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Article

The Use of the Fraud Pentagon Model in Assessing the Risk of Fraudulent Financial Reporting

by
Georgiana Burlacu
1,
Ioan-Bogdan Robu
2,*,
Ion Anghel
3,
Marius Eugen Rogoz
4 and
Ionela Munteanu
5,6,*
1
Doctoral School of Economics and Business Administration, Alexandru Ioan Cuza University of Iasi, 700505 Iasi, Romania
2
Faculty of Economics and Business Administration, Alexandru Ioan Cuza University of Iași, 700505 Iasi, Romania
3
Faculty of Accounting and Management Information Systems, Bucharest University of Economic Studies, 010374 Bucharest, Romania
4
Doctoral School of Accounting and Management Information Systems, Bucharest University of Economic Studies, 010374 Bucharest, Romania
5
Department of Finance and Accounting, Faculty of Economic Sciences, Ovidius University of Constanta, 900527 Constanta, Romania
6
Department Accounting, Bucharest University of Economic Studies, 010374 Bucharest, Romania
*
Authors to whom correspondence should be addressed.
Risks 2025, 13(6), 102; https://doi.org/10.3390/risks13060102
Submission received: 19 April 2025 / Revised: 11 May 2025 / Accepted: 14 May 2025 / Published: 22 May 2025
(This article belongs to the Special Issue Risk Analysis in Financial Crisis and Stock Market)
Browse Figure
Versions Notes

Abstract

:
This study examines the relevance of the Fraud Pentagon Theory in detecting fraudulent financial reporting among companies listed on the Bucharest Stock Exchange. While financial reporting is essential for informed stakeholder decisions, requiring information to be accurate, reliable, and fairly presented and pressure to meet expectations can lead to manipulation. The Fraud Pentagon Theory identifies five potential drivers of such behavior: pressure, opportunity, rationalization, capability, and arrogance. This research contributes to the literature by empirically testing the theory in the Romanian context, an emerging market with limited prior analysis, using a sample of 62 listed companies over the 2017–2021 period. Regression analysis was applied, using the Dechow F-score, which combines accrual quality and financial performance to assess the likelihood of fraudulent financial reporting. The findings reveal that not all dimensions of the theory significantly affect the likelihood of fraudulent reporting. Specifically, pressure-related factors (financial performance and financial stability) were found to be statistically significant, while external pressure, opportunity (external auditor quality and nature of industry), rationalization (change of auditor), capability (change of director), and arrogance (number of CEO’s pictures) did not show significant influence in the Romanian framework. These results highlight the importance of contextual factors such as market structure, governance practices, and stakeholder expectations, suggesting that fraudulent reporting risk indicators may vary across different economic environments.

1. Introduction

Currently, companies are witnessing a series of challenges arising with the development of technology, the economic environment, and the complexity of information (Fitriyah and Novita 2021). All these challenges have substantially increased the risk of fraud within companies (Han 2017). The most common form of fraud at the company level is fraudulent financial reporting (Triandi 2019). Financial reporting is used to present a true and fair view of the company’s financial position and performance, which managers make available to stakeholders to support their investment decisions (Osadchy et al. 2018). Considering that even subtle accounting choices within legal limits can significantly influence how investors perceive a company’s health, the situation becomes concerning when such choices, driven by mischievous intent, exceed legal boundaries. This occurs, for example, when financial statements are deliberately manipulated by managers to obtain financial benefits or to present a more favorable image of the company’s performance, a practice known as fraudulent financial reporting (Fathmaningrum and Anggarani 2021).
Fraudulent financial reporting is described by the Association of Certified Fraud Examiners (ACFE) as a distortion of a company’s economic situation, with the aim of providing stakeholders with a better view of financial performance (ACFE 2022). In an attempt to explain which factors lead to fraud, many researchers have developed several theories. The first theory is that of Donald Cressey, who argues that the determinants of financial fraud could be synthesized in a fraud triangle, in which each angle is represented by the motivation for committing fraud (Cressey 1953; Mironiuc et al. 2012). The Fraud Triangle proposed by Cressey includes opportunity, motivation (also referred to as “pressure” or “incentive”), and attitude (also known as “rationalization”) as the three triggers that can lead to fraudulent intent. Psychologists and sociologists have widely used the Fraud Triangle to investigate criminal behavior (Schuchter and Levi 2016).
Other studies have discussed the expansion of the Fraud Triangle. Wolfe and Hermanson (2004) further developed Cressey’s theory by adding a fourth dimension, “capability”, to the Fraud Triangle, thus expanding it into the Fraud Diamond. “Capability” refers to the idea that some people will not commit fraud even if all three original factors (pressure, opportunity, and rationalization) are present. The perpetrators are most likely to commit fraudulent acts when they possess certain personality traits (like greed or dishonesty) and knowledge of incidental regulations and are confident that their actions will go undetected (Vousinas 2019).
A comprehensive theory that reveals more incentives about the determinants of fraud is the Fraud Pentagon Theory. This theory was developed in 2010 by Jonathan Marks, one of the partners responsible for fraud and ethics practices at Crowe Horwarth LLP. The Fraud Pentagon Theory builds upon the earlier Fraud Triangle and Diamond models (Hidayah and Saptarini 2019), by introducing “arrogance” as an additional factor, providing a deeper explanation for the psychological traits that may lead to fraudulent behavior. In recent years, this framework has drawn increasing attention from researchers aiming to develop quantitative approaches for identifying the drivers of fraudulent financial reporting across diverse national and temporal contexts. Studies such as those by Situngkir and Triyanto (2020) or Sahla and Ardianto (2023) have used quantitative methods to test the Fraud Pentagon Model in the context of emerging economies and different stock exchanges, highlighting the applicability and relevance of the theory beyond its conceptual origins. Researchers have consistently emphasized the need to expand the literature by applying the Fraud Pentagon Theory in varied geographic, economic, and institutional settings to assess its explanatory power and robustness (Situngkir and Triyanto 2020; Ariyanto et al. 2021). Although the research body has gained momentum, it still encompasses a notable gap regarding the limited exploration of the Fraud Pentagon Model in Eastern European capital markets, including Romania. Very few empirical studies, if any, have comprehensively tested the Fraud Pentagon framework in the Romanian context, particularly among companies listed on the Bucharest Stock Exchange.
Given Romania’s transitional economy, evolving corporate governance structures, and increasing integration into global financial systems (Vancea et al. 2017), an empirical investigation of the Fraud Pentagon in this setting offers a novel and meaningful contribution to the literature. It addresses a regional research gap by contributing to the understanding of fraud risk indicators in environments where institutional enforcement mechanisms and financial transparency may differ from more developed markets.
The research focus of this study is twofold: (a) on the one hand, it aims to test whether the five dimensions of the Fraud Pentagon affect the fraudulent financial reporting of Romanian listed companies, and (b) on the other hand, it aims to determine the factors that dominate the effect on the occurrence of fraudulent reporting.
The paper is organized into several key sections: a comprehensive review of the relevant literature underlying the development of research hypotheses, a detailed explanation of the research methodology, the presentation of the empirical results, followed by the discussion of the findings and conclusions.

2. Literature Review and Hypotheses Development

The Fraud Pentagon Theory represents a conceptual advancement in understanding the behavioral drivers behind fraudulent financial reporting. Evolving from earlier models like the Fraud Triangle (Cressey 1953) and the Fraud Diamond (Wolfe and Hermanson 2004), this theory was introduced by Crowe Horwath in 2011 to better reflect the complexity of fraud-related decisions. It introduces a fifth element, arrogance, to the existing dimensions, emphasizing the role of overconfidence or a sense of invincibility in enabling unethical actions (Crowe 2011). Arrogance, as a psychological dimension, improves the comprehension of individual motivation to commit fraud when powerful decisional positions are in force (Fathmaningrum and Anggarani 2021). The model proposed by the Fraud Pentagon Theory is presented in Figure 1.
The five factors summarized in the Fraud Pentagon are, in turn, determined by other elements that lead to fraudulent financial reporting. As a first factor of the Fraud Pentagon, pressure, occurs when the entity fails to achieve its financial objectives, when it faces financial instability, or when external pressures exist. Opportunities for fraud arise when internal control is deficient or when the low quality of external control permits omissions in the assessment of significant nonconformities. The third element of the fraud pentagon, namely rationalization, is monitored in the study considering the change of the auditor. The fourth element of the Fraud Pentagon, competence, is represented by the change of directors, while arrogance is reflected by the number of pictures of the CEO in annual reports.
Theoretical diversity in fraud research reflects the multifaceted nature of the phenomenon. The literature in forensic accounting and corporate fraud detection also recognizes the “Fraud Tree” developed by Joseph T. Wells (2009) under the Association of Certified Fraud Examiners (ACFE). The Fraud Tree offers a taxonomical approach to fraud classification by organizing occupational fraud into three major categories: corruption, asset misappropriation, and fraudulent financial statements. Each model brings specific strengths and inherent trade-offs. The Fraud Triangle is foundational in illuminating the motivational drivers behind fraud, such as pressure and rationalization, but it simplifies complex interactions by excluding organizational dynamics. The Fraud Diamond addresses this by introducing “capability”, recognizing that not all individuals under pressure with opportunity will act unethically unless they possess the means and position to do so. The more recent Fraud Pentagon expands this further by including “arrogance”, capturing traits often seen in executive-level misconduct. In contrast, the Fraud Tree shifts focus from motive to method, offering a structured classification of fraud schemes. While highly useful for internal control assessments and forensic audits, it lacks the behavioral depth of the other models. Therefore, the choice of theory should reflect the research objective: behavioral models are better suited for studying causes, while structural models are more effective in categorizing and diagnosing fraud cases.
Acknowledging that the literature on fraud includes a myriad of perspectives and theoretical approaches, this study focuses on the Fraud Pentagon Theory due to its expanded behavioral scope and relevance to corporate-level misconduct. The Fraud Pentagon offers a more nuanced understanding of the psychological and organizational drivers behind financial statement manipulation. This is particularly important when examining companies listed on public stock exchanges, where executive decision making and reputational incentives often play a central role in shaping reporting practices. By applying the Fraud Pentagon, this research seeks to address both the complexity of individual intent and the influence of structural opportunities within firms. This framework is especially fitting for emerging markets like Romania, where evolving governance norms and regulatory environments require a more comprehensive behavioral model for fraud risk assessment.
Based on the above-mentioned, the following research model is proposed in the present study, according to Table 1:
The financial target (financial objective) represents the goals that the manager should achieve (Fathmaningrum and Anggarani 2021). In this respect, previous studies highlighted the relevance of the return on assets ratio (ROA) when calculating business profitability to measure the effectiveness of the company in generating profits by using the assets held (Tjahjani et al. 2022). When this financial target is not met, scholars suggest that managers resort to manipulating financial results (Setiawati and Baningrum 2018). In addition, studies by Akbar (2017) and Septriani and Handayani (2018) found that financial targets have a significant positive effect on the potential for fraud in financial statements.
The financial stability of a company could be measured by its ability to pay interest expenses, the timely repayment of loans, and the ability to pay dividends (Evana et al. 2019). Financial stability shows that a company’s financial sources are in a stable state (Rimadanti et al. 2022). There are cases when the financial stability of a company can worsen, thus creating pressure on managers. In this situation, there is a risk that managers will resort to different ways to try to improve the state of the company. Managers’ actions can lead to fraud because they will do their best, including manipulating data in financial statements (Fathmaningrum and Anggarani 2021).
External pressure is part of the pressure element of the Fraud Pentagon Theory. One of the external pressures that a company often faces is given by the loans it takes out for the normal conduct of business (Farida et al. 2022). When a company mainly uses external financing sources in its current activity, it exposes itself to a much higher risk of loss. This situation creates pressure for the company, possibly motivating managers to resort to manipulating the results to convince creditors that the company’s debts can be paid (Utami and Pusparini 2019).
Based on the above explanations, the study proposed the following hypothesis:
H1: 
In the Romanian context, at the level of the Bucharest Stock Exchange, pressures have a positive effect on fraudulent financial reporting.
In many cases, companies are the ones that do not pay close attention to the internal control system. Ineffective monitoring by the company provides the opportunity to commit fraudulent acts (Fuad et al. 2020). Increasing the supervision and monitoring ineffectiveness of the company could determine an increase in the probability that the financial statements will be defrauded (Fathmaningrum and Anggarani 2021).
In turn, the selection of the audit firm plays an important role in terms of audit quality. It is often suggested that the financial statements audited by an auditor who is part of the Big 4 are more credible or reliable compared to those audited by a non-Big-4 auditor. In this case, it is assumed that auditors who are members of the Big 4 have a higher reputation, which gives them confidence from different stakeholders (Utami and Purnamasari 2021).
Drawing on this rationale, the study formulates the following hypothesis:
H2: 
In the Romanian context, at the level of the Bucharest Stock Exchange, opportunity has a positive effect on fraudulent financial reporting.
Rationalization is another element of the Fraud Pentagon that could encourage fraud in a company’s financial statements (Crowe 2011). This factor explains a person’s behavior by giving reasonable reasons, replacing them with real ones (Puspitosari 2022). It is reasoning that leads the fraudster to justify his actions (Bagus et al. 2019; Nurcahyono and Hanum 2023). In this study, rationalization is measured through a change of auditor. Previous studies have argued that changing the auditor contributes positively to the distorted reporting of the company’s financial situation (Husmawati et al. 2017; Ulfah et al. 2017).
Based on the above, the following hypothesis is proposed:
H3: 
In the Romanian context, at the level of the Bucharest Stock Exchange, rationalization has a positive effect on fraudulent financial reporting.
Competence reflects a person’s ability to achieve their goals. In this study, competence is represented by the change of directors. According to Septriani and Handayani (2018), companies that commit fraud often resort to changing directors. The change of directors may indicate political motives aimed at replacing the previous board, often signaling shifts in control or influence within the company (Andriani et al. 2022; Feleagă et al. 2023). (Ulfah et al. 2017) demonstrate that competence has a positive effect in detecting fraudulent financial reports.
Considering the above, the following hypothesis can be formulated:
H4: 
In the Romanian context, at the level of the Bucharest Stock Exchange, capacity has a positive effect on fraudulent financial reporting.
Arrogance is a personal characteristic that entails a superior attitude (Nanda et al. 2019). This characteristic could lead a person within the company to commit fraudulent acts, assuming no one will be held accountable (Hidayah and Saptarini 2019). Many studies suggest the idea that the CEO’s photo in the company’s annual report may be a way to measure arrogance (Yusof 2016; Puspitha and Yasab 2018; Nizarudin et al. 2023). The frequency of the CEO’s visual appearance in the company’s annual report may reflect an intention to convey superiority and assert their dominant position within the organization (Crowe 2011). Through their studies, Tessa and Harto (2016) and Yusof (2016) demonstrated that arrogance significantly affects financial reporting.
Building on the previous considerations, the following hypothesis can be formulated:
H5: 
In the Romanian context, at the level of the Bucharest Stock Exchange, arrogance has a positive effect on fraudulent financial reporting.
Starting with the hypotheses proposed for testing, the analysis seeks to observe if the five elements of the Fraud Pentagon have a positive effect on fraudulent financial reporting.
In light of the growing academic interest in the Fraud Pentagon Theory, this study draws on previous empirical approaches regarding its testing in various contexts. By critically examining existing methodologies and findings, the research aims to identify both common patterns and gaps in the previous research literature. This analysis provides the foundation for formulating the above five research hypotheses tailored to the Romanian market context, where, to our knowledge, no empirical validation of the theory has been conducted to date.
Evana et al. (2019) examined the importance of the factors summarized in the Fraud Pentagon in the manipulation of financial statements. Their sample consisted of 57 companies listed on the Indonesian Stock Exchange from 2013–2015. The independent variables were tailored based on the five factors in the Fraud Pentagon. For example, pressure was measured based on financial stability, external pressure, and financial target, while opportunity was observed considering the nature of the industry. For rationalization, total accruals formed the basis of its proxy. Capability was expressed by the change of directors, and arrogance was observed considering the ownership of management. The dependent variable, fraudulent financial reporting, was calculated using the F-score. The findings argued that only rationalization (total accruals) and capability (the change of directors) positively affect fraudulent financial reporting.
Hidayah and Saptarini (2019) employed panel regression analysis on a sample of 33 banking institutions over the 2013–2017 period. Their findings highlight the significant influence of pressure arising from unmet financial targets and managerial capability, particularly when associated with changes in executive leadership, on the manipulation of financial outcomes.
Similarly, Ramadhan (2020) examined 144 publicly traded firms over the 2017–2018 period using root cause analysis and the Fraud Pentagon Matrix approach. His results emphasized pressure, rationalization, and capability as the most influential factors in facilitating fraudulent behavior. In another contribution, Devi et al. (2021) analyzed 20 state-owned enterprises between 2014 and 2019 and assessed the relationship between the Fraud Pentagon variables and fraudulent reporting, using F-score calculations alongside factor analysis and simple linear regression. Their findings confirm that all five dimensions (pressure, opportunity, rationalization, competence, and arrogance) play a role in influencing financial statement fraud.
Expanding the geographical scope of the analysis, Fathmaningrum and Anggarani (2021) conducted a comparative study of 120 listed companies in Indonesia and Malaysia. They used the modified Jones model to detect fraudulent reporting and applied multiple regression analysis to test ten independent variables. Their study concluded that pressure and opportunity were the most impactful factors in both countries, reinforcing the theory’s cross-border applicability.
Other research efforts have produced more nuanced findings. Rukmana (2021), examining 66 listed companies from 2012 to 2016, observed that, while most Fraud Pentagon elements were significant, the competence (ability) of the fraud perpetrator did not show a measurable effect on fraudulent reporting. Andriani et al. (2022), focusing on companies sanctioned by Indonesia’s Financial Services Authority (OJK), demonstrated that pressure was a dominant driver of financial statement manipulation among 62 firms.
However, the utility of the Fraud Pentagon Model has not gone unchallenged. Tjahjani et al. (2022) provided contrasting evidence, reporting that none of the five Fraud Pentagon dimensions significantly influenced financial reporting fraud in their sample of Indonesian firms, suggesting contextual limitations to the model’s predictive validity. Meanwhile, Joshi et al. (2022) found that pressure and rationalization were particularly significant in prompting financial manipulation, and Yanti et al. (2024) further argued for the importance of including capability alongside pressure and opportunity when assessing the risk of fraudulent reporting.
These diverse findings across studies underscore both the relevance and limitations of the Fraud Pentagon Theory, highlighting the need for continued empirical validation in various national and institutional settings. A summary of the key studies discussed is presented in Table 2.
While prior research on fraud detection using the Fraud Pentagon Model has been concentrated in Southeast Asia, studies from Europe and North America offer useful contrasts. For instance, research on US firms highlights the influence of regulatory enforcement and audit committee effectiveness in moderating fraud risk, especially under the Sarbanes–Oxley framework (Cordis 2024; Chimonaki et al. 2023). In European contexts, studies conducted in countries such as Germany, the UK, and the Nordic region emphasize the role of institutional trust, transparency norms, and ownership structures in shaping fraud vulnerabilities (Ramos et al. 2024; Edelbacher 2018). The comparison between these diverse research insights and contexts shows that, while fraud drivers may be universally defined, their relevance and manifestations differ across jurisdictions.
The effectiveness and relevance of the Fraud Pentagon Theory’s components are not uniform across all economic environments. In more mature markets with strong regulatory enforcement and robust corporate governance, opportunity and rationalization tend to be more prominent fraud drivers, often influenced by complex financial instruments or pressures to meet investor expectations (Cordis 2024). In contrast, in emerging or transitional economies, where institutional enforcement may be weaker and corporate governance structures are still evolving, pressure-related factors such as financial instability and unmet performance targets may play a more important role (Chimonaki et al. 2023; Bătae et al. 2021). Cultural attitudes toward authority, compliance, and transparency can shape how indicators like arrogance or capability manifest in practice. Considering such variations across various contexts, fraud risk indicators should be interpreted within the broader context of national governance practices and stakeholder norms.
Considering the methods previously used in established research applying the Fraud Pentagon Theory, this study aims to test the theory in the Romanian context. Similar to studies by Bawekes et al. (2018), Akbar (2017), and Annisya and Asmaranti (2016), this research uses financial target, financial stability, and external pressure to assess the pressure dimension. The opportunity factor is investigated through external auditor quality (Apriliana and Agustina 2017) and industry-specific characteristics, while rationalization is captured by auditor change, following the model proposed by Fathmaningrum and Anggarani (2021). Changes in company directors serve as proxies for capability (Fitriyah and Novita 2021), and the frequency of CEO appearances in annual reports accounts for arrogance, following the reasoning of Hidayah and Saptarini (2019).
While these variable selections are grounded in prior international studies, the present research offers a new empirical perspective by applying them to Romanian companies listed on the Bucharest Stock Exchange, an emerging European market with distinct regulatory, economic, and corporate governance characteristics. To our knowledge, this is among the first studies to empirically validate the Fraud Pentagon Theory in the Romanian context using the Dechow F-score as a measure of fraudulent financial reporting (Richardson et al. 2005; Dechow et al. 2011), thereby addressing a significant gap in the literature and offering insights that may inform both regional policy and broader comparative fraud analysis.

3. Research Methodology

This research investigates the impact of the Fraud Pentagon Theory on the likelihood of fraudulent financial reporting among Romanian companies listed on the Bucharest Stock Exchange during the 2017–2021 period. By examining the individual influence of each of the five fraud determinants (pressure, opportunity, rationalization, capability, and arrogance), the study utilizes the F-score model (Richardson et al. 2005; Dechow et al. 2011) to quantify the probability of financial misreporting. The methodological framework involves a structured statistical approach to define the target population, select the sample, and apply relevant models based on established variables in prior literature. The chosen time frame reflects the period in which audited and standardized financial data were consistently available, beginning with the implementation of Law No. 162/2017, which introduced enhanced audit obligations for Romanian companies. The end point, 2021, ensures completeness and comparability of financial reports, as data beyond this year were not fully published or verified at the time of analysis.

3.1. Target Population and Sample Data

The target population was represented by all companies listed on the Bucharest Stock Exchange (BSE) that are subject to the Law No. 162/2017 issued by the Romanian Parliament regarding the mandatory audit of annual financial statements and annual consolidated financial statements and amending certain regulatory acts, published in the Official Gazette of Romania No. 548/12 July 2017. In Romania, the principal capital market regulated by law is the Bucharest Stock Exchange, while the fight against financial reporting fraud is supported by a combination of national regulatory bodies, professional associations, and international frameworks. The Romanian Financial Supervisory Authority (ASF) and the National Agency for Fiscal Administration (ANAF) play key roles in monitoring compliance and investigating financial irregularities. The Chamber of Financial Auditors of Romania (CAFR) and the Body of Expert and Licensed Accountants of Romania (CECCAR) work to uphold ethical and professional standards among auditors and accountants, offering training, licensing, and disciplinary oversight. Romania participates in broader anti-fraud initiatives such as European Anti-Fraud Office (OLAF) investigations and adheres to financial transparency practices promoted by the European Securities and Markets Authority (ESMA). Together, these institutions form a preventive framework that promotes stronger internal controls, transparent reporting, and corporate accountability. However, ongoing challenges in enforcement capacity and institutional reform highlight the need for empirical research to uncover vulnerabilities and guide effective policy development.
The analyzed sample includes only companies listed on the regulated market. From the total number of 83 listed companies during the analyzed period (2017–2021), those in the financial banking, insurance, and financial intermediation sectors were excluded due to their use of different financial reporting standards, as well as companies with incomplete data. Based on these criteria, the final sample consisted of 62 listed companies, with data collected from their financial statements over the review period, resulting in a total of 310 observations (see Table 3). This sample represents approximately 75% of the eligible population, ensuring a high degree of representativeness for the analysis and enhancing the generalizability of the findings within the context of Romanian capital markets.
Regarding the activity field, the analyzed sample includes companies operating in different activity fields, such as the manufacturing industry (68%), service entities (19%), construction entities (7%), and trade entities (6%).

3.2. Analyzed Variables and Proposed Econometric Models

Starting from the proposed research hypotheses, the dependent variable is represented by fraudulent financial reporting. Also, starting from the literature, we included in the analysis some independent variables, such as: financial target, financial stability, external pressure, effective monitoring, quality of external auditor, change of auditors, change of directors, and frequency of CEO photos.
Each variable is described in Table 4.
To test and validate the proposed research hypotheses, multiple linear regression analysis was used to test the relationship between the proposed dependent variable and the independent variables described in Table 4:
FFR = β0 + β1·ROA + β2·ACHANGE + β3·LEV + β4·BIG4 + β5·NI + β6·CHIA + β7·DCHANGE + β8·CEOPIC + ε
where:
  • βi,i=0,…,8 represents the coefficients of the proposed model associated with each independent variable;
  • ε represents the residual part or the error term of the econometric model, and the dependent and independent variables are presented in Table 4.
In order to calculate the values for each proposed variable, the data were collected from the annual financial statements of the companies included in the sample. For these companies, data were collected manually from the annual financial reports, and their analysis was carried out using the SPSS 25.0 statistical program.

4. Results and Discussion

After performing the data analysis, the main results include the descriptive statistics, correlation matrix, coefficient estimates, and robustness tests. In this study, descriptive statistical analysis was performed in order to provide a description of the variables used in the study, given the mean, the minimum value, the maximum value, and their standard deviation. The data obtained are summarized in Table 5.
Table 5 presents the descriptive statistics for the variables included in the analysis. The table offers valuable insights into the financial and governance characteristics of Romanian listed companies during the 2017–2021 period and highlights patterns and contextual factors relevant to the application of the Fraud Pentagon Theory in Romania.
The dependent variable (FFR) ranges from 0 to 19.14, with a mean of 0.994 and a standard deviation of 2.299. FFR values above 1 suggest that financial statements may have been manipulated by company management to gain financial advantages. The first independent variable, ROA, which measures the company’s return on assets, has an average of 0.028, indicating that Romanian listed companies achieved an average profitability of 2.80% during the 2017–2021 period. The second independent variable, financial stability (ACHANGE), has an average value of 0.065, reflecting an average asset growth of 6.5%. The financial leverage indicator (LEV) shows a mean of 0.495, suggesting a moderate level of indebtedness, where total debts are nearly equal to total equity. A higher leverage ratio may negatively impact a company’s financial stability, increasing pressure and risk. The use of borrowed resources in the normal course of business may affect the long-term state of the company and the confidence of stakeholders in the investment process.
The type of auditor (BIG4) has an average value of 0.246, indicating that 24.6% of the Romanian companies in the sample had their financial statements audited by one of the Big 4 audit firms. This may suggest a higher perceived credibility of financial reports among stakeholders. However, the involvement of a Big 4 auditor does not guarantee reliability, as there have been instances where audits conducted by these firms were later found to be flawed.
The average for director change (DCHANGE) is 0.012, showing that only 1.2% of the companies experienced a change in leadership during the analyzed period. Infrequent director changes may reflect managerial stability or, conversely, stress-related turnover under challenging conditions.
The CEO photo variable (CEOPHOTO) ranges from 0 to 1, indicating that at most one image of the CEO appeared in a company’s annual report.
Table 6 presents the correlation coefficients between the variables included in the model specified in Equation (1).
As shown by the Pearson correlation, there is a significant relationship between the independent variable (ROA) and the dependent variable (FFR), measured by the F-score. Additionally, several independent variables included in the model from Equation (1) exhibit significant intercorrelations, which may enhance their combined influence on the variance of FFR. To further assess the presence of multicollinearity among the independent variables, we conducted a variance inflation factor (VIF) analysis. The results indicated that all VIF values were below the commonly accepted threshold of 10, suggesting that multicollinearity is not a concern in this model and the individual effects of predictors can be further interpreted.
The results from testing the validity of the proposed multiple linear regression model are presented in Table 7.
Table 7 shows that the results support the relevance and significance of the model proposed in this study, with a significance level of 0.03 (threshold of significance is 0.03 < 0.05). This suggests that the model is appropriate for assessing fraud risk among companies listed on the Bucharest Stock Exchange.
The parameter estimates for the variables included in the model from Equation (1) are presented in Table 8.
As shown in Table 8, the first variable, measured by ROA, has a coefficient of 0.224, a t-value of 3.231, and a significance level of 0.001 (<0.05). This indicates that return on assets has a statistically significant positive effect on fraudulent financial reporting among Romanian listed companies. This positive relationship may be explained by unmet managerial expectations regarding company performance or by the possibility that high ROA values create opportunities or incentives for managers to manipulate financial statements.
The second variable, financial stability, measured by ACHANGE, has a coefficient of −0.157, a t-value of −2.450, and a significance level of 0.015 (<0.05), indicating a statistically significant negative relationship with fraudulent financial reporting. Despite the negative coefficient, this suggests that lower financial stability (i.e., higher instability) is associated with a greater likelihood of financial reporting fraud. These findings are consistent with the results of Nugroho et al. (2020), Fathmaningrum and Anggarani (2021), and Tjahjani et al. (2022). The influence of financial stability on fraudulent reporting may stem from attempts to obscure declining asset values or broader instability, which can signal increased financial risk and pressure within the company.
External pressure, measured by financial leverage, has a coefficient of 0.027 and a significance level of 0.690, which exceeds the conventional threshold of 0.05. Therefore, it can be concluded that external pressure does not have a statistically significant effect on fraudulent financial reporting in Romanian listed companies. This finding is consistent with the results reported by Nurbaiti and Hanafi (2017), Nugroho et al. (2020), and Tjahjani et al. (2022). The lack of a significant relationship may suggest that debt levels alone do not serve as a direct incentive for companies to manipulate financial statements.
Of the three variables representing pressure (ROA, ACHANGE, LEV) only two (ROA and ACHANGE) have a significant effect on fraudulent financial reporting, based on the results obtained. Therefore, the first hypothesis (H1) is validated, indicating that pressure is a key factor influencing Romanian listed companies to manipulate financial results. This finding aligns with the study by Akbar (2017), which also found that companies listed in Indonesia tend to engage in fraudulent reporting due to the pressures they face.
The proxies for opportunity, the nature of the industry, and the quality of the external auditor did not have a significant effect on fraudulent financial reporting among Romanian companies during the analyzed period, as indicated by a significance level of 0.476. This suggests that audits conducted by Big 4 firms do not necessarily lead to the detection of financial statement fraud and that auditor affiliation is not a reliable indicator of fraud prevention. The effectiveness of fraud detection is more closely linked to the auditor’s professional skepticism than to the reputation of the audit firm. Given that neither of the two variables (effective control and auditor quality) showed statistical significance (p > 0.05), the second hypothesis (H2) is rejected.
For the rationalization variable, change of auditors, a coefficient of −0.036 and a t-value of −0.575 were obtained, with a significance level of 0.566, well above the accepted threshold of 0.05. This indicates that hypothesis H3 is rejected. Thus, the rationalization factor from the Fraud Pentagon Theory did not significantly influence fraudulent reporting during the analyzed period. This suggests that long-term auditor–client relationships did not lead to familiarity risks or impair auditor independence in the Romanian context. Similarly, the change of directors was found to have no significant effect on fraudulent financial reporting, leading to the rejection of hypothesis H4, which proposed that ability/competence influences the presentation of financial position and performance. Although prior studies (Utami and Pusparini 2019; Hidayah and Saptarini 2019) have associated director changes with organizational stress and increased risk of manipulation, this effect was not confirmed in the Romanian market.
The final variable analyzed, the frequency of CEO appearances, has a significance level exceeding the 0.05 threshold. Consequently, hypothesis H5, which posits that arrogance has a positive effect on fraudulent financial reporting, is rejected. The results indicate that the frequent appearance of the CEO’s image in annual reports cannot be considered a key indicator for detecting financial statement fraud.
Reflecting on the results from a country-level perspective, the application of the Fraud Pentagon Theory in the Romanian context reveals a mixed level of alignment with findings from international studies. In Romania, pressure (particularly through financial targets and financial stability) was found to have a statistically significant impact on financial statement fraud, supporting the hypothesis that companies under financial pressure are more prone to manipulation. This is consistent with research from Indonesia (Akbar 2017; Nugroho et al. 2020), Malaysia (Fathmaningrum and Anggarani 2021), and other emerging markets, where pressure and instability have been strongly linked to financial misreporting. However, in contrast to other studies (Farida et al. 2022), external pressure measured by leverage was not a significant factor in Romania, suggesting that the role of debt may vary depending on the financial maturity and corporate governance standards of each national context.
Other dimensions of the Fraud Pentagon Theory yielded results in Romania that diverge from international evidence. For instance, opportunity (represented by the quality of external auditors and nature of the industry) did not significantly influence fraudulent reporting, challenging assumptions commonly supported in studies from Southeast Asia (Apriliana and Agustina 2017; Evana et al. 2019). Rationalization (auditor change), capability (director change), and arrogance (CEO photo frequency) were also found to be statistically insignificant in the Romanian sample. These findings differ from studies in Indonesia, where changes in leadership or auditors were found to affect fraud likelihood (Nugroho et al. 2020; Tessa and Harto 2016). For instance, Haqq and Budiwitjaksono (2020) noted the role of auditor changes and professional competence as risk factors in fraud detection, while studies such as those by Rimadanti et al. (2022) emphasized arrogance as a relevant signal in manipulated financial statements. Compared to other EU markets, such as Poland, Slovakia, or the Czech Republic, similar studies have found greater significance for opportunity and rationalization-related fraud drivers (Sylwestrzak 2022; Mottinger 2024), indicating that the scale and impact of fraud dimensions may vary substantially across neighboring economic contexts. The Romanian results, therefore, suggest that institutional and cultural differences, such as governance norms, market maturity, and stakeholder expectations, may moderate the effectiveness of certain fraud indicators (Vancea et al. 2021; Aivaz et al. 2024). This divergence highlights the novelty and importance of regional empirical validation, as it demonstrates that, while pressure appears to be a consistent fraud driver globally, other Fraud Pentagon components may have context-dependent significance.

4.1. Robustness Test—Using Panel Data Analysis for Unobserved Heterogeneity and Multicollinearity

Starting from the nature of the analyzed sample, which constitutes a balanced panel dataset, this study employs panel data analysis to examine whether temporal and cross-sectional (firm-level) effects influence the relationship between the independent variables and the dependent variable, fraudulent financial reporting (Jaba et al. 2017).
Firstly, using the Hausman test (Jaba et al. 2016b), we determined the appropriate type of panel model—fixed effects (FEs) or random effects (REs). The results are presented in Table 9.
Based on the results presented in Table 9, we conclude that the random effects model is appropriate for our analysis. The random effects model decomposes the error term into three components: one that exhibits no autocorrelation either across individuals or over time, an individual-specific effect, and a time-specific effect. These components are assumed to be uncorrelated with each other and with the explanatory variables (Jaba et al. 2016a).
The estimated parameters of the panel model with random effects are shown in Table 10.
Starting from the model proposed in Equation (1), and following the panel data analysis using the random effects approach, the estimated parameters and associated statistics are presented in Table 10. The results are comparable to those in Table 8 and indicate that only ROA and ACHANGE have a statistically significant influence on fraudulent financial reporting (FFR).

4.2. Reflections on the Implications of the Study

The findings of this study offer practical implications for policymakers and regulators in Romania aiming to enhance fraud detection and prevention frameworks. The significant influence of pressure-related factors, specifically financial performance and stability, suggests that regulatory bodies should prioritize monitoring indicators linked to financial stress and performance volatility when assessing fraud risk. Tools such as early warning systems based on financial ratios could be developed to flag at-risk firms. Additionally, since opportunity, rationalization, capability, and arrogance were not statistically significant in this context, Romanian regulators may consider revisiting the effectiveness of current governance policies, internal control requirements, and audit quality standards. Strengthening board oversight, improving transparency in management changes, and increasing auditor independence may help close the gap between formal regulations and actual detection capacity. By aligning policy responses with empirically validated risk factors, authorities can better allocate resources and adapt enforcement strategies to the specific characteristics of Romania’s corporate environment.

4.3. Research Limitations

The limitations of this study stem from the inherent complexity of the topic of fraudulent financial reporting and the application of the Fraud Pentagon Theory. While the research is based on a focused sample of available data for 62 companies over the 2017–2021 period, this targeted approach offers a clear and context-specific understanding of fraudulent reporting dynamics within Romania. However, to enhance the generalizability and depth of future studies, extending the time frame or incorporating additional independent variables may yield new insights. The use of quantitative methods in this paper lays a strong foundation for future research to build upon by integrating qualitative approaches to capture managerial behavior and organizational culture.
In another vein, the limitations of this study also lie in the operationalization of certain Fraud Pentagon variables. For instance, using the frequency of CEO pictures as a proxy for arrogance, while supported by prior literature, may not fully capture executive dominance within the Romanian corporate context due to differing cultural and reporting practices. Similarly, the use of auditor change as a proxy for rationalization is limited by its potential to reflect governance reforms or concerns about audit quality, rather than intent to justify fraudulent actions. Future research should consider alternative indicators, such as CEO compensation structures, governance scoring metrics, or audit committee characteristics, to reflect internal control dynamics and managerial behavior depending on country-specific scenarios.

5. Conclusions

The application of the Fraud Pentagon Theory to Romanian companies listed on the Bucharest Stock Exchange revealed that not all five determinants significantly influence fraudulent financial reporting. Specifically, pressure-related factors such as financial performance (ROA) and financial stability (ACHANGE) showed a statistically significant effect, consistent with findings in other emerging markets. However, other components of the theory, including opportunity, rationalization, capability, and arrogance, did not exhibit significant impacts in the Romanian environment, indicating potential contextual differences in how fraud risk manifests.
Based on the results obtained, it can be concluded that financial targets posed challenges to the financial reporting practices of listed companies during the 2017–2021 period. Additionally, financial stability was associated with uncertainties in how company performance was reported, potentially influencing investment decisions. External pressure was found to have no significant effect on fraudulent financial reporting. The quality of the external auditor, whether from a Big 4 or non-Big-4 firm, also had no significant impact. Similarly, changes in the board of directors had no measurable effect on fraudulent financial reporting. Lastly, the frequency of CEO appearances in annual reports was found to be irrelevant to the likelihood of financial statement fraud. These findings reinforce the critical role of Romanian regulatory and professional bodies in fraud prevention, while also highlighting enforcement gaps that empirical studies such as this can help identify and address through evidence-based policy recommendations.
The findings of this study underscore the importance of contextualizing fraud risk analysis within specific national environments. The Romanian case highlights that, among the five elements of the Fraud Pentagon Theory, only particular insights of pressure significantly influence fraudulent financial reporting. This suggests that institutional, cultural, and market-specific factors may moderate the relevance of other fraud indicators. The findings validate the need for regional empirical studies and contribute to a more nuanced understanding of how fraud risks manifest in different economic contexts.

Author Contributions

Conceptualization, G.B. and I.-B.R.; methodology, G.B., I.-B.R. and I.A.; software, M.E.R.; validation, I.-B.R. and I.A.; formal analysis, G.B.; investigation, M.E.R.; resources, M.E.R.; data curation, G.B.; writing—original draft preparation, G.B.; writing—review and editing, M.E.R. and I.M.; visualization, I.A. and I.M.; supervision, I.-B.R. and I.M.; project administration, I.-B.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Risks 13 00102 g001
Figure 1. Fraud Pentagon Theory by Crowe (Source: adapted after Crowe (2011)).
Figure 1. Fraud Pentagon Theory by Crowe (Source: adapted after Crowe (2011)).
Risks 13 00102 g001
Table 1. The research model proposed in the study.
Table 1. The research model proposed in the study.
Fraudulent Financial Reporting
(FFR)		Pressure (P)
  • Financial target
  • Financial stability
  • External pressure
Opportunity (O)
  • External auditor quality
  • Nature of industry
Rationalization (R)
  • Change of auditor
Capability/Competence (C)
  • Change of director
Arrogance (A)
  • Number of CEO’s pictures
(Source: authors’ processing).
Table 2. Studies that tested the Pentagon Theory.
Table 2. Studies that tested the Pentagon Theory.
Authors and Year of the Research StudyAnalyzed PeriodSample AnalyzedFFRCountryFactors from Fraud Pentagon
(P)(O)(R)(C)(A)
(Evana et al. 2019)2013–201559 companies, 177 observationsF-scoreIndonesia⮽⮽☑☑⮽
(Hidayah and Saptarini 2019)2013–201738 banking companiesF-score
Panel data regression analysis		Indonesia☑⮽⮽☑⮽
(Ramadhan 2020)2017–2018144 companiesRCA-FPIndonesia☑⮽☑☑⮽
(Devi et al. 2021)2014–201920 companiesF-ScoreIndonesia☑☑☑☑☑
(Fathmaningrum and Anggarani 2021)2017–2018118 companiesModified Jones, multiple linear regression analysisIndonesia, Malaysia☑☑⮽⮽⮽
(Rukmana 2021)2012–201666 companiesPanel data regression analysisIndonesia☑☑☑⮽☑
(Andriani et al. 2022)2015–201962 companiesLogistic regression analysis and discriminant analysisIndonesia☑⮽⮽⮽⮽
(Tjahjani et al. 2022)2017–2019111 companiesLogistic regression analysisIndonesia⮽⮽⮽⮽⮽
(Joshi et al. 2022)2019–2021126 companies, IDXLogistic regression analysisIndonesia☑⮽☑⮽⮽
(Yanti et al. 2024)2017–2021131 companiesMultiple linear regression analysisIndonesia☑☑⮽☑⮽
(Source: authors’ processing).
Table 3. The sample analyzed and the total observations.
Table 3. The sample analyzed and the total observations.
YearObservations
201762
201862
201962
202062
202162
Total sample firm/year observations310
(Source: authors’ processing).
Table 4. The variables proposed in the study.
Table 4. The variables proposed in the study.
Dependent VariableCalculationReference
Fraudulent financial reporting (FFR)Dechow F-score
F-Score = Accrual quality + Financial Performance 		Richardson et al. (2005)
Dechow et al. (2011)
Independent variablesCalculationReference
Return on assets (ROA)Net Profit/Total AssetBawekes et al. (2018)
Financial stability (ACHANGE)(Total Assett − Total Assett−1)/Total AssettAkbar (2017)
External pressure (LEV)Total debts/Total assetsAnnisya and Asmaranti (2016)
External auditor quality (BIG4)Dummy variable: code 1 if the company uses the audit services of the Big Four, and code 0 if the company does not use the audit service of the Big FourApriliana and Agustina (2017)
Nature of industry (NI)(Receivablest/Salest) − (Receivablest−1/Salest−1)
Changes in auditor (CHIA)Dummy variable: code 1 for companies that implement change in auditors and code 0 for companies that do not carry out a change in auditorsFathmaningrum and Anggarani (2021)
Change of directors (DCHANGE)Dummy variable: code 1 for companies that carry out a change in directors and code 0 for companies that do not change directorsFitriyah and Novita (2021)
Number of CEO’s pictures (CEOPIC)Total photos of CEOs emblazoned in an annual report of the companyHidayah and Saptarini (2019)
(Source: authors’ processing).
Table 5. Descriptive statistics.
Table 5. Descriptive statistics.
VariablesNMinimumMaximumMeanStd. Deviation
FFR2480.00019.1400.9942.299
ROA248−0.8101.2600.0280.133
ACHANGE248−0.5801.9100.0650.232
LEV2480.0205.6800.4950.707
BIG42480 (24.6%)1 (75.4%)--
NI248−4.7809.7300.0760.997
CHIA2480.0001.0000.1050.307
DCHANGE2480.0001.0000.0120.110
CEOPIC2480.0001.0000.0320.177
Valid N248
(Source: authors’ processing in SPSS 25.0).
Table 6. Correlation between the variables used in the study.
Table 6. Correlation between the variables used in the study.
FFRROAACHANGELEVBIG4NICHIADCHANGECEOPIC
FFRPearson Correlation10.191 **−0.122−0.041−0.0510.071−0.028−0.023−0.038
Sig. (2-tailed) 0.0030.0550.5230.4230.2680.6600.7180.551
N248248248248248248248248248
ROAPearson Correlation0.191 **10.172 **−0.378 **0.0520.140 *−0.035−0.0120.002
Sig. (2-tailed)0.003 0.0070.0000.4150.0270.5840.8450.973
N248248248248248248248248248
ACHANGEPearson Correlation−0.1220.172 **1−0.0570.065−0.075−0.061−0.0510.016
Sig. (2-tailed)0.0550.007 0.3750.3070.2390.3370.4210.808
N248248248248248248248248248
LEVPearson Correlation−0.041−0.378 **−0.0571−0.0960.001−0.029−0.063−0.019
Sig. (2-tailed)0.5230.0000.375 0.1310.9860.6540.3210.767
N248248248248248248248248248
BIG4Pearson Correlation−0.0510.0520.065−0.09610.052−0.043−0.0630.320 **
Sig. (2-tailed)0.4230.4150.3070.131 0.4180.5040.3220.000
N248248248248248248248248248
NIPearson Correlation0.0710.140 *−0.0750.0010.05210.084−0.066−0.009
Sig. (2-tailed)0.2680.0270.2390.9860.418 0.1850.3000.893
N248248248248248248248248248
CHIAPearson Correlation−0.028−0.035−0.061−0.029−0.0430.0841−0.038−0.062
Sig. (2-tailed)0.6600.5840.3370.6540.5040.185 0.5530.327
N248248248248248248248248248
DCHANGEPearson Correlation−0.023−0.012−0.051−0.063−0.063−0.066−0.0381−0.020
Sig. (2-tailed)0.7180.8450.4210.3210.3220.3000.553 0.752
N248248248248248248248248248
CEOPICPearson Correlation−0.0380.0020.016−0.0190.320 **−0.009−0.062−0.0201
Sig. (2-tailed)0.5510.9730.8080.7670.0000.8930.3270.752
N248248248248248248248248248
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
Table 7. Validation of the model from Equation (1).
Table 7. Validation of the model from Equation (1).
ModelSum of SquaresdfMean SquareFSig.
1Regression24,630,08383078.7602.1770.030
Residual338,034,4162391414.370
Total362,664,499247
Dependent Variable: F-SCORE;Predictors: (Constant), ROA, ACHANGE, LEV, BIG4, NI, CHIA, DCHANGE, CEOPIC. (Source: authors’ processing in SPSS 25.0).
Table 8. Parameter estimates.
Table 8. Parameter estimates.
Model from Equation (1)Unstandardized
Coefficients		Standardized CoefficientstSig.
βStd. Errorβ
1(Constant) 9.012 3.732 2.415 0.017
ROA 64.528 19.975 0.224 3.231 0.001
ACHANGE −25.932 10.585 −0.157 −2.450 0.015
LEV 1.473 3.690 0.027 0.399 0.690
BIG4 −4.222 5.914 −0.048 −0.714 0.476
NI 1.181 2.460 0.031 0.480 0.632
CHIA −4.527 7.876 −0.036 −0.575 0.566
DCHANGE −10.293 22.045 −0.029 −0.467 0.641
CEOPIC −4.964 14.289 −0.023 −0.347 0.729
Dependent Variable: FFR. (Source: authors’ processing in SPSS 25.0).
Table 9. Hausman test results.
Table 9. Hausman test results.
Coefficients
Variable(b)
Fixed		(B)
Random		(b-B)
Differences		Sqrt(diag(V_b-V_B))
S.E.
ROA92.55064.56227.98916.775
ACHANGE−23.778−25.9332.1556.191
LEV−6.9941.446−8.44020.112
BIG42.100−4.2376.33824.442
NI0.6111.171−0.5600.817
CHIA−8.099−4.697−3.4024.517
DCHANGE−14.892−10.519−4.37312.085
b = consistent under H0 (RE) and Ha (FE); B = inconsistent under Ha (FE), efficient under H0 (RE). Chi2 = 7.65. Prob > Chi2 = 0.3641. (Source: authors’ processing).
Table 10. Parameter estimates for the panel model with random effects.
Table 10. Parameter estimates for the panel model with random effects.
Random Effects Model Coef.Std. ErrorzP > |z|
(Constant)9.0973.7592.420.016
ROA64.56219.8863.250.001
ACHANGE−25.93310.558−2.460.014
LEV1.4463.7190.390.477
BIG4−4.2375.962−0.710.477
NI1.1712.4550.480.633
CHIA−4.6977.876−0.600.551
DCHANGE−10.51922.043−0.480.633
CEOPIC−5.05814.414−0.350.726
Dependent Variable: FFR. R2: within = 0.097; between = 0.016; overall = 0.068. Number of obs. = 248; number of groups = 62. Sigma_u = 2.865; Sigma_e = 37.456; rho = 0.006. (Source: authors’ processing).
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Burlacu, G.; Robu, I.-B.; Anghel, I.; Rogoz, M.E.; Munteanu, I. The Use of the Fraud Pentagon Model in Assessing the Risk of Fraudulent Financial Reporting. Risks 2025, 13, 102. https://doi.org/10.3390/risks13060102

AMA Style

Burlacu G, Robu I-B, Anghel I, Rogoz ME, Munteanu I. The Use of the Fraud Pentagon Model in Assessing the Risk of Fraudulent Financial Reporting. Risks. 2025; 13(6):102. https://doi.org/10.3390/risks13060102

Chicago/Turabian Style

Burlacu, Georgiana, Ioan-Bogdan Robu, Ion Anghel, Marius Eugen Rogoz, and Ionela Munteanu. 2025. "The Use of the Fraud Pentagon Model in Assessing the Risk of Fraudulent Financial Reporting" Risks 13, no. 6: 102. https://doi.org/10.3390/risks13060102

APA Style

Burlacu, G., Robu, I.-B., Anghel, I., Rogoz, M. E., & Munteanu, I. (2025). The Use of the Fraud Pentagon Model in Assessing the Risk of Fraudulent Financial Reporting. Risks, 13(6), 102. https://doi.org/10.3390/risks13060102

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