Perception of Corporate Governance Factors in Mitigating Financial Statement Fraud in Emerging Markets: Jordan Experience

Abstract

This study investigates the influence of corporate governance on reducing financial statement fraud (FSF) in Jordanian service and industrial companies listed on the Amman Stock Exchange from 2018 to 2022. To achieve this, the study employed the Beneish M-score model to assess the likelihood of FSF and logistic regression to examine the influence of corporate governance structure on fraud mitigation. The study identified 13 independent variables, including board size, board director’s independence, board director’s compensation, non-duality of CEO and chairman positions, board diversity, audit committee size, audit committee accounting background, number of annual audit committee meetings, external audit fees, board family business, the presence of women on the board of directors, firm size, and market listing on FSF. The study included 74 companies from both sectors—33 from the industrial sector and 41 from the service sector. Primary data was collected from financial statements and other information published in annual reports between 2018 and 2022. The results of the study revealed a total of 295 cases of fraud during the examined period. Out of the 59 companies analyzed, 21.4% demonstrated a low probability of fraud, while the remaining 78.6% (232 observations) showed a high probability of fraud. The results indicate that the following corporate governance factors significantly impact the mitigation of financial statement fraud (FSF): independent board directors, board diversity, audit committee accounting backgrounds, the number of audit committee meetings, family business involvement on the board, and firm characteristics. The study provides several recommendations, highlighting the importance for companies to diversify their boards of directors by incorporating different perspectives and experiences.

1. Introduction

Interest in corporate governance has surged among regional and international institutions, largely due to the initiatives of the World Bank and the Organization for Economic Cooperation and Development (OECD). In 1999, the OECD introduced corporate governance principles in response to the failures of several high-profile international companies and a wave of financial scandals (OECD, 2004). This growing concern about corruption in financial, administrative, and accounting practices has prompted regional and international bodies to acknowledge that effective corporate governance helps to prevent such issues, fosters economic development, and enhances social welfare (Tourani-Rad & Ingely, 2010).

Corporate governance is a fundamental pillar for economic entities, particularly as many countries adopt capitalist economies that rely on private enterprises. Effective governance promotes transparency and accountability in financial reporting, establishing frameworks that protect the rights of shareholders and other stakeholders (Aris et al., 2015).

The interdependence of public and private sector entities—including shareholders, lenders, insurance companies, and tax authorities—exerts a significant demand for transparency regarding a company’s financial health. The obligation to disclose financial information in corporate reports underscores its critical importance (Alzoubi & Selamat, 2012). Thus, organizations are becoming more careful in providing financial reports that ensure reliability and credibility to all stakeholders. Since the higher level of trust in corporate activity will assist in attracting investors and partners, and enhance the competitive advantage that facilitates meeting the corporate objectives. Effective governance is also crucial in mitigating conflicts of interest and reconciling divergent interests of various internal and external stakeholders with the organization overarching goals (Arshad et al., 2015).

Therefore, evaluating the effectiveness of governance is vital for recognizing the mechanisms that determine the roles and responsibilities of executive directors (Alzoubi & Selamat, 2012; Shanikat & Abbadi, 2011). These mechanisms ensure the autonomy of the audit committee and internal and external auditors. Hence, establishing a robust risk management framework and improving the disclosure and transparency of financial reports. Moreover, it influences the financial reports user’s decision making and strengthens the link between corporate governance principles and the reliability of financial statements (Hermalin & Weisbach, 2012).

In Jordan, the majority of previous studies have focused on a single cross-sectional period, following the short period since the adoption and application of the code of corporate governance in 2009 (Hamdan et al., 2012). Al-Hiyari (2017) argued that sufficient time is required to investigate the effectiveness and impact of corporate governance in reducing financial statement fraud (FSF).

This study aims to examine the influence of corporate governance structures on the mitigation of financial statement fraud. The primary contribution of this research is the formulation of a logistic regression model designed to elucidate the relationship between corporate governance variables, a relationship that has not been thoroughly documented in the context of Jordan in previous studies. The research is conducted on companies listed on the Amman Stock Exchange.

2. Literature Review and Previous Studies

2.1. Corporate Governance

Corporate governance is considered an extensive framework that includes a set of regulations and procedures that aims to assist the organization in maximizing long-term value and profitability while balancing the interests of shareholders and stakeholders (Omar et al., 2014). Razali and Arshad (2014) defined corporate governance as a system of rules and marketplace traditions that govern decision-making processes, particularly in listed companies. In the last few decades, corporate governance has become a vital function for national and international companies, particularly in the wake of events surrounding financial crises that adversely affected the global economy. Such a scenario has reinforced the necessity of good governance practices (R. Abdullah et al., 2018).

Governance systems aim to mitigate the potential misuse of administrative authority that may jeopardize shareholder interests. Arum et al. (2020) pointed out that the objectives of governance include enhancing board performance, strengthening internal controls, supervising the implementation of strategic initiatives, and clearly delineating the roles and responsibilities of shareholders, the board of directors, executive management, and stakeholders. Furthermore, these systems underscore the critical importance of transparency and disclosure (Rostami & Rezaei, 2022).

In conclusion, corporate governance encompasses the rules and mechanisms that direct a corporation’s leadership and management. It regulates the relationships among the board of directors, executive management, shareholders, and stakeholders. By building a holistic framework, corporate governance facilitates a transparent and credible decision-making process that protects the rights of shareholders and stakeholders, ultimately promoting fairness, competition, and transparency in the marketplace.

2.2. Factors Influencing Corporate Governance

The corporate governance framework delineates the responsibilities of the board of directors and senior management. Numerous factors influence the efficacy of governance, including the board’s size, independence, and diversity, as well as the compensation structures for board members. Other important factors include defining the roles of the CEO and the chairman, the frequency and scope of audit committee meetings, and the composition of committee members. Additionally, factors such as market listing status, total assets, and the representation of women on the board significantly influence the development of the governance framework.

• Size of Board Directors 

Prior research revealed that company’s board size significantly influences its operations and overall effectiveness (A. Lotfi et al., 2022; Al-Juwaisim & Amer, 2020; Atta, 2019; Al-Tahan & Nakhal, 2020). Nevertheless, there are two contrasting perspectives regarding this issue. The first argument revolves around the large boards working more effectively in fulfilling their responsibilities. According to Al-Juwaisim and Amer (2020), large boards increase task distribution and reduce pressure in work. Similarly, Atta (2019) highlighted that larger boards ensure stronger connections with the external environment and greater expertise. Al-Tahan and Nakhal (2020) asserted that larger boards facilitate greater exchanges of experience and ideas, ultimately leading to improved company performance. On the other hand, the other argument suggested that smaller boards are better in their role. Meanwhile, larger boards experience a set of challenges, of which the most important is ineffective communication between members, raising the need for increased participation (Seifzadeh et al., 2022). Manry et al. (2023) emphasized that use of opportunistic behaviuer such as earnings management is more widespread in larger company boards. However, in firms with small boards, where there is effective communication, timely, strategic decision making is facilitated.

• Board Independence 

Independent board members often possess a better capability to observe the performance of a company than executive directors. They bring rich experience, distinctive knowledge, and intelligence difficult to obtain from other resources, thus becoming invaluable advice in strategic decision making (Manry et al., 2023). Therefore, organizations that have independent board members who have affiliations with other firms are more likely to demonstrate superior operating performance relative to their peers who lack such privilege (Abu Khadra & Delen, 2020).

According to various theories such as agency, resource dependence, and stakeholder theories, the independence of board directors plays a vital role in enhancing a company’s performance. Stakeholder theory emphasizes that independent directors prioritize the interests of all stakeholders. They understand that their responsibilities go beyond merely serving shareholders; they also address the needs and expectations of all parties involved with the company (Panda & Leepsa, 2017). Girau et al. (2022) demonstrated that boards with a higher proportion of independent members exhibit improved oversight functions, thereby enhancing the company’s performance and the quality of its accounting profits.

• Board Compensation 

Companies evaluate compensation based on employees’ experience, qualifications, and job profiles, providing them with diverse and distinctive compensation that is in line with their role in developing the company’s performance, enhancing its brand reputation, and achieving the set goals (Bravo et al., 2015). This type of compensation represents an important incentive for members of the company’s senior management, starting with the Chairman of the Board of Directors, passing through the members of the Board of Directors, and ending with the CEOs, as it keeps them with a high degree of interest in everything that is in the interest of the company and the rest of the interested parties (Abu Khadra & Delen, 2020).

• Non-Duality of CEO and Chairman Positions 

Duality refers to a situation where a single individual serves as both the Chief Executive Officer (CEO) and the Chairman of the Board of Directors. There are two main perspectives on the relationship between duality and organizational performance. Agency theory argues that separating these roles is essential for maintaining the independence and effectiveness of the board of directors (Freihat et al., 2019). In contrast, stewardship theory suggests that a unified leadership structure can improve efficiency by fostering better coordination and effective leadership, which, in turn, addresses strategic challenges more effectively (Ahmadi & Bouri, 2017). Duality may enhance performance by centralizing power in one individual, reducing uncertainty about who is making decisions (Bose, 2009). Consolidating power within the Board of Directors can undermine the interests of various stakeholders (Demirbas & Yukhanaev, 2011). When one individual serves as both CEO and Chairman, they can manipulate the information presented to board members, framing it in a way that aligns with their objectives. Bravo et al. (2015) and Nasir et al. (2019) indicated that the dual role may reduce the effectiveness of the board of directors, encourage earnings management practices, and weaken adherence to conservative accounting policies, which leads to harm to the organization’s performance.

Bravo et al. (2015) and Nasir et al. (2019) indicated that the dual role may reduce the effectiveness of the board of directors, encourage earnings management practices, and weaken adherence to conservative accounting policies, which leads to harm being caused to the organization’s performance.

• Board Background Diversity 

The diversity within the board of directors is an important aspect in order to strengthen corporate governance and obtain a broader range of perspectives into decision making. This diversity may include professionals with different backgrounds, skills, and experiences. Consequently, these elements collectively will allow gaining a deeper understanding of the business environment and more actively identifying potential risks and opportunities. A diversified board of directors improves strategic planning, and ultimately contributes to better corporate performance (Demirbas & Yukhanaev, 2011; Musa et al., 2020; Xie et al., 2020).

• Audit Committee Size

The composition of the audit committee is based on the size of the board of directors and the specific characteristics of the company. W. N. Abdullah and Said (2018) pointed out the significance of the influence of the audit committee’s size on its effectiveness and indicated that an appropriately sized committee enhances oversight and improves the quality of corporate governance disclosures, thereby positively impacting financial reporting. Therefore, it is important to balance the number of audit committee members with their expertise and qualifications while also considering specific tasks, which may vary across companies.

• Audit Committee with Accounting Background 

A background in finance and accounting is imperative for members of corporate audit committees, as it significantly enhances their effectiveness and performance (Al-Madhoun et al., 2021). Such qualifications enable committee members to critically evaluate business activities and identify organizational risks, thereby facilitating the assessment of the alignment between accounting principles and the economic realities of financial transactions, which in turn improves the transparency of accounting reports. Moreover, robust accounting skills contribute to more effective oversight when compared to non-accounting financial experts serving on audit committees (Madi, 2022).

• External Audit Fees 

The compensation received by external auditors is a key indicator of their independence and the quality of their services. According to Agrawal and Cooper (2016), determining external audit fees is complex due to the numerous factors influencing these estimations. Auditors aim to provide an unbiased opinion, ensuring the accuracy and integrity of financial statements through regular examination procedures.

• Market Listing (First and Second Market) 

In the first market, firms issue and sell new securities to raise capital, whereas in the second market, existing securities are exchanged among investors, commonly referred to as the stock market. Globally, numerous financial markets are increasingly mandating that companies listed on stock exchanges comply with governance regulations as a prerequisite for listing. These regulations are being implemented worldwide, with the Capital Market Authority finalizing governance frameworks that provide companies with the necessary time to align their operations with established corporate governance standards (Chang et al., 2014).

Companies working in various sectors in Jordan often seek to list their shares and securities on the Amman Stock Exchange (ASE). However, there are certain procedures set by the Jordan Securities Commission (JSC) they need to meet (JSC, 2017). Moreover, companies must prepare a governance report in accordance with JSC requirements and must fulfill specific governance requirements (Ahmad et al., 2012).

Corporate governance, including disclosure, transparency, and the protection of shareholders’ rights, is recognized as a key mechanism for enhancing the performance and efficiency of financial markets. It maximizes firm value and helps make these markets drivers of economic growth while aiming to reduce corporate failures (French et al., 2023). A study of capital markets, particularly in emerging markets, indicates that these markets uniformly implement governance systems for their listed companies, which is essential for listing on these exchanges (Chakraborty et al., 2019). However, many emerging markets fail to enforce such systems due to various factors, including the absence of essential mechanisms for effective implementation. These deficiencies significantly contribute to the inefficiency of capital markets in emerging markets, hindering their ability to achieve even minimal levels of efficiency (French et al., 2023).

• Firm Size (Total Assets) 

Firm size can be categorized in several ways, such as total assets, logarithmic size, and market value of shares (Ayuba et al., 2019). Large companies have to prepare their audited financial statements more quickly (Cassar, 2009). The speedy reporting process is often due to their access to diverse information sources and effective internal control systems, which reduces errors in financial statement preparation and facilitates the audit process. In addition, larger companies typically have more investors and are required to prepare their audited financial statements more quickly than their smaller counterparts (Chand et al., 2015).

• Family Business Board 

Family business boards share governance responsibilities with boards of directors in other organizations, but they encounter unique challenges that complicate their roles (Manry et al., 2023). Board structures can be customized to fit ownership dynamics and organizational culture. Bravo et al. (2015) identify two main types of boards: the unified board system, which combines both executives and non-executives into a single board, and the dual board system, which separates the executive board from the advisory board (Bravo et al., 2015). Dual board model can be particularly beneficial for family boards, especially when some members may lack the necessary skills to lead or influence company decisions. Family businesses play a vital role in the global economy, serving as an important avenue for enterprise emergence and growth.

• The Presence of Women on the Board of Directors 

Evidence indicates that women’s involvement in decision-making processes is positively correlated with corporate financial performance (Bravo et al., 2015). Boards with female members tend to prioritize non-financial performance indicators, such as customer satisfaction and corporate social responsibility, and are more effective in overseeing board accountability, thereby enhancing corporate governance (Manry et al., 2023). There is increasing interest in improving the representation of women on boards. In 2003, Norway enacted legislation mandating gender balance in board membership, a measure subsequently emulated by several EU countries, including Sweden, Germany, Italy, France, and Spain, as well as nations such as China, India, and various countries in the Middle East (Xie et al., 2020).

• Audit Committee Meetings 

The frequency of audit committee meetings significantly influences its effectiveness and ability to fulfill its responsibilities. The committee determines the meeting frequency based on the company’s circumstances (Demirbas & Yukhanaev, 2011). Infrequent meetings may hinder oversight, making it difficult to detect fraud or accounting irregularities (Agrawal & Cooper, 2016). Committee members must dedicate sufficient time to auditing issues relevant to the company (Shanikat et al., 2014). Therefore, meetings should occur at least four times a year, as audit committee members are responsible for monitoring risk management policies, including risks from the company’s activities (Abutaber et al., 2021).

2.3. Financial Statement Fraud

FSF involves the deliberate manipulation of financial reports to misrepresent an organization’s financial status. This may include overstating revenues, understating expenses, and concealing liabilities. FSF can be perpetrated by company executives, accountants, or auditors (Apriliana & Agustina, 2017). Motivations for FSF include the desire to meet earnings expectations, as organizations may manipulate their financial statements to present higher profits than earned to align with analysts’ forecasts (A. Lotfi et al., 2022). Another motivation is to secure financing; companies may distort their financial statements to depict a more favorable financial position to obtain loans or other forms of financing. Additionally, some organizations may engage in FSF to obscure fraudulent activities (Endah et al., 2020).

In Jordan, the ACFE (2024) report identified seven instances of corporate fraud. This study aims to deepen the understanding of fraud, particularly in the context of the Amman Stock Exchange (ASE), an emerging market vulnerable to financial misconduct. Al-Natsheh and Al-Okdeh (2020), Al-Daoud et al. (2023), and Bader et al. (2024) examined fraudulent practices among companies listed on the ASE, which often utilize deceptive techniques such as income smoothing, earnings management, and creative accounting. These studies focus on the motivations behind fraudulent behaviors and support efforts to effectively combat and reduce these issues.

2.4. Corporate Governance Development in Jordan

In the context of Jordan, global crises have prompted stakeholders to reassess the credibility of financial reporting among listed companies (Hamdan et al., 2012). Various initiatives have been implemented to enhance Jordan’s economic environment, including new laws and the Corporate Governance Code. This regulatory reinforcement has increased the number of companies listed on ASE from 161 in 2000 to 247 by 2013 (Marashdeh, 2014). Since the late 1990s, Jordan’s economy has demonstrated stable growth, evidenced by rising trade volumes and market capitalization. This growth is attributed to economic liberalization, corporate governance reforms, and the Jordanian government’s efforts to promote foreign investment.

Jordan has established three national corporate governance codes: the Code for Banks, the Code for Private and Limited Liability Companies, and the Code for Non-Listed Public Shareholding Companies, in addition to the Code for Shareholding Companies listed on the Amman Stock Exchange (EBRD, 2017). The JSC issued the Corporate Governance Code in 2009, governing shareholding companies listed on the ASE to strengthen corporate governance. This code details the responsibilities and structure of the board and its committees. It specifically outlines the duties of the board of directors, which include: (1) establishing strategies, policies, and procedures to meet the company’s objectives; (2) ensuring compliance with applicable laws; (3) formulating a risk management policy; (4) preventing insiders from utilizing confidential information for personal gain; (5) ensuring internal oversight of the company’s operations; (6) reviewing and assessing the performance of executive management; (7) adopting criteria for granting incentives, compensation, and privileges to board members and executive management; and (8) developing a policy to manage relations with stakeholders that fulfills the company’s commitments, safeguards their rights, provides adequate information, and fosters positive relations (JSC, 2017). Furthermore, the Corporate Governance Code specifies the composition of committees formed by the board of directors, such as the audit committee. The JSC (2017) states that audit committee members should have knowledge of finance or accounting, with at least one member possessing experience and an academic or professional qualification in these areas. Additionally, the code requires the audit committee to meet regularly and conduct at least one meeting with an external auditor.

2.5. The Impact of Corporate Governance Structures on Financial Statement Fraud

Independent auditors examine financial statements which may fail to accurately reflect a company’s actual financial position. Due to several accounting scandals and fraud cases, the trustworthiness of financial reports has been damaged, which causes uncertainty over the accuracy of information used in strategic decisions (Rostami & Rezaei, 2022). Therefore, corporate management must address this challenge. Accountants, along with financial analysts, push for strategies that resolve unreliability issues. Organizations needing to combat financial statement fraud and improve reporting quality now focus on corporate governance as a vital topic (Girau et al., 2022).

Effective corporate governance includes internal and external factors. Internal factors include the board of directors, the audit committee, internal control systems, and risk management. External factors consist of external auditing, stakeholder engagement, and regulatory frameworks (Al-Tahan & Nakhal, 2020; Manry et al., 2023). The deployment of these mechanisms necessitates adherence to established procedures executed by relevant authorities, in accordance with the powers and responsibilities assigned to the Board of Directors and Executive Management. The proper implementation of these policies and procedures is anticipated to significantly deter fraud and diminish fraudulent activities (Hasnan et al., 2020).

2.6. Previous Studies in Emerging Markets

Recent studies explored the connection between corporate governance structures and FSF. Key contributions to this field include works by Kuzey et al. (2023), Md Nasir and Hashim (2021), Ozcelik (2020), Stuebs and Sun (2015), Liou (2008), Mertzanis et al. (2023), Lumadi and Rusgowanto (2023), Handoko and Olivia (2022), Uwuigbe et al. (2019), Wahyudi et al. (2019), and Al-Hiyari (2017).

Kuzey et al. (2023) conducted an empirical investigation into the impact of effective corporate governance on fraudulent financial reporting, utilizing a data set comprising 187 companies listed on the Tehran Stock Exchange from 2013 to 2019. The authors employed a modified version of the Beneish (1999) corporate governance assessment model to detect instances of fraudulent reporting. The study examined nine distinct corporate governance mechanisms and concluded that strong corporate governance practices considerably reduce the probability of fraudulent financial disclosures. Interestingly, the findings indicated that compensation structures did not demonstrate a negative correlation with fraudulent activities.

Lumadi and Rusgowanto (2023) investigated the effects of Beneish’s M-score model and financial ratio analysis on indicators of fraudulent financial statements within manufacturing companies in the consumer goods sector, registered on the Indonesia Stock Exchange from 2017 to 2020. The findings indicated that only financial leverage significantly influenced the indications of fraudulent financial statements.

Mertzanis et al. (2023) analyzed the impact of corporate governance on external financing decisions among companies operating in the Middle East and North Africa (MENA) region. The research employed a panel data set comprising 2425 non-financial firms within the MENA region. An ordinary least squares model was utilized to estimate regression coefficients and sensitivity analysis. The study revealed a significant relationship between corporate governance characteristics and their effects on financing decisions.

Handoko and Olivia (2022) investigated the relationships between corporate governance mechanisms and fraudulent financial reporting. The researchers analyzed annual reports of food and beverage companies listed on the Indonesia Stock Exchange from 2018 to 2020. Findings indicated that the size of the board of commissioners significantly influenced fraudulent financial reporting. Conversely, factors such as the composition of independent commissioners, gender diversity within the audit committee, and the frequency of audit committee meetings did not demonstrate any significant effect on fraudulent financial reporting.

Md Nasir and Hashim (2021) evaluated the performance of corporate governance practices in Malaysia over two decades covering 2002 to 2018. The research focused on five categories of corporate governance scores: rules and regulations, enforcement, the policy/regulatory environment, GAAP adoption, and corporate governance culture. The findings suggested that Malaysian businesses benefited from effective laws and regulations implemented through corporate governance reforms. Uwuigbe et al. (2019) investigated the association between FSF and governance within Nigerian business organizations. The study encompassed 122 non-financial companies listed on the Nigeria Stock Exchange. The findings indicate no significant association between audit committee independence, board composition, and FSF.

Wahyudi et al. (2019) conducted an investigation into the relationship between corporate governance mechanisms and financial reporting fraud within non-financial Indonesian companies. Utilizing logistic regression analysis, they designated financial reporting fraud as the dependent variable, while examining audit committee effectiveness and leverage as independent variables. The results indicated that the corporate governance variables accounted for 11.5% of the variance in occurrences of fraud.

Al-Hiyari (2017) evaluated the impact of corporate governance on the reliability of financial reports for public joint-stock industrial companies listed on the Amman Stock Exchange (ASE). The findings revealed that all governance mechanisms exerted a positive influence on reliability, with disclosure and transparency demonstrating the most significant effect.

Aryani (2023) examined the effects of corporate governance mechanisms on financial reporting fraud in the real estate sector. The study focused on the role of the board of commissioners, independent commissioners, managerial ownership, institutional ownership, and audit committees. The research was based on 16 companies listed on the Indonesia Stock Exchange from 2018 to 2022. The results indicated that the audit committee plays a significant role in mitigating financial reporting fraud, while other factors showed little impact. This is in contrast to the analysis conducted by Mertzanis et al. (2023), which utilized a unique panel data set comprising 2425 non-financial firms listed on stock exchanges within the MENA region from 2007 to 2017. Their study investigated the impact of corporate governance on the external financing decisions of firms in the Middle East and North Africa region. The research employed an ordinary least squares model to estimate regression coefficients and conducted a sensitivity analysis utilizing alternative measures of critical variables, and an endogeneity analysis through instrumental variable methods with plausible external instruments.

This study is distinguished from previous research in several respects. First, it incorporates 13 corporate governance factors. Additionally, whereas Aryani’s research concentrated on companies in the real estate sector listed on the IDEX, this study specifically examines industrial and service companies listed on the ASE. While several studies have tested hypotheses using linear regression models, Aryani employed a modified Beneish (1999) corporate governance assessment model to measure FSF. In contrast, this study evaluates the likelihood of FSF based on the Beneish model and tests the hypotheses using a logistic regression model.

3. Hypotheses Development

Based on the literature review presented above, which explores the impact of corporate governance factors on mitigating financial statement fraud (FSF) and highlights various previous studies, we can formulate the primary hypothesis and its associated sub-hypotheses to achieve the study’s objectives as follows:

H₁. 

The corporate governance structure positively affects the mitigation of FSF in Jordanian companies listed on the Amman Stock Exchange (ASE).

The following sub-hypotheses are derived from the primary hypothesis:

H_1.1. 

The size of the board of directors positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.2. 

The independence of the board of directors positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.3. 

The board of directors’ compensation positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.4. 

The lack of duality between the CEO and the Chairman of the Board of Directors positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.5. 

The board diversity positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.6. 

The size of the audit committee positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.7. 

The audit committee with an accounting background positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.8. 

The number of meetings of the audit committee with external auditors positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.9. 

The external auditor’s compensation positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.10. 

The board family business positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.11. 

The presence of women on the board of directors positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.12. 

The firm size positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

H_1.13. 

The market listing positively affects the mitigation of FSF in Jordanian companies listed on the ASE.

4. Research Methods

The present study utilizes logistic regression models to investigate the influence of corporate governance structures on mitigating fraud in the financial statements of companies listed on the Amman Stock Exchange (ASE). The analysis focuses on the relationship between corporate governance frameworks and a reduction in FSF. The study population consists of industrial and service enterprises listed on the ASE. Financial data were extracted from the ASE Company Guide 2022, covering 74 companies. Companies without sufficient data were excluded, resulting in a final sample of 59 companies. The data were sourced from published annual reports from 2018 to 2022.

4.1. Data Collection

The researchers gathered financial data pertinent to the study variables from the annual reports of 74 companies in the service and industrial sectors of the Amman Stock Exchange, covering the period from 2018 to 2022. The decision to limit the sample period to 2018–2022 was based on both methodological and contextual factors. First, corporate governance reforms in Jordan began to gain traction after 2017, particularly following improvements in regulatory disclosure frameworks. Prior data were often inconsistently reported or lacked comparability due to weak enforcement of governance standards. Second, financial and environmental, social, and governance (ESG)-related disclosures were frequently incomplete before 2018, undermining the reliability of essential governance variables. Third, this timeframe captures a relevant economic context, including both pre-pandemic and post-pandemic years, offering a balanced view of corporate behavior. Finally, with a sample size of 59 companies and 295 observations, this period provides adequate statistical power for logistic regression analysis while maintaining internal consistency. Including earlier periods would have significantly compromised data completeness and comparability. Additionally, as per the listing requirements for companies on the Amman Stock Exchange in 2018 (Article 4), submitting a corporate governance report for the previous fiscal year became mandatory.

Therefore, this study relied on a time series of data to more clearly express this phenomenon.

4.2. Beneish’s M-Score

Beneish’s M-score assesses the likelihood of FSF, represented as a binary variable. M-score values identify companies with problems in the preparation of their financial statements (Aryani, 2023). Thus, M-scores are calculated and identified as (M_i = 1), the likelihood of the firm having problems preparing financial statements. Meanwhile, (M_i = 0) is the non-likelihood of such issues.

Several studies, such as Omar et al. (2014); Ofori (2016); MacCarthy (2017); N. Lotfi and Chadegani (2018), Triani (2019); Sutainim et al. (2019); Hołda (2020); and Budić (2023), have investigated the identification of Financial Statement Fraud (FSF) in companies across various countries using the Beneish M-score.

The Beneish M-score model is a financial analysis tool for assessing a company’s financial performance and the likelihood of fraud. An M-score value below −2.22 indicates a low probability of fraud, while a value above −2.22 indicates a high probability of fraud. Although the eight-variable Beneish model (see

Table 1. The M-score’s components and the formulas.

Index (Component)	Formula
Days Sales in Receivables Index (DSRI)	DSRI = (Net Receivables/Sales)/(Net Receivables for the previous year/Sales for the previous year).
Gross Margin Index (GMI)	GMI = [(Prior year sales − Previous year cost of goods sold)/Previous year sales]/[(Current year sales − Current year cost of goods sold)/Current year sales].
Asset Quality Index (AQI)	AQI = [1 − current year’s current assets + previous year’s plant, property and equipment + securities)/current year’s total assets]/[1 − (previous year’s current + previous year’s plant, property, and equipment + previous year’s securities)/previous year’s total assets].
Sales Growth Index (SGI)	SGI = Current Year Sales/Previous Year Sales.
Depreciation Index (DEPI)	DEPI = (Depreciation for the previous year/(Plant, property, and equipment for the previous year + Depreciation for the previous year))/(Depreciation for the current year/(Plant, property, and equipment for the current year + Depreciation for the current year)).
Sales, General, and Administrative Expenses Index (SGAI)	SGAI = (Sales and Administration Expenses for the current year/Sales for the current year)/(Sales and Administration Expenses for the previous year/Sales for the previous year).
Leverage Index (LVGI)	LVGI = [(Current year current receivables + Current year total long-term debt)/Current year total assets]/[(Previous year current receivables + Previous year total long-term debt)/Previous year total assets].
Total Accruals to Total Assets (TATA)	TATA = (income from continuing operations for the current year − cash flows from operations for the current year)/total assets for the current year.

Adopted from Beneish (1999).

) is the most widely used, it is important to note that, as a probabilistic model, it does not guarantee 100% accuracy in detecting fraud. Below is the Beneish M-score model for assessing the likelihood of FSF.

M-Score = (−4.84 + 0.92 × DSRI + 0.528 × GMI + 0.404 × AQI + 0.892 × SGI + 0.115 × DEPI − 0.172 × SGAI + 4.679 × TATA − 0.327 × LVGI)

4.3. Logistic Regression Models

To analyze the relationship between the corporate governance structure and financial statement fraud, this study uses logistic regression models, with pooled panel data, and variables fitted at 1% to avoid the effect of outliers on the dated group. In this case, a logistic regression for this study can be expressed as follows:

$$\begin{gathered} Ln\left({\displaystyle \frac{f(FSF)}{1-f(FSF)}}\right)=\mathrm{P}({\mathrm{Y}}_{it}=1)= \\ {\beta }_0+{\beta }_1{\mathit{BDsize}}_{\mathit{it}}+{\beta }_2{\mathit{BDInd}}_{\mathit{it}}+{\beta }_3{\mathit{BDC}}_{\mathit{it}}+{\beta }_4{\mathit{BDual}}_{\mathit{it}}+{\beta }_5{\mathit{BDiv}}_{\mathit{it}}+{\beta }_6{\mathit{AucSize}}_{\mathit{it}}+{\beta }_{7}Au{\mathit{CAB}}_{\mathit{it}}+{\beta }_{8}AuC{M}_{\mathit{it}}+{\beta }_{9}AuC{c}_i+{\beta }_{10}{\mathit{BFm}}_i+{\beta }_{11}\mathit{WB}+{\beta }_{12}{\mathit{TAsset}}_{\mathit{it}}+ \\ {\beta }_{13}\mathit{MListit}+{\mathsf{\delta }}_{\mathrm{j}}+{\mathsf{\gamma }}_{\mathrm{t}}+{\mathsf{\epsilon }}_{\mathrm{i}\mathrm{t}} \end{gathered}$$

where

FSF: Financial Statement Fraud. For every firm I in period t, Y_it is a binary variable that indicates the likelihood of FSF in model 1, if (P(M-score) > −2.22) there is a likelihood of the earning manipulation while if (P(M-score) < −2.22) there is non-likelihood fraud. Likelihood of fraud takes (1), non-likelihood takes (0).

β₁Bsize_it: board size, the company has between 7 and 9 members on the board of directors, (x₁).

β₂BInd_it: Board Independence take 1, non take 0, (x₂)

β₃BDC_it: Board Compensation represents the annual total compensation of the directors, (x₃)

β₄BDual_it: indicates Non-duality of CEO and Chairman positions. Duality takes 1 and non takes 0, (x₄)

β₅BDiv_it: board diversity represents the business background of the board directors. Diversity takes 1, non takes 0, (x₅)

β₆AucSize_it: Number of audit committees’ members, (x₆)

Β₇AuCAB_it: Number of audit committee members with an accounting background, (x₇)

Β₈AuCM_it: Number of audit committee meetings during the year, (x₈)

β₉AuCC_it: Audit Compensation represents the total annual amount paid to the external auditor, (x₉)

β₁₀BFm_it: Board family business represents whether there are family relationships among the directors or not. Family board takes 1, non takes 0, (x₁₀)

β₁₁WB_it: Women board member takes 1, non takes 0, (x₁₁)

Β₁₂TAsset_it: natural logarithm of Total Assets, (x₁₂)

Β₁₃ MList_it: market listing represents whether the company is listed in Market 1 or Market 2 on ASE, (x₁₃).

δ_j: industry fixed effects

γ_t: year fixed effects

ε_it: error.

5. Research Results

5.1. Descriptive Statistics

This research aims to investigate the relationship between the corporate governance structure and the likelihood of FSF in services and industrial companies listed on the ASE from 2018 to 2022. The study observed a total of 295 cases (observations) during this period. Among the 59 companies analyzed, 21.4% were found to have a non-probability of fraud, while the remaining 78.6% (232 observations) showed a probability of fraud.

5.2. Model Fit Measures

A significance level (α) of 0.05 was used to evaluate the model.

Table 2. Model fit measures.

					Overall Model Test
Model	Deviance	AIC	R2McF	R2CS	χ2	df	p
1	21.06	32.0	0.697	0.416	163	13	<0.001

shows the overall model was found to be significant, with a chi-square value of 163 and p < 0.001. This suggests that the corporate governance factors included in the model have a significant positive or negative impact on the mitigation of FSF.

We calculated AIC, McFadden’s R-squared (R²McF) and Cox and Snell’s R-squared (R²CS) values to assess the model fit. Values greater than 0.2 indicate an excellent fit (Louviere et al., 2000). For this model, the calculated R²McF and R²CS values were 0.697 and 0.416, respectively. The Akaike Information Criterion (AIC) value was 32.00, with 13 degrees of freedom (df), and p < 0.001. A lower AIC value typically signifies a model that demonstrates a more effective fit to the data.

Table 2 presents the chi-square, df, and p-values for the independent variables.

5.3. Correlation Matrix

The results of the Pearson correlation analysis in

Table 3. Correlation matrix.

	X1	X2	X3	X4	X5	X6	X7	X8	X9	X10	X11	X12	X13	Industry
B.D size (x1)	-
B.D Ind. (x2)	0.394 ***	—
B.D.C (x3)	0.551 ***	0.051	—
Duality (x4)	0.037	0.192 ***	−0.325***	—
Diversity (X5)	0.017	−0.086	0.016	−0.049	—
Audit C.S (x6)	0.426 ***	0.124 *	0.164 *	0.018	0.012	—
Audit.C.A.B (x7)	0.055	0.141 *	−0.170*	0.163 **	0.075	0.385 ***	—
Audit C. M. (x8)	0.110	0.164 **	0.163 *	−0.106	0.074	0.150 **	0.095	—
Audit.C (x9)	0.589 ***	0.536 ***	0.095	0.034	0.085	0.202 *	0.131	0.254 **	—
F. Bus (x10)	0.163 **	0.281 ***	0.268 **	0.234 ***	0.061	−0.047	0.193 ***	0.152 **	−0.186 *	—
Women (x11)	0.313 ***	0.081	0.633 ***	0.386 ***	0.041	0.126 *	−0.136 *	−0.067	0.254 **	0.284 ***	—
F.Size (x12)	0.111	0.124 *	0.194 *	0.036	0.103	0.023	0.042	0.214 ***	0.234 **	0.093	0.043	—
Market .L (x13)	0.326 ***	−0.048	0.417 ***	−0.093	−0.066	0.173 **	0.219 ***	0.108	0.268 ***	0.015	0.328 ***	0.193 ***	—
Industry	0.129 *	0.081	0.030	−0.124 *	0.051	0.099	0.157 **	0.215 ***	−0.011	0.054	0.076	0.152 **	0.076	—
Year	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000

Note. * p < 0.05, ** p < 0.01, *** p < 0.001.

show that there is no statistically significant correlation among the independent variables in the model at p < 0.05. Although the relationship is positive, it is weak and does not reach the level of statistical significance. Therefore, based on these findings, the null hypothesis is not rejected, and it can be concluded that the variables under investigation are positively correlated.

To evaluate the impact of explanatory variables on the likelihood of observing FSF, a correlation matrix was conducted. The reference classification for Y was 0 or 1. The analysis included a total of 59 companies with 295 observations from the service and industrial sectors. Also,

Table 4. Relationship between the variables of corporate governance structure and FSF (M-score) 2018–2022.

Predictor	Estimate	SE	Z	p	VIF	Tolerance
Constant	14.3728	8.660	1.660	0.097	-	-
(x1)	0.6374	0.358	1.782	0.075	4.61	0.206
(x2)	−0.5167	0.260	−1.990	0.047	3.30	0.303
(x3)	−1.01 × 10−5	6.89 × 10−6	−1.462	0.144	4.49	0.223
(x4)	0.2047	1.635	0.125	0.900	1.51	0.662
(x5)	−2.0220	1.446	−1.398	0.043	1.40	0.712
(x6)	0.0787	0.605	0.130	0.896	1.76	0.569
(x7)	−0.8371	0.476	−1.759	0.041	2.42	0.413
(x8)	−0.9133	0.341	2.680	0.007	3.00	0.333
(x9)	3.00 × 10−5	3.55 × 10−5	0.845	0.398	2.03	0.492
(x10)	−2.5422	0.980	−2.593	0.010	3.02	0.331
(x11)	0.1715	0.849	0.202	0.840	1.78	0.563
(x12)	−1.0985	0.481	−2.284	0.022	4.19	0.239
(x13)	1.0507	1.421	0.740	0.460	4.75	0.211

Note: Estimates represent the log odds of “M. Score = Non-Probability” vs. “M. Score = Probability Fraud”.

presents a check for multicollinearity by examining the VIFs and tolerance for each predictor in the model. The table indicates that all VIF values are below 5, except for the B.D number, which suggests that there is no multicollinearity in the model. Generally, a VIF above 4 or a tolerance below 0.25 indicates the presence of multicollinearity, and further investigation is required. If the VIF is higher than 10 or the tolerance is lower than 0.1, it indicates significant multicollinearity that needs to be addressed.

5.4. Logistic Regression Results

Table 4 shows the relationship between the variables corporate governance structure and FSF (M-score) between 2018 and 2022. In the majority of analyses, an alpha of 0.05 was used as the cutoff for significance. If the p-value is less than 0.05, we accept the hypothesis that there is a positive effect on the mitigation of the FSF. Thus, based on the results shown in Table 4, the B.D Ind (x₂), Diversity (x₅), Audit C.A.B (x₇), Audit. C.M (x₈), F. Bus (x₁₀), and F. Size (x₁₂) have a positive effect on the mitigation of FSF. In contrast, the others have no effect.

From Table 4, we can formulate the logistic regression as follows:

Y = 14.3728 + 0.6374 x₁ − 0.5167 x₂ − 1.01 × 10⁻⁵ x₃ + 0.2047 x₄ − 2.0220 x₅ + 0.0787 x₆ − 0.8371 x₇ − 0.9133 x₈ + 3.00 × 10⁻⁵ x₉ − 2.5422 x₁₀ + 0.1715 x₁₁ − 1.0985 x₁₂ + 1.0507 x₁₃ + 3.62_industry − 5.27_year + e_i

The regression coefficient of variable X₁ is 0.6374 (positive), while the p-value is 0.075 greater than (α) 0.05, which indicates that the B. size is not a significant variable. However, there is a positive relationship between changes in the number of board directors (X₁) and the likelihood of FSF.

The regression coefficient of the variable X₂ is −0.5167 (negative), while the p-value is 0.047 less than (α) 0.05, which indicates that B.D independent is a significant variable. However, a negative coefficient indicates that FSF is negatively associated with the independence of the board of directors (X₂). This implies that having more independent board directors reduces the likelihood of FSF.

The regression coefficient of the variable X₃ is −1.01 × 10⁻⁵ (negative), while the p-value is 0.144 greater than (α) 0.05 which indicates that the B.D compensation is not a significant variable. However, a negative coefficient indicates that FSF is negatively associated with the compensation and incentives rewards to the board of directors (X₃). This implies that increasing the amount of board directors’ compensation reduces the likelihood of FSF.

The regression coefficient for the variable X4 (non-Duality), is 0.2047 (Positive), while the p-value is 0.90 greater than (α) 0.05, which indicates that the CEO and chairman positions (non-duality) are not a significant variable. However, a positive coefficient suggests that FSF will occur frequently when the same person holds both the positions of CEO and Chairman of the Board of Directors (duality) (X4).

The regression coefficient for the variable X₅ (diversity), is −2.0220 (negative), while the p-value is 0.043 less than (α) 0.05, which indicates that the diversity background of the board of directors is a significant variable. However, a negative coefficient implies that FSF moves in the opposite direction of changes in the diversity level of the board directors (X₅). In other words, an increase in the diversity level leads to a decrease in the likelihood of FSF.

The regression coefficient of the variable X₆ (Audit C.S), is 0.0787 (positive), while the p-value is 0.896 greater than (α) 0.05, which indicates that Audit C.S is not a significant variable. However, a positive coefficient indicates that FSF will be positively associated with changes in the number of audit committee members (X₆).

The regression coefficient for variable X₇ (Audit C.A.B) is −0.8371, indicating a negative relationship, while the p-value is 0.043 less than (α) 0.05, which indicates that Audit C.A.B is a significant variable. However, a negative coefficient suggests that as the involvement of accounting experts in the audit committee (X₇) increases, the occurrence of FSF decreases.

The regression coefficient of the variable X₈ (Audit. C.M) is −0.9133 (negative), while the p-value is 0.007 less than (α) 0.05, which indicates that the frequency of audit meetings is a significant variable. However, a negative coefficient indicates that FSF is negatively associated with the frequency of audit meetings (X₈).

The regression coefficient of the variable X₉ (Ext. A.C.) is 3.00 × 10⁻⁵ (positive), while the p-value is 0.398 greater than (α) 0.05, which indicates that the external audit fees is not a significant variable. However, a positive coefficient indicates that FSF will be positively associated with changes in the amount of audit compensation (X₉).

The regression coefficient for variable X₁₀ (FBus) is −2.5422, indicating a negative relationship, while the p-value is 0.010 less than (α) 0.05, which indicates that family business board is a significant variable. However, a negative coefficient implies that FSF occurrence is negatively associated with family board-managed firms (X₁₀). So, having more family board directors leads to a lower likelihood of FSF.

The regression coefficient of the variable X₁₁ (WD) is 0.1715 (positive), while the p-value is 0.84 greater than (α) 0.05, which indicates that the involvement of women on the board of directors is not a significant variable. However, a positive coefficient indicates that FSF is positively associated with the level of the women board director members (X₁₁).

The regression coefficient for variable X₁₂ (F. Size) is −1.0985, indicating a negative relationship, while the p-value is 0.022 less than (α) 0.05, which indicates that the firm size is a significant variable. However, a negative coefficient suggests that if the size of the firm (X₁₂) increases, the occurrence of FSF decreases. In other words, a larger size of the firm with good corporate governance practices leads to a lower likelihood of FSF.

The regression coefficient of the variable X₁₃ (MList) is 1.0507 (positive), while the p-value is 0.46, greater than (α) 0.05, which indicates that whether the company listed in the first or second market is not a significant variable. However, a positive coefficient suggests a positive association but not significant between FSF and whether the company is listed in the first market or second market (X₁₃).

6. Discussion

The influence of corporate governance factors, a chi-square value of 49.2, indicates that the addition of independent variables has a notable impact on the model. This value exceeds the chi-square value of 49.2 obtained from Table 2 at df 13 (number of independent variables), at a significance level of 0.006, which is lower than the conventional threshold of 0.05. Therefore, we accept the primary hypothesis H₁. Thus, the practice of corporate governance structure has a significant influence on FSF.

Based on the results shown in Table 4, B.D Ind (x₂), Diversity (x₅), Audit C.A.B (x₇), Audit. C.M (x₈), F. Bus (x₁₀), and F. Size (x₁₂) are significant variables. In contrast, the others are not significant. The impact of various factors on instances of FSF in companies listed on the ASE from 2018 to 2022 can be observed through the R²McF value, which is 0.49 or 49%. This means that approximately 49% of the variability in FSF can be explained by the factors mentioned. The remaining 51% of the variability is attributed to other variables not included in the research model. To enhance the R²McF value, it is essential to incorporate additional variables, including shareholder types (distinguishing between individuals and companies, both Jordanian and non-Jordanian), company performance and financial position, an extension of the sample period, accounting disclosure practices, and the quality of internal control.

6.1. The Influence of Board Size on FSF

The analysis results indicate that the variable of board size (X1) has a significance level of 0.075, which is higher than the threshold of 0.05. In addition, it has a coefficient value of 0.6374. Therefore, it can be concluded that board size does not significantly influence FSF. As a result, hypothesis H_1.1 is rejected. This study does not provide evidence of board size’s impact on FSF. This suggests that regardless of the number of board directors, they have not effectively coordinated and distributed tasks and duties among themselves, leading to a higher likelihood of FSF. Consequently, board size as a corporate governance factor does not address the issue of FSF. Concerning Jordanian companies, whether listed on the first or second market, it seems the number of board directors is not a crucial factor in exerting a vital impact on reducing FSF.

Wahba and Elsayed (2010) posited that an increase in the size of the board of directors results in heightened complexity in coordination, thereby presenting greater challenges. This increased complexity may inadvertently create opportunities for management to engage in fraudulent activities, thereby enabling them to exert a more significant degree of control over the board.

6.2. The Influence of Board Director Independence on FSF

The analysis’s findings indicate that the variable of board director independence (X2) has a significance value of 0.047, which is below the threshold of 0.05. Additionally, it has a coefficient value of −0.5167. Therefore, it can be concluded that the board director independence variable has a positive impact in the mitigation of FSF. Consequently, hypothesis H_1.2 is accepted. This study provides evidence of the influence of board director independence on FSF, suggesting that having a certain number of independent board directors in a company has a significant effect in combating instances of FSF.

This finding is consistent with previous studies conducted by Xie et al. (2020) and Siladi (2006), which emphasize the positive effect of board director independence on management monitoring. This, in turn, reduces agency problems (Jensen & Meckling, 1976) and the likelihood of FSF. However, Ebaid (2023) indicates that there is a significant negative correlation between board independence and the likelihood of financial statement fraud. These contrasting results suggest that independent directors play a crucial role in directly overseeing the companies they serve, thereby enhancing the effectiveness of monitoring functions within the organization. Independent directors bear the responsibility of supervising and overseeing the decisions and actions of management to ensure alignment with the organization’s best interests.

6.3. The Influence of Board Compensation on FSF

The findings of the study suggest that board director compensation (X3) does not have a significant impact on FSF. The statistical analysis reveals a negative association, with a coefficient value of −1.01 × 10⁻⁵. However, the significance level of 0.144 is higher than the threshold of 0.05. Therefore, the variable of board compensation does not significantly influence FSF in Jordanian companies listed on the ASE. As a result, hypothesis H_1.3 is rejected, indicating that this study fails to demonstrate the influence of board compensations on FSF. This implies that although board compensation serves as an incentive for management to align their objectives with those of shareholders, many managers do not hold shares in the company. Consequently, they lack a direct interest in addressing or reducing FSF committed by managers.

This result contradicts the findings of Martins and Ventura (2020), who observed that boards with higher pay are more effective at mitigating the likelihood of fraud in corporate financial reporting.

6.4. The Influence of Duality of CEO and Chairman Positions on FSF

The analysis findings show that the variable X4, which represents the duality of CFO and chairman positions, has a significance level of 0.90, surpassing the threshold of 0.05. Moreover, its coefficient value is 0.2047. Therefore, we can conclude that the duality of CEO and chairman positions does not have a statistically significant impact on FSF. As a result, hypothesis H_1.4 is rejected, indicating that this study does not provide evidence for the influence of duality positions between CFO and chairman on FSF.

In the majority of cases (89.5%), there is no duality between the roles of CEO and Chairman. This indicates that in most companies, directors and chairmen of the board are fully committed to their respective responsibilities. This approach, as demonstrated by Chhaochharia and Grinstein (2009), helps prevent the concentration of power and unilateral decision making.

6.5. The Influence of Diversity Experience of Board Directors on FSF

The analysis findings show that the variable X5, which represents the diversity experience of the board director, has a significance level of 0.042, which is below the threshold of 0.05. Moreover, its coefficient value is −2.0220. Therefore, we can conclude that the diversity experience board directors has a positive impact in the mitigation of FSF. As a result, hypothesis H_1.5 is accepted, indicating that this study provides evidence for the influence of diversity of board director background on FSF.

This result is consistent with Haron et al. (2021), who asserted that diverse experience of board directors with industrial and accounting/finance experience decreases the likelihood of the occurrence of corporate fraud.

6.6. The Influence of the Audit Committee Size on FSF

Based on the test results, it is evident that the variable representing audit committee size (X6) is highly significant with a significance level of 0.896, surpassing the threshold of 0.05. Additionally, it exhibits a coefficient value of 0.0787. Hence, we can conclude that the audit committee size variable does not have a significant and positive impact on FSF. Consequently, the hypothesis H_1.6 is rejected. This result is the opposite of that of the study conducted by Widodo and Syafruddin (2017) that revealed a positive correlation between the effectiveness of the audit committee and a reduction in FSF.

Statistical data reveal that the average number of individuals serving on an audit committee is 3.00. The Securities Law No. (18) For the Year 2017, Article (46/1), stipulates the regulations governing audit committees, stating that “The Audit Committee should consist of at least three non-executive members”. The key objective of creating an audit committee is to employ a supervisory responsibility over company management. Implementing this critical role enhances the transparency and accountability within the company and mitigates the risk of FSF.

6.7. The Influence of an Audit Committee with an Accounting Background on FSF

The analysis’s findings show that the variable X7, which represents the audit committee with accounting background experience, has a significance level of 0.043, which is below the threshold of 0.05. Moreover, its coefficient value is −0.8371. Therefore, we can conclude that an audit committee with accounting background experience has a positive impact in the mitigation of FSF. As a result, hypothesis H_1.7 is accepted, indicating that this study provides evidence for the influence of the accounting background of audit committee members on FSF.

This finding is in accordance with the assertions made by Haron et al. (2021), who contended that an audit committee comprising members with expertise in accounting or finance is less prone to permitting corporate fraud. Additionally, Mustafa and Ben Youssef (2010) bolster the argument that an independent audit committee possessing financial and accounting proficiency significantly mitigates the likelihood of corporate fraud.

6.8. The Influence of Frequent Audit Committee Meetings on FSF

The analysis reveals that variable X8, representing the frequency of audit committee meetings, exhibits a significance level of 0.007, which is substantially lower than the 0.05 threshold. The corresponding coefficient value is −0.9133, allowing us to infer that the frequency of audit committee meetings has a positive impact in the mitigation of FSF. Consequently, we accept hypothesis H_1.8, thereby providing empirical support for the influence of audit committee meeting frequency on FSF.

This finding is consistent with the research conducted by Huang and Thiruvadi (2010), which established a significant relationship between the audit committee’s activities and the likelihood of FSF. The observed impact can be attributed to the enhancement of control mechanisms and the improvement of oversight associated with more frequent meetings, ultimately contributing to the reduction and prevention of fraudulent financial reporting.

6.9. The Influence of the External Audit Fees on FSF

Based on the test results, it is evident that the variable representing external audit fees (X9) is highly significant with a significance level of 0.398, surpassing the threshold of 0.05. Additionally, it exhibits a coefficient value of 3.00 × 10⁻⁵. Hence, we can conclude that the external auditor fees variable does not have a significant and positive impact on FSF. Consequently, the hypothesis H_1.9 is not supported.

This result is the opposite of the empirical study conducted by Mironiuc and Robu (2012), who concluded that a low level of audit compensation has caused an increase in the likelihood of fraud of the companies listed on the New York Stock Exchange between 2001 and 2002. This demonstrated that there is a high influence of audit compensation on FSF.

6.10. The Influence of Board Family Business on FSF

The analysis’s findings show that the variable X10, which represents that the board directors consist of many members from the same family, has a significance level of 0.010, which is below the threshold of 0.05. Moreover, its coefficient value is −2.5422. Therefore, we can conclude that the board director’s family has a positive impact in the mitigation of FSF. As a result, hypothesis H_1.10 is accepted, indicating that this study provides evidence for the influence of board family structure on decreases in the occurrence of FSF.

This result is inconsistent with Abadi et al. (2023), who asserted that the competence of the family business board does not have the power to amplify the influence of FSF, and the variable of the family business board cannot increase the impact of arrogance on FSF.

6.11. The Influence of the Presence of Women on the Board of Directors on FSF

Based on the test results, it is evident that the variable representing audit committee size (X11) is highly significant with a significance level of 0.840, surpassing the threshold of 0.05. Additionally, it exhibits a coefficient value of 0.1715. Hence, we can conclude that the presence-of-women variable does not have a significant and positive impact on FSF. Consequently, the hypothesis H_1.11 is not supported.

It is concluded by different studies that the presence of women on boards of directors also enhances a company’s culture and image. It promotes diversity and inclusion, allowing companies to retain and develop the best talent and performance at all levels (Manry et al., 2023).

The findings of this study are incongruous with the research conducted by Wang et al. (2022). Wang et al.’s study supports the notion that women in corporate leadership positions display risk aversion tendencies and exhibit a stronger dedication to ethical practices compared to their male counterparts. Furthermore, their research indicates that an increase in female representation in high-level leadership positions can effectively mitigate and detect instances of fraud within non-state-owned enterprises. However, this relationship does not hold for state-owned enterprises.

6.12. The Influence of Firm Size on FSF

The analysis findings show that the variable X12, which represents the firm which is represented by the natural logarithm of the firm total assets, has a significance level of 0.022, which is below the threshold of 0.05. Moreover, its coefficient value is −1.0985. Therefore, we can conclude that firm size has a positive impact in the mitigation of FSF. As a result, hypothesis H1.12 is accepted, indicating that this study provides evidence for the influence of firm size on FSF.

Girau et al. (2022) asserted that corporate governance is a crucial aspect that focuses on safeguarding the financial system, ensuring stability, and protecting capital and assets from crises and collapse. The results of this study contrast with the study of Martins and Ventura (2020). They concluded that the practice of corporate governance structure has a non-significant relationship with FSF. Thus, they pointed out that the finding is surprising because larger firms are expected to be less likely to manipulate earnings as they tend to have a bigger and better governance structure.

The previous results align with research that shows how firm size positively affects FSF. In simpler terms, larger firms, along with good corporate governance practices, are less likely to be involved in FSF.

6.13. The Influence of Market Listing on FSF

Based on the test results, the variable market listing (X13) is significant with a significance level of 0.460, surpassing the threshold of 0.05. It exhibits a coefficient value of 1.0507. Thus, we conclude that the market listing variable does not have a significant positive impact on FSF. Consequently, the hypothesis H1.13 is not supported.

Most financial markets are considering requiring companies listed on the stock exchange to commit to applying governance rules as a new condition for listing. These rules are applied globally, and the Capital Market Authority issues governance rules in their final form, granting a period for companies to comply with corporate governance (Chang et al., 2014).

7. Conclusions

This study concludes that several corporate governance variables significantly influence FSF. The impact of these factors on FSF in companies listed on the ASE from 2018 to 2022 is reflected in the R²McF value of 0.49, indicating that 49% of the variance in FSF is explained by these variables. A total of 295 cases were observed during this period. Among the 59 companies analyzed, 21.4% were found to have a low probability of fraud, while the remaining 78.6% (232 observations) showed a high probability of fraud.

This research investigates the influence of corporate governance structure on mitigating FSF. The primary contribution is the development of a logistic regression model to ascertain the relationship between corporate governance variables, which has not been extensively documented in the Jordanian context in previous studies. This study successfully developed a logistic regression model capable of predicting the likelihood of fraudulent activity within the financial statements of industrial and service companies listed on the Amman Stock Exchange. The model was developed to investigate the influence of 13 corporate governance variables on reducing the likelihood of FSF. The model was evaluated for collinearity using the VIF and tolerance values. The model fit measures, including overall model fit, R²McF, and R²CS values, were determined to be 0.491 and 0.451, respectively.

The M-score model assesses the likelihood of FSF manipulation. It incorporates variables such as board size (positive coefficient), board director’s compensation (negative coefficient), non-duality of CEO and chairman positions (positive coefficient), audit committee size (positive coefficient), external auditor fees (positive coefficient), the presence of women on the board of directors (positive coefficient), and market listing (positive coefficient). However, these do not exhibit a statistically significant effect (α ≤ 0.05) in mitigating FSF in Jordanian companies listed on the ASE. Conversely, the corporate governance structure concerning board director’s independence (negative coefficient), board diversity (negative coefficient), audit committee accounting background (negative coefficient), number of annual audit committee meetings (negative coefficient), board family business (negative coefficient), and firm size (negative coefficient) demonstrates a statistically significant effect (α ≤ 0.05) in mitigating FSF in these companies.

Financial statement fraud can be analyzed through the lens of agency theory, which posits that managers (agents) may engage in opportunistic behavior to optimize their interests, potentially to the detriment of shareholders (principals). This behavior may manifest in the manipulation of financial statements to meet performance targets, secure bonuses, or obscure subpar performance. Consequently, this study emphasizes various governance mechanisms that may mitigate the challenges associated with agency theory. Notably, the active implementation of corporate governance codes emerges as a significant strategy that organizations can adopt to reduce the incidence of financial statement fraud. The study identifies several corporate factors where companies can reduce agency challenges, including the presence of independent board directors, board diversity, the accounting backgrounds of audit committee members, the frequency of audit committee meetings, the involvement of family members on the board, and specific firm characteristics.

This study is subject to several limitations, including constraints related to the variables associated with corporate governance, which are influenced by the sample size and time horizon. Additionally, the omission of depreciation in estimating the M-score is significant, as most financial statements typically present only the net value of property, plant, and equipment. Furthermore, certain companies fail to provide sufficient data, even in voluntary disclosures. Limitations are also present within the models utilized, which tend to oversimplify a complex reality that necessitates highly accurate and consistent data. Moreover, the current empirical design raises substantial endogeneity concerns; specifically, the design cannot eliminate the possibility that firms with a low likelihood of engaging in financial state fraud may choose to adopt a more robust corporate governance structure. Nevertheless, given the scarcity of research on this topic in the existing literature, the methodological rigor of this study, and the significance of its findings, these limitations do not undermine the validity of the research, which remains closely aligned with the relevant literature.

Recommendations for practitioners: companies should emphasize strong corporate governance practices, including independent oversight and clear delineation of roles, to mitigate potential fraud risks effectively. Recommendations for academics: Future research could explore additional factors influencing the effectiveness of external audits in fraud detection to enhance fraud prevention strategies. Further research could also investigate the mechanisms through which governance rules influence fraud prevention in newly listed companies for a deeper understanding. In addition, future research may examine the influence of governance factors on the mitigation of fraud, both in general and specifically in financial statements, by categorizing governance rules into internal and external classifications.