was applied. We used a sample of 61 banks from European Union countries (between 2015–2017), and sampling was environmental, social, or governance (ESG)-driven in order to capture the effect of non-financial disclosure provided by Bloomberg. A cross-section econometric model was built in order to examine the relationship between the percentage of female directors on boards and the equal opportunity policy. Both the independent variables of banks and performance indicators were adopted as dependent variables. Our study provides empirical evidence that while there is a lack of efficiency and performance when boards are fragmented, the enactments of equal opportunity policies create a good reputation for the firm and the positive performance of staff. The study aims to contribute to the ongoing debate on social sustainability and on the phenomenon of the glass ceiling, and provides political and entrepreneurial implications.

1. Introduction

Banking institutions play a crucial role in the accomplishment of the United Nations’ Sustainable Development Goals (SDGs) [1]. Their activity goes beyond a mere matter of ecological impact tout-court, being a zero-emission industrial sector—as is considered in several empirical analyses on corporate sustainability [2,3]. Their indirect impact on sustainable activities is, instead, noticeable: for example, they can boost clean energy projects, invest in green bonds, offer green credit funds, and finance virtuous social initiatives [4]. All these practices, as discussed in the literature, enhance the corporate social performance (CSP) of the banking institutions, which has a positive impact on their corporate financial performance (CFP) [5]. Other relevant outcomes are attributed to the increased corporate social responsibility (CSR) practices [6] as an instrument to improve both corporate reputation and firm performance [7].

The impact of banking activity on external stakeholders is significantly positive when CSR commitment occurs, and it is increased by continuous social reporting through the years [8,9]. The current literature contains several studies on how banks incentivize sustainable development [10,11]. This field of study outlines, in particular, the efforts carried out by financial institutions, as well as concentrating on the single area of action, such as environmental credit risk management, sustainable project finance, impact investing, and banking loans activities [12,13]. Recent studies have focused on how banks implement their strategies to promote sustainability in an enlarged perspective, while assessing internal operations, too [14].

This is quite an unexplored field, which opens a wide range of questions that ought to be answered. An interesting dimension is provided by the role of environmental, social, or governance (ESG) disclosure, which is the clarification of sustainability strategies carried on by firms—even banking institutions.

In the last few years, new literature in the field of corporate sustainability has emerged, introducing the field of study to new issues regarding the inclusion of corporate governance sustainability. This includes research on the Triple Bottom Line (TBL) concept [15] in the new framework of the Quadruple Bottom Line [16,17,18,19,20]. The long perpetrated financial crisis that occurred in 2007—the consequences of which are still felt in the current economy—showcased several issues, especially regarding social and governance problems [21]. This is because, while banks might only have an indirect effect on the environment, as the financial industry is a zero-emission sector, social and governance issues are critical concerns regarding corporate sustainability in the banking sector. The global financial crisis (GFC) sparked a debate on the role of corporate governance strategies because they had a crucial impact on the catastrophic outcome of the GFC [22,23]. One of the most recently debated issues on corporate governance improvement is gender diversity on boards. As a result, many financial firms have recently begun to adopt gender balance strategies. The EU Commission has approved several directives to satisfy the gender balance for non-executive directors, which should come into force in 2020 for listed companies [24]. The European Parliament has also approved a regulation recommendation for large firms to increase the number of under-represented gender members (usually women) in non-executive roles to at least 40% of the total directors in order to reduce the existing gender gap. While these are positive examples, such as the Norwegian model [25], the results are far from being satisfactory. This is due to an ongoing debate regarding the real effects of board diversity on corporate governance issues and on operative results. Jensen and Anderson, among others, have stated that more visible diversity is a positive outcome of efficient resource utilization and better innovative product and strategy development, which includes a cross-sectional mix of competences and backgrounds [26,27]. Furthermore, regarding social and corporate governance issues, Farag and Mallin argue that a larger presence of women on boards is helpful in the reduction of the phenomenon of the “glass ceiling” [21] and provides higher incomes for women in high directive positions. Moreover, Putnam takes a different position, arguing that the costs of communication and coordination due to diversity could overcome the benefits [28].

The aim of the paper is to investigate the impact of two dimensions of ESG disclosure—specifically, the governance and the social components—by analyzing variables of gender diversity in board composition and the effort of the firm in actively adopting non-discrimination policies on financial performance. We do this using a sample of 61 banks from the 28 countries of the European Union between 2015 and 2017. The result of the empirical analysis shows a negative relationship between diverse board composition and operative result measures, and a positive relationship between equal opportunity policies and return on equity.

The choice of banking sector is related to the strategical importance of the latter in financing sustainable economic development [1,2,3,4]. Therefore, it is crucial to investigate whether the banking sector has sought more environmentally sustainable goals since the GFC. The current literature shows that gender diversity in board composition and the adoption of non-discrimination policies are a clear example in this perspective [29,30]. Therefore, this contribution could be a further observation regarding the sustainable path of a strategic area.

The theoretical contribution of this paper is consistent with other studies that argue that the cohesion and homogeneity of boards have a positive impact on financial performance in the presence of highly profitable activities. The reason for this is the reduction of assertiveness in the decision-making process. Moreover, it suggests that, according to the results, the social component related to non-discrimination policies has a positive impact on market capitalization, implying a positive reaction from the market towards adequate social policies for inclusion.

The paper is composed as follows: in Section 2, we explore the current literature on sustainability strategies in banking and the gender and inclusion policies related to corporate governance strategies. Then, in Section 3, we discuss the methodology and sampling used, matching them with the hypothesis formulation. The final sections, Section 4, Section 5 and Section 6, consist of an in-depth examination of results, a discussion on the results, the political implications, and the conclusions.

2. Theoretical Background and Hypotheses Development

The goal of the present work is to contribute to the analysis of the social and governance dimensions of sustainability, focusing on the bank sector. The intent is to observe if the two aforementioned performances could affect the CFP of banking institutions. Gender diversity and non-discrimination policies are present in the ESG disclosure, indicating the sustainable commitment inside the CSP framework.

The following literature review was developed by taking the main contributions present in the scientific context into account, starting with an overview of the research area from a firm perspective, notwithstanding the industrial sector. Indeed, a specific focus on banks, which has only recently gained much interest [29,30], could not prospect the whole phenomenon in its entirety.

With regard to the CSP, it is important to underline the presence of a full-bodied literature from different decades and, until now, there has not been a convergent definition that can define precise borders [31]. Surely, this difficulty is connected with the different contexts where CSP could be addressed but, taking into account some of the last definitions, it could be represented as a snapshot of a firm’s overall social performance at a particular point in time—a summary of the firm’s aggregate social posture [32]. In addition, evaluating the strong relationship with CSR, CSP could also be a firm’s overall social performance at a specific point in time, which can be ascribed to its investments in CSR over time [33,34]. Following the strong debate about CSP, it is simple to comprehend the absence of a univocal perspective on the relationship between Corporate Social Performance (CSP) and Corporate Financial Performance (CFP), too [35,36]. In regards to the two concepts, surely, CSP deserves more attention, having more intangible borders. However, even if there is a lack of a common definition/vision, scholars, considering the growing importance of this topic, are concretely involved in this field of research, aiming to highlight all possible dynamics.

Some authors represented the difficult work to make the contributions provided by previous researches comparable [37,38], as well as the theoretical problems in the empirical analysis [39], since it is difficult, for example, to define a standard metric to measure the corporate social performance [40]. Therefore, the need to redefine this topic in accordance with a common outlook is clear [41] when identifying a wide approved methodology [42]. Recent papers have still tried to update this framework, introducing new points of view as the difference among developed and emerging market firms [43], the results coming from different industry contexts [44] or the mediation role of national institutions [45]. The aim of this work is to further contribute to the exploration of the growing dimensions in terms of attention, social performances, indicating gender representation—that is, the percentage of female directors on boards—and the equal opportunity polices provided in the bank sector. This perspective, related to gender composition on the boards, was recently opened to highlight a specific aspect of CSP [46,47]. This is applied to the Corporate Sustainability theory regarding all firms. Thus, there are four main hypotheses regarding the relationship between Corporate Social Performance (CSP) and Corporate Financial Performance (CFP):

• Negative relationship: in line with what Milton Friedman asserted, “a company that opts to invest in Social Responsibility would produce significantly higher costs than the profits that can be generated” [48]. Consequently, such “wrong” investments would cause a deterioration in the level of economic and financial indicators;
• Positive relationship: according to this hypothesis, there would be a direct and growing relationship between CSP and CFP, even if their causal relationship seemed doubtful. It can be argued that good financial performances generate good social performances: in fact, more profitable companies, when allocating profits, would have more resources for programs focused on social responsibility than less profitable enterprises. On the other hand, investing socially also affects the level of reputation, which indirectly generates a return in terms of cash flow. This is confirmed by the work of Barnett and Salomon [49], which suggests that companies with a higher CSR index perform better than those with a lower score [50];
• Mixed relationship: the connection between CSP and CFP may not always be constant over time and can take the form of a “U” or a “U-inverted” depending on the commitment undertaken. The “U” relationship can be explained by the hypothesis that, for a company, the implementation of a Corporate Social Responsibility program could initially generate an increase in costs compared to revenues (and, therefore, a decrease in terms of economic performance–financial), a trend that reverses in the medium to long term. On the contrary, the U-inverted relationship would suggest the existence of an “excellent” level, beyond which, being socially responsible in the long term would not produce any economic advantage; for instance, Wu and Shen and Farag and Mallin stated the existence of a mixed relationship between CSP and CFP in the financial sector [5,21];
• No relationship: according to the latter hypothesis, CSP and CFP should be assumed as two separate variables that are unrelated to each other and, consequently, corporate social responsibility would have no impact on the profitability of companies [51].

Focusing on the bank industry, there is a need to prioritize social and governance dimensions since, as is commonly known, banks are zero-emission firms themselves, so the environmental disclosures might have an indirect impact on the bank’s performance by enhancing reputation, social engagement, and green credit line access [4,5]. Governance and social measures, such as diversity and inclusion, are reported to have an impact on the financial performance of banks [52,53]. The importance given to the board composition of banks is justified and proven by several studies: De Andres, for example, underlines some features, such as size and independence, compared to boards in non-financial institutions [54]. Another relevant issue in the field deals with the importance of bank governance strategies and their accountability to other stakeholders: it is argued that bank performance trends have a spillover effect on other banks worldwide [55].

The different composition of boards, carrying various peculiar experiences and backgrounds, has increased in importance among scholars [21,55,56,57,58]. In this field, a famous definition by Ingley and Van der Valt describes diversity in boards as the complex of different values, backgrounds, and expertise owned by each member, and this affects the very decision-making process of the board itself [59]. Earlier, Kosnik provided a relevant distinction between board membership and outside board members, arguing that diversity in board members helps to reduce narrow-mindedness on the board’s executive proposals: i.e., the decision making process may result in easing the cross-section of different backgrounds [56].

A relevant aspect concerns gender diversity and the existence of a possible effect of the presence of women within the boards of banks. Research on social psychology stresses the relevance of diversity in regard to the existing differences between male and female directors in better applying their skills in some specific fields: women, for example, are likely to have a legal, HR, or public relations background in respect to their male counterparts, who are more focused on operations and marketing [60].

Research in this field focuses on the concept of “value in diversity” and states that the presence of women on boards shall have a positive effect in representing the various interest of shareholders, enhancing discussion [61] and transparency [62].

The phenomenon of the “glass ceiling” is a crucial issue when speaking about female employment, which, of course, reflects its effects at all levels. Women, therefore, are pushed to invest more effort into their work and to gain more capabilities in order to reach higher positions, as they are supposed to be more industrious and talented [63].

The empirical testing of board diversity when profiling, in particular, gender diversity has been investigated in several studies [21,55,64,65,66]. A comprehensive analysis of the literature operated by Terjesen et al. recognizes more than 400 publications on this subject, showing that the degree of the presence of women as directors and its impact on performance has no clear or univocal results [67]. Some of them have a positive relationship, while others show negative effects, giving an undetermined conclusion of the issue.

The diversity–performance nexus has spare and ambiguous outcomes, and a real postulation of the phenomenon has not occurred. This could be due to the discrepancies in sample sizes, periods of time, and industries, in addition to the econometrics problems—e.g., endogeneity [21]. Most of the studies are empirical and depend on a series of variables that might radically influence the results in each specific case. Indeed, very few studies rely on the empirical results obtained by the analysis of financial firms [21,55], and most of them count on the outcomes of studies made on non-financial firms, proving both positive [68,69] and negative effects [70,71].

Indeed, there is not unanimous consent about the positive or negative effects of board gender diversity on financial performance, which turns out to be impacted by several conditions that are arbitrary and country-specific [72]. Therefore, the first hypothesis can be formulated either as affirmative or null. We opted for an affirmative form:

Hypothesis 1 (H1).

The percentage of female executives generates a positive effect on the single variables of corporate financial performance.

A parallel but similar approach might be followed when we speak about diversity in terms of ethnicity and disability. Inclusion and non-discrimination policies have become a central topic for many countries, so that regulatory frameworks have been introduced by the government in order to guarantee equal opportunities for every demographic category. Beyond the legal and ethical context, the managerial one must also deal with this relevant issue. There is a massive literature review that applies the concept of inclusion, examining, from different aspects, firms and their performance [73]. Most of the analyses focus on corporate non-financial disclosure, since CSR reporting has a strong relevance for what regards the company’s reputation and its corporate social performance [74,75,76,77].

Literature has only recently focused on non-financial reporting over the last fifteen years [78,79], and CSR has become a relevant aspect in firm reputation and strategic asset [64]. Moreover, a few studies have focused on the relation between CSP and CFP as result of voluntary non-financial reporting, subordinating reporting to a positive financial performance [78]. The reason for considering the literature on non-financial reporting is due to the nature of the considered variable, since the equal opportunity policy is a parameter that is voluntarily adopted by firms. Beyond the gender diversity aspect, as already disclosed in the previous paragraph, some studies focus on the composition of boards, considering various demographic groups, including nationality [55] and ethnic groups [80,81]. To the best of our knowledge, there is no specific literature on the effect of the adoption of equal opportunity and non-discrimination policies on corporate financial performance. Erhardt et al. argue of the existence of a positive relationship between cultural diversity (as a complex of observable and non-observable features) and organizational performance in US firms [80]. Therefore, our second hypothesis aims to capture the effect of the adoption of equal opportunity policies voluntarily disclosed by banks on the variables of corporate financial performance, so we formulated it as follows:

Hypothesis 2 (H2).

The equal opportunity policy generates a positive effect on the single variables of corporate financial performance.

3. Materials and Methods

3.1. Sampling and Variable Definition

The methodology adopted to build the analyzed sample can be defined “ESGs-driven”—i.e., driven by the bank’s environmental, social, and governance disclosure score presence provided by Bloomberg LP. In fact, the increasing interest in non-financial disclosure by society, the government, and NGOs led companies to shed light on their sustainable practices. However, even though ESG variables have been adopted for more than a decade, the Bloomberg LP database presents missing data for several banks and years. Nevertheless, this study offers new insights into researching the effects of female boardroom participation and the adoption of the equal opportunity policy on the financial performance of banks engaged in non-financial disclosure. The sample identification followed several passages, and data was collected from different databases, using new variables. Therefore, the sample was unique. Using the BankFocus database [82], a first database was set up by looking for all the banks active in the time period of 2011–2017 that belonged to the European Union geographic region. This first database had 5251 active banks. However, it was almost useless for the purpose of the study, because there were no indicators on the BankFocus database that could express the commitment of the banks in terms of sustainability. To address this shortcoming, these indicators were found on the Bloomberg database, obtaining—after eliminating the banks without ESG data—a database made up of 152 active banks that presented ESG data over the reference as a final output [83].

As mentioned above, the dataset, characterized by such a large time period (2011–2017), was missing some data, which proved it, therefore, to be unbalanced. It was concluded that a shorter time period, ranging from 2015 to 2017, could be more significant for the purposes of the analysis. Considering all these facts, the final database was obtained, which appeared to be composed of 61 active banks belonging to the European Union geographic area (28 countries). The distribution of the sample was totally unbiased and not proportional to the total number of banks in each country, and it was interesting to observe the matter of communication of CSR activities.

At this point, some considerations of the sample size were necessary. The sample had the maximum size available for the databases from which the data were extracted [82,83]. In addition, there were two factors that made the sample homogeneous: first, although the European Union geographic area did not have a banking union, it certainly had common rules and exchanges; second, in a fragmented dataset, the two largest shares (i.e., Italy and the United Kingdom) did not exceed 10%–15% of the total. Therefore, they were to be considered low shares. In addition, Italy and the United Kingdom had diametrically opposed behaviours, equilibrating their effects. Lastly, statistical tests were carried out with dummy variables for both countries: the dummy was not significant.

The variables present in the database could be divided into three main categories:

• Corporate Financial Performance variables (i.e., return on average assets (ROAA), return on average equity (ROAE), ln Market Capitalization, Tobin’s Q, and ln Net Interest Income), taken as dependent variables;
• Corporate Social Performance variables (percentage of female executives and the equal opportunity policy), taken as independent variables;
• Control variables (e.g., Leverage, Net Interest Margin, Loan Dept, Cost to Income ratio, Coverage, and ln Total Assets).

Dependent variables were described as follows:

The ROAA (acronym for Return on Average Assets) is an indicator to assess the profitability of a company’s assets and is used by banks and financial institutions as a tool to estimate financial performance [5,51,53,71,84,85,86,87,88,89]. ROAA indicates the efficiency of a company in using its resources and is very useful for analyzing similar companies belonging to the same sector. This accounting-based performance measure is able to record the ability of banks to generate income based on the total capital employed: that is, returns generated from the assets financed by the banks [84,88].

ROAE (acronym for Return on Average Equity), on the other hand, is a profitability indicator aimed at measuring the performance of a company by evaluating the profit obtained on the basis of the money invested in the capital. A high ROAE identifies a favourable situation, in which the company generates more income for each unit of equity [5,51,53,71,84,88].

Market Capitalization represents the assessment made by the market on the value of a company. The capitalization is estimated by multiplying the number of existing shares by the market price of a specific trading day (Schroders). The variable was used in its logarithmic value [53].

For testing the market value of the firm, we used Tobin’s Q, which is intended as the ratio between current market value and the rate of replacement of the value of the firm [53,72,86,87,90,91,92,93]. The market value of the firm is the sum of common shareholders’ investment in a company, the stocks, and the sum of long and short-term debt. The replacement value of firm assets is the sum of gross property and short-term assets [2]. Tobin’s Q reflects the market’s expectations for future performances rather than accounting-based measures; thus, it represents a good proxy for the firm’s competitive advantages [69,94,95].

The Net Interest Income is calculated as the difference between the revenues generated by the company assets and the charges related to the liabilities. Based on a bank’s specific assets and liabilities (i.e., whether at a fixed or variable rate), the Net Interest Income may be more or less sensitive to changes in interest rates [5,88]. The variable was used in its logarithmic value.

The independent variables were extracted from the Bloomberg database, and were described as follows:

The Percentage of Female Executives (field ID: ES291, mnemonic: PERCENTAGE_OF_FEMALE_EXECUTIVES) provides the number of female managers as a percentage of the total managers [53,69,72,85,87,93], starting from the end of the tax year where available, or, otherwise, to the last financial year to date. Executives are defined by the company or the individuals who make up the executive committee or management committee/board or equivalent. The field is part of the group of ESG fields (environmental, social, or governance).

The Equal Opportunity Policy (field ID: ES058, mnemonic: EQUAL_OPPORTUNITY_POLICY) variable relates to equal treatment legislation and indicates whether the company has actively committed itself to guarantee the non-discrimination of any demographic group. This may be in the form of an equal opportunity policy as described by the company. The field is part of the group of ESG fields (environmental, social, or governance). Being a dichotomous dummy variable, the field reported ‘1’ for Yes or ‘0’ for No [83]. As far as we know, there is no use of this variable in the current literature.

The control variables referred to the financial characteristics of the banks:

Leverage refers to the ratio between the book value of the equity and total liabilities [53,84], detecting the capital adequacy of the bank [5,96].

Net Interest Margin (NIM) refers to the ratio of net interest income to earning assets, which is the sum of total investment earning interest or dividends and net loans [53,71,97], expressed as a percentage. The net interest margin reflects the business the bank engages in. For example, higher margins are associated with banks with more lending operations instead of those that engage in advising and mediating. Hence, this variable is not reflecting performance, but merely revealing the source of the bank’s revenues [97].

The Total Asset variable identifies the size of the company and represents a determinant of social and financial performance [98]. The variable is expressed in its logarithmic value (ln Total Asset) [5,53,84,85,86].

Further control variables were the ones proposed by Wu and Shen among the bank’s main characteristics [5]: Loan Dept—that is, the ratio between net loans and deposits and short-term funding [86,99]; Cost to Income ratio, expressed as a percentage of the ratio of total operating expenses to operating revenues [51]; and, lastly, Coverage, calculated as the ratio between loan loss reserves to gross loans [53,84].

All the variables are resumed as follows in

Table 1. Variable description (own elaboration).

Variables	Description	Source
DEPENDENT VARIABLES
CFP Variables
ROAA	Return on Average Assets %	BankFocus
	(Profit or loss after tax/Total assets) × 100
ROAE	Return on Average Equity %	BankFocus
	(Profit or loss after tax/Total equity) × 100
ln Market Capitalization	log (Market Capitalization)	BankFocus *
Tobin’s Q	(Market capitalization/Total assets)	BankFocus
ln Net Interest Income (expense)	log (Net Interest income)	BankFocus *
	(Total interest income—Total interest expense)
INDEPENDENT VARIABLES
CSP Variables
Percentage of female executives	Number of female directors, as percentage of the total board members	Bloomberg
Equal opportunity policy	States if firms are involved in equal opportunity policies, such as inclusion and non-discrimination	Bloomberg
CONTROL VARIABLES
Leverage	(Equity/Liabilities)	BankFocus
Net Interest Margin (NIM) %	(Net interest income (expense)/Total earning assets) × 100	BankFocus
Loan Dept	(Net Loans/Deposits & Short-Term Funding)	BankFocus *
Cost to Income (efficiency) ratio	(Total operating expenses/Operating revenues) × 100	BankFocus
Coverage	(Loan loss reserves/Gross Loans)	BankFocus *
ln Total Asset	log (Total Assets)	BankFocus *

* Own elaboration from BankFocus data.

.

3.2. Econometric Model

Once we defined the considered variables, we built our econometric models. Even if the study included a timeline of three years, we considered the average value of each variable, being the time period short enough not to register sensible variations during the period. The model, therefore, has been identified as a cross-section analysis, split into five different regression analyses per each hypothesis, resulting in ten different analyses. The model adopted is validated by previous work [53,86,100]. A linear regression model was used to test our hypotheses with some modifications (i.e., introducing new variables and different combinations between the independent and control ones).

The first hypothesis ought to be studied according to the following econometric models:

• ROAA_i = β₀ + β₁LEVERAGE_i + β₂ NET INTEREST MARGIN_i + β₃ LOAN DEPT_i + β₄ COST TO INCOME_i + β₅COVERAGE_i + β₆ ln TOTAL ASSET_i+ β₇ Percentage of Female Executives_i + ε_i
• ROAE_i = β₀ + β₁LEVERAGE_i + β₂ NET INTEREST MARGIN_i + β₃ LOAN DEPT_i + β₄ COST TO INCOME_i + β₅COVERAGE_i + β₆ ln TOTAL ASSET_i + β₇ Percentage of Female Executives_i + ε_i
• ln MarketCapitalisation_i = β₀ + β₁LEVERAGE_i + β₂ NET INTEREST MARGIN_i + β₃ LOAN DEPT_i + β₄ COST TO INCOME_i + β₅COVERAGE_i+ β₆ ln TOTAL ASSET_i + β₇ Percentage of Female Executives_i + ε_i
• Tobin’s Q_i = β₀ + β₁LEVERAGE_i + β₂ NET INTEREST MARGIN_i + β₃ LOAN DEPT_i + β₄ COST TO INCOME_i + β₅COVERAGE_i + β₆ ln TOTAL ASSET_i + β₇ Percentage of Female Executives_i + ε_i
• ln Net Interest Income_i = β₀ + β₁LEVERAGE_i + β₂ NET INTEREST MARGIN_i + β₃ LOAN DEPT_i + β₄ COST TO INCOME_i + β₅COVERAGE_i + β₆ ln TOTAL ASSET_i + β₇ Percentage of Female Executives_i + ε_i

So as the following ones, built in order to verify Hypothesis 2:

• ROAA_i = β₀ + β₁ LEVERAGE_i + β₂ NET INTEREST MARGIN_i + β₃ LOAN DEPT_i + β₄ COST TO INCOME_i + β₅COVERAGE_i + β₆ ln TOTAL ASSET_i+ β₇ Equal Opportunity Policy_i + ε_i
• ROAE_i = β₀ + β₁LEVERAGE_i + β₂ NET INTEREST MARGIN_i + β₃ LOAN DEPT_i + β₄ COST TO INCOME_i + β₅COVERAGE_i + β₆ ln TOTAL ASSET_i + β₇ Equal Opportunity Policy_i + ε_i
• ln MarketCapitalisation_i = β₀ + β₁LEVERAGE_i + β₂ NET INTEREST MARGIN_i + β₃ LOAN DEPT_i + β₄ COST TO INCOME_i + β₅COVERAGE_i+ β₆ ln TOTAL ASSET_i + β₇ Equal Opportunity Policy_i + ε_i
• Tobin’s Q_i = β₀ + β₁LEVERAGE_i + β₂ NET INTEREST MARGIN_i + β₃ LOAN DEPT_i + β₄ COST TO INCOME_i + β₅COVERAGE_i + β₆ ln TOTAL ASSET_i + β₇ Equal Opportunity Policy_i + ε_i
• ln Net Interest Income_i = β₀ + β₁LEVERAGE_i + β₂ NET INTEREST MARGIN_i + β₃ LOAN DEPT_i + β₄ COST TO INCOME_i + β₅COVERAGE_i + β₆ ln TOTAL ASSET_i + β₇ Equal Opportunity Policy_i + ε_i

3.3. Correlation Matrix

Table A1. Correlation matrix (own elaboration).

	ROAA	ROAE	Ln NII	Ln Total Assets	NIM	Leverage	Ln MktCapitalisation	Tobin’s q	Coverage	Percentage of Female Executives	Equal Opportunity Policy
ROAA	1
ROAE	0.777	1
Ln NII	−0.263	−0.302	1
Ln Total Assets	−0.445	-0.310	0.911	1
NIM	0.597	0.127	−0.038	−0.321	1
Leverage	0.512	0.004	−0.184	−0.494	0.761	1
Ln MktCapitalization	−0.036	0.033	0.836	0.864	−0.111	−0.281	1
Tobin’s q	0.774	0.338	−0.295	−0.494	0.884	0.749	−0.162	1
Coverage	−0.412	−0.593	0.058	−0.076	0.190	0.399	−0.305	−0.010	1
Percentage of Female Executives	0.044	0.253	−0.163	−0.131	−0.113	−0.194	−0.097	−0.110	−0.312	1
Equal Opportunity Policy	0.036	0.143	0.173	0.193	0.004	−0.105	0.160	−0.004	−0.002	−0.077	1

(Appendix A) illustrates the correlation matrix of the variables under study. Overall, the analysis highlighted good direct linear correlations between independent social performance variables and dependent variables in Market Capitalization and Net Interest Income. Furthermore, the independent variable Percentage of Female Executives had a medium/low correlation with the dependent variable ROAE. In detail:

• The independent variable Percentage of Female Executives, on the one hand, was the only one with a direct, albeit modest (0.25) linear correlation with the dependent variable ROAE.
• The independent variable Equity Opportunity Policy, on the other hand, was characterized by small correlations, which were not significant for the purposes of the analysis.

Considering the other dependent variables, there were no relevant significant values.

4. Results

Table 2. Hypothesis 1 (H1) test (own elaboration).

	ROAA	ROAE	ln Market Capitalization	Tobin’s Q	ln Net Interest Income
Intercept	2.9760 ***	61.5837 ***	−6.1653 ***	0.4262 ***	−6.1960 ***
	(0.7370)	(11.1582)	(0.8540)	(0.1164)	(0.8842)
Percentage of Female	−0.0074 *	−0.0116	−0.0025	−0.0013 **	0.0059
Executives	(0.0041)	(0.0619)	(0.0047)	(0.0006)	(0.0049)
Leverage	0.0728 ***	−0.3016	0.0971 ***	0.0068 **	0.0976 ***
	(0.0203)	(0.3074)	(0.0235)	(0.0032)	(0.0244)
Net Interest Margin (NIM)	0.1322 ***	1.5963 ***	0.0641 **	0.0288 ***	0.0439
	(0.0234)	(0.3538)	(0.0271)	(0.0037)	(0.0280)
Loan Dept	−0.0038 ***	−0.0698 ***	−0.0034 ***	−0.0003 *	−0.0004
	(0.0011)	(0.0159)	(0.0012)	(0.0002)	(0.0013)
Cost to Income	−0.0186 ***	−0.3548 ***	−0.0119 ***	0.0002	−0.0102 **
	(0.0035)	(0.0531)	(0.0041)	(0.0006)	(0.0042)
Coverage	−0.1074 ***	−1.1165 ***	−0.0869 ***	−0.0078 ***	0.0088
	(0.0092)	(0.1390)	(0.0106)	(0.0015)	(0.0110)
ln Total Assets	−0.0678 *	−1.1635 **	0.8395 ***	−0.0208 ***	1.0844 ***
	(0.0346)	(0.5240)	(0.0401)	(0.0055)	(0.0415)
Observ.	61	61	61	61	61
R-square	0.8660	0.7528	0.9140	0.8950	0.9376
Adj. R-square	0.8483	0.7202	0.9027	0.8811	0.9293

Significance: * p < 0.10; ** p < 0.05; *** p < 0.01; standard error value is in brackets.

reports the results relating to Hypothesis 1, which investigated the possible existence of a positive relationship between the independent variable Percentage of Female Executives and the dependent variables relating to financial performance.

The output of the regressions carried out on the sample identified a negative and significant relationship between the percentage of women holding top positions and two variables of financial performance: ROAA (characterized by low significance with p-value less than 10% and with β = −0.0074) and Tobin’s Q (characterized by an average significance with the p-value less than 5% and with β = −0.0013). No further significant relationships emerged with the other dependent variables.

These results showed that H1 was not confirmed and differed from other contributions in literature. In fact, Carter, Simkins, and Simpson (2003) documented a positive relationship between the gender and ethnic diversity of the board and corporate performance, as proxied by Tobin’s Q [85]. In addition, other studies validate this positive relationship [69,84,93,101], finding evidence that is consistent with the idea that the market values workplace diversity. However, the model results did not allow us to foster the major literature in the field, but made us reflect on the reasons behind it. In fact, some explanations of the negative influence of females on ROAA and Tobin’s Q may be down to differences in country and organizational culture, family dynamics (that might constrain the board’s active participation), gender pay gaps, obstacles in hiring or reaching top management charge for women, etc. These are some suggestions for further investigation.

Moreover,

Table 3. Hypothesis 2 (H2) test (own elaboration).

	ROAA	ROAE	ln Market Capitalization	Tobin’s Q	ln Net Interest Income
Intercept	2.1768 ***	53.9355 ***	−6.2132 ***	0.3058 **	−5.7088 ***
	(0.7290)	(10.4717)	(0.8402)	(0.1176)	(0.8787)
Equal Opportunity Policy	0.4687	9.4735 **	−0.1397	0.0521	−0.1744
	(0.2895)	(4.1591)	(0.3337)	(0.0467)	(0.3490)
Leverage	0.0825 ***	−0.2162	0.0980 ***	0.0083 **	0.0914 ***
	(0.0202)	(0.2915)	(0.0234)	(0.0033)	(0.0245)
Net Interest Margin (NIM)	0.1251 ***	1.4877 ***	0.0651 **	0.0279 ***	0.0474
	(0.0237)	(0.3406)	(0.0273)	(0.0038)	(0.0286)
Loan Dept	−0.0036 ***	−0.0673 ***	−0.0035 ***	−0.0003	−0.0005
	(0.0011)	(0.0152)	(0.0012)	(0.0002)	(0.0013)
Cost to Income	−0.0174 ***	−0.3417 ***	−0.0119 ***	0.0004	−0.0109 **
	(0.0035)	(0.0508)	(0.0040)	(0.0006)	(0.0043)
Coverage	−0.1045 ***	−1.1246 ***	−0.0855 ***	−0.0073 ***	0.0062
	(0.0090)	(0.1297)	(0.0104)	(0.0015)	(0.0109)
ln Total Assets	−0.0635 *	−1.3281 ***	0.8466 ***	−0.0193 ***	1.0772 ***
	(0.0345)	(0.4955)	(0.0398)	(0.0056)	(0.0416)
Observ.	61	61	61	61	61
R-square	0.8643	0.7747	0.9139	0.8890	0.9362
Adj. R-square	0.8464	0.7450	0.9025	0.8743	0.9277

Significance: * p < 0.10; ** p < 0.05; *** p < 0.01; standard error value is in brackets.

reports the results relating to the second hypothesis, in which we investigated the possible existence of a positive relationship between the independent variable Equal Opportunity Policy and the dependent variables relating to financial performance. The use of the dichotomous dummy variable, relating to the adoption of equal opportunity policies, gave a positive outcome for the dependent variable ROAE (characterized by a high significance with a p-value lower than 1% and with β = 9.4735). Therefore, equal opportunity policies only influence profitability on invested capital.

According to the results that were previously shown, H2 was confirmed. To the best of our knowledge, to date, no contribution in literature has used this variable, so there are no previous works capable of validating our study. This makes our results so unique that they will certainly be the subject of future research.

5. Discussion

The debate on diversity has dramatically risen in the last two decades, focusing on both institutional and entrepreneurial concern on social issues. Some disruptive events, such as the financial crisis, have contributed to the boost of policies and strategic decisions regarding these aspects.

This paper aimed to investigate the relationship between gender diversity and financial performance, and the influence of the possible existence of equal opportunity policies within banking institutions in a relatively recent period. The choice, besides the necessity to compose a balanced dataset, was strategic to observe the differences and possible comparisons with previous periods that were temporally closer to the financial crisis. This choice gave the opportunity to settle the consequences of social policies adopted after 2007.

As the analyses conducted show, the impact of the percentage of female executives on boards had a slightly negative effect on ROAA and the Tobin’s Q. These were the only two variables in which the relationship was significant. It did not have any significant relationship with the others. This result is consistent with the analysis of Farag and Mallin, who observed a decrease in the financial performance of banks when the composition of boards started to have a diffused fragmentation [21]. This is justified as a lack of efficiency in decisional processes, which, of course, condition the pace of the firm (financial or non-financial), impacting negatively on the financial performance. This is particularly evident in the relationship with Tobin’s Q, which is a measure of the replacement of assets. A decrease or, worse, a lack in efficiency obviously impacts the rate of replacement and the market value of the firm. This is even more evident when dealing with banking institutions, in which the replacement of financial assets happens at a faster pace than any other firm.

The second step of the analysis revealed a very positive relationship between the equal opportunity policy variable and the ROAE. This was a very interesting result, which, of course, had a twofold consideration: on one hand, we observed internally a possible positive effect on operations, as the productivity of employees and their positive effect on process in terms of cross-section decisional processes and strategy composition increased; on the other hand, we observed the possible improvement of the bank’s reputation in the market, increasing their return on equity. This is a novelty in literature, according to the extant literature, which qualifies as a relevant contribution to the present study.

The non-significance of the other relationships with the two considered variables gives an interesting perspective: the indicators used in the analyses are probably not the ones influenced by the social dimension of sustainability in financial firms. There are, indeed, numerous indicators that contribute to the debate of non-financial disclosure in all the production sectors in a precious way.

6. Conclusions

The aim of the study was to find a relationship between CSP—namely, social and governance sustainability components and CFP in the banking sector. According to the results obtained, H1 has been rejected, as negative significant relationships were found between the percentage of females on boards and ROAA and Tobin’s Q, while H2 has been confirmed as a significant positive relationship between the adoption of equal opportunity policies and the ROAE was found. The research contributed to the study of sustainable behaviour in the banking sector, aiming for the pursuit of the SDGs of the United Nations, with a specific focus on the social and governance disclosure, which is often underestimated in comparison with the conventional aspect of the TBL scheme. Social sustainability has numerous implications both in the firm’s theory and governmental political action. The most discussed topic regards the popular “glass ceiling,” a wage gap between men and women that, nowadays, must be overcome. Some scholars proved the need for women to make more effort to reach higher positions, so a further step in policy ought to be made in this way, allowing equal salaries between sexes. The impact on the financial performance is crucial for the firm’s activity, both on decisional and operative levels. The values collected show, first of all, that many institutions are still far from being involved in equal opportunity policies, so an effort from governments in boosting the adoption of social policies is still needed. Based on the results, our study has obtained suggestive results, but a lot could still be done.

Of course, the study has some limitations that might be overcome. First, the study, for lack of data, ought to be completed on a larger sample by selecting other variables from other databases. ESG disclosure is, actually, not a very spread practice, yet, with regard to the banking sector, as observed through the sampling strategy. This, of course, implies different possible outcomes. The sampling strategy may be conducted notwithstanding the existence of the interest of banks in ESG reporting activities, which is itself a relevant deduction. Contrarily, we based our sampling starting from the Bloomberg assessment of ESG disclosure in financial firms. Another limitation is given by the short time interval, which is also linked to the lack of data. Future studies might consider the opportunity to enlarge the sample gradually on both the population and time interval aspects, as the information disclosure on the sustainability aspect improves itself as a good practice on the firm side. Possible future analyses may consider the time effect on the variables.