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Abstract

We examine 2,190 SEC Accounting and Auditing Enforcement Releases (AAERs) issued between 1982 and 2005. We obtain a comprehensive sample of firms that are alleged to have misstated their financial statements. We examine the characteristics of misstating firms along five dimensions: accrual quality, financial performance, non-financial measures, off-balance sheet activities, and market-based measures. We compare misstating firms to themselves during non-misstatement years and misstating firms to the broader population of all publicly listed firms. We find that managers appear to be hiding diminishing performance during misstatement years. We find that accruals are high and that misstating firms have a greater proportion of assets with valuations that are more subject to managerial discretion. In addition, the extent of leasing is increasing and there are abnormal reductions in the number of employees. Misstating firms are raising more financing, have higher price-to-fundamental ratios, and have strong prior stock price performance. We develop a model to predict accounting misstatements. The output of this model is a scaled logistic probability that we term the F-Score, where values greater than one suggest a greater likelihood of a misstatement.

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... In recent years, artificial intelligence approaches have been widely introduced into financial fraud detection, enhancing the effectiveness of detection and reducing the time required to discover fraud [4][5][6]. Most of these methods are based on quantified financial data, such as financial ratios, and employ machine learning techniques to identify potential problematic features within financial statements, thereby detecting fraud [4,7,8]. These studies typically employ machine learning methods such as Logistic Regression (LR), Support Vector Machines (SVM), or Decision Trees (DT). ...
... where TP (true positive) denotes the number of samples correctly identified as fraudulent; FN (false negative) denotes the number of fraudulent samples incorrectly classified as nonfraudulent; TN (true negative) denotes the number of non-fraudulent samples correctly identified; FP (false positive) denotes the number of non-fraudulent samples incorrectly classified as fraudulent. Recall (Sensitivity) is the proportion of actual fraud cases correctly identified [7]. A higher recall means fewer missed fraud cases. ...
... Accuracy is the proportion of correctly classified instances out of all instances, with higher values indicating better overall performance [9]. The F1 score is the harmonic mean of precision and recall, balancing the two metrics [7]. Higher F1 scores indicate better performance in handling imbalanced data, with fewer false positives and negatives. ...
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The relationships within a supply chain are crucial for analyzing business transactions and can reveal significant patterns in disclosed financial data. These relationships also aid in the assessment and detection of financial fraud. Recent studies employing graph neural networks (GNNs) have demonstrated enhanced detection capabilities by integrating corporate financial features with supply chain relationships, surpassing traditional methods that rely solely on financial features. However, these studies face notable limitations: (1) they do not model enterprise associations across consecutive years, hindering the detection of long-term financial fraud, and (2) they lack efficacy in interpretive analyses of supply chain relationships to uncover patterns of fraud or risk transfer. To address these gaps, this paper introduces an interpretable and efficient Heterogeneous Graph Convolutional Network (ieHGCN) designed to analyze supply chain knowledge graphs. It also extends the model’s learning scope to multi-year financial data for detecting fraud. The experimental results indicate that our method, offering both extensibility and interpretability, significantly outperforms existing machine learning and GNN approaches in continuous multi-year fraud detection, achieving the highest AUC of 0.7498, a 3.8% improvement over the leading method. Furthermore, meta-path analysis reveals that companies sharing the same supplier exhibit correlated financial fraud risks and that fraud can propagate through the supply chain, providing novel insights into anti-fraud and risk management strategies through enhanced interpretability.
... Our focus is set on misstatements which have been detected during the audit process and that occur much more frequently but these misstatements have not been previously analysed due to the fact that pre-audit data and audit adjustments are usually not publicly available. Second, a major disadvantage of using SEC Accounting and Auditing Enforcement Releases (AAERs) or other samples that contain financial restatements is that many firms that manipulate earnings are likely to go unidentified as SEC has a limited budget, so it selects firms for enforcement action and does not investigate all firms (Dechow et al, 2011). Therefore, a selection bias may limit the generalizability of estimated results. ...
... Based on Beneish (1997;1999) research, Dechow et al (2011) conducted a detailed analysis of 2,190 AAERs between 1982 and 2005 and identified firms with misstated earnings. They investigated various characteristics of misstating firms and found that at the time of misstatements, accrual quality is low; financial and non-financial measures of performance are deteriorating, and financial and off-balance-sheet activities are more likely to occur. ...
... Even though we build our research on Beneish (1997;1999) and Dechow et al (2011) approach, our main goal is not to estimate the most accurate predictive model rather than to test the usefulness of accrual quality measures in detecting accounting misstatements. Namely, a large body of literature assumes that earnings are mostly manipulated through the accrual component of earnings (Dechow et al., 2011). ...
... Omeir et al. [22] use two well-known fraud detection models created by Beneish [23] and Dechow et al. [24]. This article compares the predictive accuracy of financial fraud for Iranian firm statements between these two models. ...
... This article compares the predictive accuracy of financial fraud for Iranian firm statements between these two models. They start by attempting to determine the statistical description linked to the Beneish [23] and Dechow et al. [24] models' first and fourth quartiles. The t-test and variance analysis are then used using SPSS software to assess the forecasting capabilities of the models. ...
... The research employs two primary fraud detection models: the Beneish model [23] and the Dechow model [24], to compare their precision in predicting financial statement fraud in Iranian companies. A sample of 197 companies was analyzed over an 11-year period from 2009 to 2019, utilizing SPSS software for statistical analysis, including t-tests and variance analysis. ...
... Altman (1968) [20] included Retained Earnings/Total Assets in his Z-score model for predicting bankruptcy, highlighting its importance in assessing financial health. The profitability ratios (net profit/Total asset and Gross profit/Total asset) are consistent with Dechow et al.'s (2011) [53] predictors of financial statement reliability. Beneish (1999) [43] also emphasized the importance of gross margin in his M-score model for detecting earnings manipulation. ...
... The importance of Retained Earnings/Total Assets is supported by Beneish (1999) [43], who included a similar ratio in his M-score model for detecting earnings manipulation. Dechow et al. (2011) [53] found that extreme values in working capital accruals, related to the Working capital/total assets ratio, were associated with a higher likelihood of material misstatements. The Gross profit/Primary business income ratio aligns with findings by Summers and Sweeney (1998) [55], who noted that gross margin index is a significant predictor of fraud. ...
... The importance of Retained Earnings/Total Assets is supported by Beneish (1999) [43], who included a similar ratio in his M-score model for detecting earnings manipulation. Dechow et al. (2011) [53] found that extreme values in working capital accruals, related to the Working capital/total assets ratio, were associated with a higher likelihood of material misstatements. The Gross profit/Primary business income ratio aligns with findings by Summers and Sweeney (1998) [55], who noted that gross margin index is a significant predictor of fraud. ...
Article
This research aims to enhance financial fraud detection by integrating SHAP-Instance Weighting and Anchor Explainable AI with XGBoost, addressing challenges of class imbalance and model interpretability. The study extends SHAP values beyond feature importance to instance weighting, assigning higher weights to more influential instances. This focuses model learning on critical samples. It combines this with Anchor Explainable AI to generate interpretable if-then rules explaining model decisions. The approach is applied to a dataset of financial statements from the listed companies on the Stock Exchange of Thailand. The method significantly improves fraud detection performance, achieving perfect recall for fraudulent instances and substantial gains in accuracy while maintaining high precision. It effectively differentiates between non-fraudulent, fraudulent, and grey area cases. The generated rules provide transparent insights into model decisions, offering nuanced guidance for risk management and compliance. This research introduces instance weighting based on SHAP values as a novel concept in financial fraud detection. By simultaneously addressing class imbalance and interpretability, the integrated approach outperforms traditional methods and sets a new standard in the field. It provides a robust, explainable solution that reduces false positives and increases trust in fraud detection models. Doi: 10.28991/ESJ-2024-08-06-016 Full Text: PDF
... We conduct a multivariate analysis using the order backlog model from Dechow et al. (2011) to estimate normal order backlog. We measure abnormal order backlog as the difference between reported and normal order backlog. ...
... Two papers examine the connection between financial reporting quality and order backlog, including Dechow et al. (2011) and Barber and Hollie (2021). Dechow et al. (2011) study order backlog as a predictor of earnings restatements and Berger and Hollie (2021) study it as a predictor of revenue restatements. ...
... Two papers examine the connection between financial reporting quality and order backlog, including Dechow et al. (2011) and Barber and Hollie (2021). Dechow et al. (2011) study order backlog as a predictor of earnings restatements and Berger and Hollie (2021) study it as a predictor of revenue restatements. Dechow et al. (2011) do not find evidence that abnormal order backlog is associated with future restatements. ...
Article
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Considerable evidence suggests the high importance of revenues to analysts and investors, which incentivizes managers to manage revenues. Research suggests managers engage in both accrual and real activities management to manage revenue. We examine whether managers exploit the order fulfillment process (a form of real activities management) to meet or beat revenue targets. Our evidence suggests that managers manipulate order backlog to avoid reporting a decline in revenue and to meet or beat analysts’ revenue forecasts. Cross-sectional analyses suggest managers are more likely to manipulate order fulfillment when incentives to report revenue growth are high and when the costs of adjusting order fulfillment are low. Counterfactual tests suggest that only firms that meet revenue thresholds by small amounts have abnormally low ending order backlog. Our inferences are robust to alternative models of normal order backlog and alternative methods of estimation. Our study provides evidence that managers adjust order fulfillment to manage reported revenues across thresholds. Our evidence is relevant to regulators who determine order backlog disclosures and other stakeholders who use financial report data.
... Various research has been conducted in searching of fraudulent financial statement detection, including utilization of supervised learning and unsupervised learning. Supervised learning is used including various models such as neural network [7]- [11], genetic algorithm [12], decision tree (DT) [8]- [10], [13], Bayesian network [8], [9], support vector machines (SVM) [8], [13]- [15], and logistic regression (LR) [16]. Unsupervised learning implementation use algorithm such as self-organizing map [17], [18] and k-means clustering [17]. ...
... This study was considered a pioneering work in the field. Dechow et al. [16] presented an alternative method using LR with financial ratios to detect fraudulent financial statements, signaling the likelihood of misstatement. Perols [10], with a larger dataset of 15,934 non-fraudulent and 51 fraudulent cases, demonstrated that LR and SVM outperformed neural network, bagging, C.45, and stacking algorithm. ...
... Their study revealed that combining AdaBoost and majority voting methods yielded the best results. Bao et al. [15] extended this research by using a large public dataset and compared the results of re-implementing the models proposed in [14], [16] with a new state-of-the-art model using RUSBoost. The proposed method outperformed the previous models with an area under curve (AUC) of 72.5% and sensitivity and precision of 4.88% and 4.48%, respectively. ...
Article
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In this paper a novel approach for detecting fraudulent financial statements by employing a combination of neural networks and synthetic minority over sampling technique (SMOTE) is introduced. This approach is designed to tackle the problem of imbalanced datasets prevalent in fraudulent cases, which if left unaddressed will hinder the model to accurately identify fraud. Three neural network models, each representing different fraud predictors as the input layer: 28 inputs raw financial data; 14 inputs financial ratios data; and 42 inputs combination both raw financial and financial ratios data are developed. Experimental validation using established research datasets is conducted to assess the performance of the proposed method. Performance metrics, namely area under the curve (AUC), precision, and sensitivity, are used for evaluation, comparing the proposed model against existing benchmark models found in literature. Results indicate that the proposed model achieves an AUC score of 70.6% and a precision score of 2.89%, in comparable to the existing models, with a sensitivity score of 83% outperforming all counterparts. The high sensitivity rate of the proposed model underscores its practical utility for auditors and regulators, as it minimizes the risk of false negatives, thereby enhancing confidence in fraud detection.
... The old leasing standard IAS 17 has confronted many of criticism by researchers such as Reither (1998) and Duke et al. (2009);professionals (AICPA, 1994); and information users (Beattie et al., 2006;Deloitte, 2020) all pointed out that, under IAS 17 entities where unable to recognise all of leases obligations and assets on their statement of financial position, hence financial statements lacked of comparability element. Moreover, firms (lessees) has structured lease contracts to be kept out off-balance sheet, so that they may be regarded as operating lease (Abdel-Khalik, 1981;Duke et al., 2009;Beatty et al., 2010;Bryan et al., 2010;Dechow et al., 2011;Cornaggia et al., 2011). Some practical inquiries also have pointed out that operating leases is united to debt assessment and securities yield and thus any concealing of such costs will overstate the company true financial position (Dhaliwal et al., 2011). ...
... Consensus among academics for the impact of leases advocates that, the core of IAS 17 is how to classify leasing contracts as a finance lease or operating lease, the type of classification has a clear influence on the financial and economic status of the entity and most likely inspire firms to engage with prearranged agreement's to avoid recognition of some classifications (Imhoff and Lipe, 1997;Duke et al., 2009;Beatty et al., 2010;Bryan et al., 2010;Dechow et al., 2011;Fülbier et al., 2008;Kostolansky and Stanko, 2011;Tai, 2013). From the earliest studies that investigated in depth avoidance of some classification is Abdel-Khalik (1981) whom found that companies approve operate leasing so as to sidestep harms of debt agreement covenant's. ...
Article
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The current research is an attempt to contribute to the accounting standards framework by examining the contribution for adopting the new leasing standard IFRS 16 that replaced the previous IAS 17 for leasing to verify the extent to which the new standard imitates the market value of companies. The study investigation centred on detailed comparison between a firm's performance results pre and post the inclusion of the new standard. The reported accounting information about stock market price, market value, net income, market to book value and market to cash flow were assessed before and after the adoption of the new leases standard through a comparison of means and regression variations to identify any changes if found. The findings of our inspection revealed significant economic consequences for IFRS 16 on the selected variables; thus a supportive evidence was established for the ability of emerging markets to imitate any changes in international accounting standards. Reference to this paper should be made as follows: Aladwan, M. (2025) 'Market return volatility under renewable lease contracting comparative approach between IFRS 16 and IAS 17', Int.
... The fraud triangle theory suggests that various pressures, opportunities, and rationalizations tend to cause financial fraud (Cressey Donald, 1953). Firms engage in fraudulent activities to present their more favorable image for attracting investments, and to satisfy the shareholders (Dechow, Ge, Larson, & Sloan, 2011). The lack of a stringent regulatory framework, complex corporate structure, and ineffective governance mechanisms provide strong grounds to managers for financial fraud (Zhou & Kapoor, 2011). ...
... Fahlenbrach, Low, and Stulz (2010) found that firms experiencing financial difficulties are under a high pressure to perform accounting misreporting. Financial distress leads the firms to adopt those measures which can be used to conceal poor performance and secure investor confidence (Dechow et al., 2011). It can be argued that greater financial pressure tends to increase the likelihood of fraudulent activities (Agrawal & Chadha, 2005). ...
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Using data from Chinese A-share listed enterprises from 2007 to 2023, this study employs a two-way fixed effects model to examine the effects of internal control quality, CEO duality, ownership concentration, and financial distress on corporate fraud. The benchmark results indicate that higher internal control quality mitigates the risk of corporate fraud, while CEO duality, ownership concentration , and financial distress increase this risk. Robustness checks utilizing lagged variables confirm these findings. Heterogeneity analysis reveals that in highly leveraged firms, CEO duality and ownership concentration significantly increase fraud risk, whereas internal control quality reduces this risk. In low-leveraged firms, internal control quality reduces fraud, and CEO duality and financial distress increase fraud risk. Analysis based on business cycle heterogeneity shows the importance of robust internal controls in both fast and slow cycles, with varied effects of CEO duality and ownership concentration. Industry analysis indicates that internal controls are crucial in both heavily and less polluted industries, with ownership concentration and financial distress having significant impacts in less polluted sectors. Policymakers should mandate stricter internal control requirements and regular audits to ensure compliance and effectiveness.
... Lease accounting has been an area of controversy and debate for several decades, traditionally associated with the off-balance-sheet treatment of operating leases. The literature in this area examines the incentives to secure operating lease treatment for lease transactions, including financial flexibility (Sharpe and Nguyen 1995;Beatty et al. 2010;Gavazza 2011;Caskey and Ozel 2019) and contracting incentives (Ang and Peterson 1984;Dechow et al. 2011;Altamuro et al. 2014). A study commissioned by the SEC in 2005 documented that over $1.25 trillion in noncancelable future cash obligations committed under operating leases are not recognized on issuer balance sheets (U.S. SEC 2005). ...
Article
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This study examines whether the revised lease standards (ASC 842 and IFRS 16) make U.S. GAAP-based accounting amounts more comparable with IFRS-based accounting amounts. Our study is motivated by the FASB and the IASB’s call for research on the comparability of the revised lease standards. We find that U.S. GAAP and IFRS pairs that are high operating lease users experience a larger increase in accounting comparability after the adoption of revised lease standards than low operating lease U.S. GAAP-IFRS pairs. Additionally, our results suggest that the improvement comes more from the changes to the balance sheet rather than the income statement and is more pronounced for IFRS firms from countries with stronger accounting enforcement. Lastly, we show that analysts who are more GAAP-focused (IFRS-focused) prior to the standard change are more likely to increase their forecasting of book value per share for IFRS (U.S. GAAP) firms.
... Return on Equity provides valuable insights into financial health and operational efficiency (Equation (19)). The return on assets ratio is also used to detect fraudulent financial statements (Equation (20)). Anomalies in these ratios may raise red flags for revenue or expense manipulations, necessitating a thorough investigation into potential financial statement fraud. ...
Article
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The study utilized Multiple Linear Regression along with advanced classification algorithms such as Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree, and Random Forest, to detect financial statement fraud. Model performance was evaluated using key metrics, including precision, recall, accuracy, and F1-Score. The analysis also identified significant indicators of fraud, such as Accounts Receivable Turnover, Days Outstanding Accounts Receivable, Days Payables Outstanding, Logarithm of Gross Profit, Gross Profit Margin, Inventory to Sales Ratio, and Total Asset Turnover. Among the models, Random Forest emerged as the most effective algorithm, consistently outperforming others on both training and testing datasets. Logistic Regression and SVM demonstrated strong reliability, whereas KNN and Decision Tree faced overfitting challenges, limiting their practical application. These findings emphasize the critical need for enhanced fraud detection frameworks, leveraging machine learning algorithms like Random Forest to identify fraud patterns effectively. The study highlights the importance of strengthening internal controls, implementing targeted fraud detection measures, and promoting regulatory improvements to enhance transparency and financial accountability.
... Source: Dechow et al. (2011). ...
Article
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Financial statement fraud (FSF) is a significant contributor to losses and has persisted for several years (Association of Certified Fraud Examiners [ACFE], 2022). Previous studies concluded that corporate governance (CG) can significantly reduce FSF (Mangala & Kumari, 2015; Rostami & Rezaei, 2022; Velte, 2023). However, while the literature study acknowledges that CG plays an important role in fraud prevention and emphasizes the importance of effective board composition, effective audit committees, independent commissioners, gender diversity, ownership structure, and engagement with Big 4 accounting firms to the occurrence of FSF, the empirical evidence in Indonesia suggests inconsistent results. This research investigates the role of CG in preventing FSF in Indonesia. The study tested a sample of 72 companies sanctioned by the Financial Services Authority (Otoritas Jasa Keuangan, OJK), Republic of Indonesia, in 2019–2021 and another 72 control sample companies from similar sectors and equivalent market capitalization. A total of 144 data units are analyzed using panel data regression and independent t-test. The study results show that the frequency of audit committee meetings and institutional ownership positively affect the indication of FSF. The study result also shows significant mean differences in the frequency of audit committee meetings and institutional ownership between companies indicated and not indicated to commit FSF. Besides enriching the global discourse on best CG practices, this study provides actionable recommendations for enhancing the integrity and transparency of financial reporting.
... In fact, the data available to researchers only cover firms' or auditors' behaviors that have been previously identified as frauds and ultimately subject to enforcement actions and sanctions. The disadvantages of using this type of proxy are the large number of fraud firms that are likely to remain unidentified and possible selection biases in the cases pursued by enforcers (Dechow et al., 2011). Accordingly, authors may need to acknowledge that some of the entities classified as "non-fraudulent firms" in their studies may potentially be companies that engaged in fraudulent activities that were not detected at the time of their research. ...
Article
Purpose This study reviews and discusses the accounting literature that analyzes the role of auditors and enforcers in the context of fraud. Design/methodology/approach This literature review includes both qualitative and quantitative studies, based on the idea that the findings from different research paradigms can shed light on the complex interactions between different financial reporting controls. The authors use a mixed-methods research synthesis and select 64 accounting journal articles to analyze the main proxies for fraud, the stages of the fraud process under investigation and the roles played by auditors and enforcers. Findings The study highlights heterogeneity with respect to the terms and concepts used to capture the fraud phenomenon, a fragmentation in terms of the measures used in quantitative studies and a low level of detail in the fraud analysis. The review also shows a limited number of case studies and a lack of focus on the interaction and interplay between enforcers and auditors. Research limitations/implications This study outlines directions for future accounting research on fraud. Practical implications The analysis underscores the need for the academic community, policymakers and practitioners to work together to prevent the destructive economic and social consequences of fraud in an increasingly complex and interconnected environment. Originality/value This study differs from previous literature reviews that focus on a single monitoring mechanism or deal with fraud in a broadly manner by discussing how the accounting literature addresses the roles and the complex interplay between enforcers and auditors in the context of accounting fraud.
... The binomial test yields a p-value of 0.648, meaning that we fail to reject the null hypothesis that the significant negative market reactions observed in five out of 110 events occur randomly in the subsamples with low earnings quality or low information availability. In untabulated tests, inferences do not change if we use F-score(Dechow et al. 2011) to proxy for earnings quality and use client size to proxy for information availability.Content courtesy of Springer Nature, terms of use apply. Rights reserved. ...
Article
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We make a collective assessment of the consequences of 110 auditor reputation-damaging events with media coverage (“negative events”) from 2007 to 2019 for the U.S. Big Four. First, we fail to find systematic evidence that investors react negatively to negative events. Second, while auditors experience statistically significant client loss after negative events, the effects are short-lived and economically negligible. Furthermore, we find statistically greater effects in situations where theory suggests economic forces could magnify reputation effects (i.e., higher market competition, more replacement auditors, lower client switching costs, and higher audit office reputational capital). However, the economic impact remains small in all cross sections. Overall, our results suggest that negative events with media coverage have only a very marginal impact on investors’ perceptions of Big Four firms’ audit quality and the ability of these firms to attract and retain clients.
... Offbook fraud schemes are much harder to detect, since they are not detectable by examining the books and records (e.g., theft of incoming cash before entering the accounting records). Practical methods of fraud detection include financial statement analysis (including the Beneish M-Score and Dechow F-Score used to identify manipulated earnings ;Beneish 1997;Dechow et al. 2011), undercover surveillance, invigilation, and admission-seeking interviews (Buckhoff and Clifton 2004). ...
Article
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This paper reviews the experimental literature on fraud detection by external auditors. We conduct a systematic literature review that includes 37 experimental studies on fraud detection from the JSTOR, EBSCO, and WoS (Web of Science) databases and from SSRN. We present a theoretical background on fraud models and common fraud detection methods. Our review covers results of studies on fraud brainstorming and fraud risk assessment, on fraud detection from interviews, inquiries, text, and speech. We also reveal the outcome of studies focusing on the effect of attention, accountability, and the evaluation of audit evidence on fraud detection. These studies show that interventions like priming, and additional instructions on fraud consideration or game-like elements enhance auditor awareness of fraud cues, thus improving brainstorming, risk assessment, and the evaluation of audit evidence. Finally, the paper considers the limitations and criticisms of the presented studies, and future research avenues in fraud detection.
... Intentional misstatement or omission of disclosures in the financial statements designed to deceive users of the financial statements. (Dechow et al., 2011). ...
Article
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Purpose: This study investigates the application of fraud diamond theory in the detection of financial statement fraud, utilizing financial targets, industry characteristics, auditor changes, and director changes as independent variables. Methodology/approach: This research focusing on healthcare companies listed on the Indonesia Stock Exchange (IDX) from 2016 until 2023, the study analyzes data from 32 firms, resulting in 185 analytical units. Employing panel data regression analysis through Eviews 12. Findings: The findings reveal that only financial targets show a positive and significant influence on financial statement fraud. In contrast, the other variables—industry characteristics, auditor changes, and director changes—show no significant impact. Additionally, while the audit committee moderates the relationship between industry characteristics and financial statement fraud, it does not influence the relationships involving financial targets, auditor changes, or director changes. Practical and Theoretical contribution/Originality: The novelty of this research is using the audit committee as a moderating variable to minimize the occurrence of financial statement fraud. Research Limitation: Future research is expected to use new theories, other proxies, and use different sector samples because this research is only limited to healthcare companies.
... The F-Score scoring model, which includes 9 indicators such as accounts receivable change rate, inventory change rate and refinancing, is screened out. The comprehensive identification accuracy rate of this model for fraudulent behaviors of listed companies is 64% [2]. Persons selected a total of 10 financial indicators from 7 aspects reflecting the company's business scale, profitability, and overall financial status as the estimator variables of the model, and then used the maximum likelihood method to construct two linear regression models, the sample of the fraud year and the sample of the previous year. ...
Article
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The pervasive threat of financial fraud casts a daunting shadow over the global financial system, bearing the potential to unleash significant financial turmoil. This article endeavors to meticulously scrutinize instances of financial fraud at both domestic and international levels, while also delving into the efficacy of the M-score model. Through an exhaustive comparative analysis of the M-score model's adaptability and utility in diverse economic landscapes, our primary goal is to bolster global fraud detection capabilities and facilitate the implementation of robust policies. This study is dedicated to unraveling the intricate complexities of financial fraud, discerning recurrent patterns and trends that transcend national borders and economic structures. By embarking on this endeavor, our aim is to fortify the resilience of financial markets and regulatory frameworks against fraudulent activities, ultimately fostering greater stability and trust within the worldwide financial ecosystem. In doing so, we endeavor to reinforce the stability and trust within the worldwide financial ecosystem, elevating the integrity of financial markets and regulatory frameworks against the pernicious influence of fraudulent activities.
... These variables include FOFS, FTs, TATAs, and NOIs. The FOFS measurement is represented by a method of (Dechow et al., 2011). For FTs, measurement using ROA is calculated based on the approach of Skousen et al. (2009). ...
Article
Fraud potential in financial statements often occurs. For this reason, this study identifies aspects that cause financial statement fraud (FOFS), including financial targets (FTs), total accruals, and total assets (TATAs), and the industries' nature (NOIs) in the banking and energy sector companies in Indonesia. The data sample is the financial and annual reports of 122 banking and energy companies. The purposive sampling is used for the selection of the data. The analysis uses different test analysis methods and panel data regression tests. The results prove that FTs prove to be a strong predictor of FOFS in banking companies, while in energy companies it is not proven. Furthermore, TATAs have not been proven to affect FOFS in companies in both sectors. Meanwhile, NOIs have a negative effect on FOFS. The implication is for the banking sector, the potential for FOFS is more due to the disclosure of high Return on assets (ROA) and low-income ratios. In contrast, in the energy sector, companies are strongly influenced only by low-income ratios.
... If financial distress influences the relationship between climate risk and corporate fraud, it is pertinent to consider which firms are most affected by this dynamic. Financial constraints are a significant factor in fraud propensity (Dechow et al., 2011). Climate risk escalates the financing requirements for affected firms to repair damages and restore production (Wang, 2023). ...
Article
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While previous research has primarily focused on the impact of climate risk on corporate socially responsible behaviors, this study investigates how climate risk may influence corporate social irresponsibility. Using panel data from Chinese listed firms spanning from 2003 to 2020, we find that heightened exposure to climate risk correlates with an increased likelihood of fraud commission. Moreover, we observe that financial distress positively moderates the relationship between climate risk and corporate fraud, particularly within climate-vulnerable industries or financially constrained firms. Our findings further suggest that climate risk exacerbates corporate fraud by increasing pressures related to performance, debt financing, and shareholder demand. This study highlights the detrimental role of climate risk in shaping corporate ethics and amplifying the incidences of corporate fraud.
... ELKit= β0 + β1SK1it + β2PTE2it + β3PA3it + β4PD4it + β5FFC5it + β6PKP6it + εit (1) KLK is Financial Report Fraud, SK is Financial Stability, PTE is Ineffective Supervision, PA is Change of Auditor, PD is Change of Director, FFC is Frequency of appearance of the CEO's photo, and PKP is Project with the government. Financial statement fraud is proxied using the Fraud Score Model developed by Dechow et al. (2011). The F-score model uses the sum of two components, namely Accrual Quality and Financial Performance, formulated with the following equation: ...
Article
Financial statement fraud is something that causes economic losses and results in a loss of investor confidence. Therefore, company management needs to identify what factors influence the company in committing fraud. One approach to detecting fraud is to use the fraud hexagon model. This model consists of stimulus, opportunity, rationalization, capability, ego, and collusion. This research is explanatory research that aims to investigate the possible factors of financial statement fraud using a fraud hexagon perspective. The objects used as research samples are 15 insurance companies registered on the IDX during 2019 - 2022. This research uses the F-Score model to separate companies that have experienced fraud and uses logistic regression as data analysis. The results of his study show that the elements of opportunity, rationalization, and ego influence financial statement fraud. Meanwhile, the elements of stimulus, capability, and collusion do not affect financial statement fraud.
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This study aims to examine the influence of fraud hexagon theory factors on financial statement fraud in transportation and logistics sector companies listed on the Indonesia Stock Exchange from 2018 to 2022. The fraud hexagon theory elements in this study are proxied by financial targets, ineffective supervision, auditor changes, board of directors changes, frequency of CEO photo appearances, and State-Owned Enterprises. The sample in this study was 19 companies that had been selected using purposive sampling techniques. The number of observations in this study was 95 observations. The data analysis carried out in the study was panel data regression analysis using EViews 12 software as a data analysis tool. The results of the analysis showed that financial targets had a positive effect on financial statement fraud. However, ineffective supervision, auditor changes, board of directors changes, frequency of CEO photo appearances, and state-owned enterprise variables were shown to have no effect on financial statement fraud. This study provides theoretical implications in the form of additional information about the influence of financial targets on financial statement fraud and this study also provides practical implications for company leaders to pay more attention and consider the company's financial targets as one of the indicators that can be used to detect financial statement fraud.
Article
Using the staggered adoption of constituency statutes across US states as an exogenous shock to stakeholder orientation, we examine its impact on opportunistic insider trading. We show a strong mitigating effect of stakeholder orientation on insider trading. We find that firms incorporated in states that passed stakeholder constituency statutes have a lower likelihood of opportunistic insider purchases, particularly in environments characterized by high information asymmetry and weak monitoring. Additionally, we find that stakeholder orientation mitigates other measures of financial misconduct, like securities class action lawsuits and financial misstatements. Our results are supported by a variety of robustness and causality tests.
Article
This study reports on chief financial officer (CFO) wrongdoing in accounting. It analyzes and synthesizes the evidence of this research stream to reveal why CFOs commit this type of misconduct and to highlight differences to chief executive officers (CEOs). We structure our systematic literature review based on the fraud diamond framework and report about studies on a CFO’s pressure, opportunity, rationalization, and capability to commit accounting wrongdoing. The 64 articles uncover similarities and differences with the CEO and demonstrate that CFOs predominantly possess stronger incentives, equal opportunities, similar or stronger rationalization, and a more wide-ranging capacity to commit accounting wrongdoing. Their context-specific settings lead to diverging accounting wrongdoing types, such as real EM (REM) and accrual EM (AEM). Our review indicates future research possibilities and suggests studying combined fraud diamond dimensions and moderators on the individual, firm, and environmental levels to explain the inconclusive results of this research stream.
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Purpose This study aims to examine the determinants of Foreign Corrupt Practices Act (FCPA) violations and consequences of FCPA enforcements. Design/methodology/approach This paper uses publicly available data from Compustat, I/B/E/S and Thomson Reuters databases, combined with Securities and Exchange Commission (SEC) and Department of Justice (DOJ) cases, to extract insights on FCPA violations and enforcements using econometric approaches. Findings The main determinants of FCPA violations appear to be firm size, multinational structure, country corruption and Sarbanes-Oxley Act control weaknesses. Traditional misreporting risks (F-score and M-score) do not predict FCPA violations. This study discovers significant differences between FCPA violations by motivation, as in, sale generation, rent extraction or cost evasion. Bribes motivated by sale generation or rent extraction are partially driven by the extent of the firm’s global operations, whereas bribes motivated by cost evasion relate to internal influences. This study also finds that enforcement is more salient for criminal violations (DOJ enforcement), compared to civil violations (SEC enforcement). Research limitations/implications This research provides new insights into the determinants of FCPA violations while underscoring the need for effective measures to combat bribery and promote ethical business practices. This research contributes to the ongoing efforts to curtail bribery, offering valuable insights into the characteristics of firms more likely to engage in bribery and contexts in which these activities occur. It provides critical implications for regulatory bodies, highlighting the differential responses of firms to varying types of enforcement, namely, criminal versus civil, as the authors observe greater decreases in internal control weaknesses following DOJ enforcement compared to SEC enforcement. Practical implications For enforcement agencies, the findings underscore the importance of rigorous criminal enforcement against FCPA violations, highlighting the improved control environments prompted by DOJ actions. Managers will find this research relevant, as it demonstrates that a firm’s entry into international markets substantially elevates the risk of its representatives engaging in bribery with foreign officials. In addition, the results are of interest to regulators, revealing that the underlying motivations driving a firm’s activities can significantly alter the factors to consider that might lead to an FCPA violation. Originality/value This paper is the original work of the authors and explores the determinants and consequences of FCPA violations and enforcement actions since 2002. To the best of the authors’ knowledge, it is the first to explore bribe determinants by their motive and documents industry-wide benefits arising from criminal enforcement.
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This study investigates the effect of an earlier contract for auditor change (ECAC) on audit quality. In November 2018, the Korean government mandated that client firms must complete audit engagement contracts before the date of the audit report. This requirement informed incumbent auditors about the final year of their engagement prior to completing audit procedures. Our hypothesis suggests that this increased awareness enhances the independence of incumbent auditors, resulting in improved audit quality. The findings support the hypothesis and reveal that audit quality with incumbent auditors in the year preceding the auditor change is higher following the implementation of ECAC. ECAC is identified as a cost‐effective approach, as it can be readily implemented by advancing the notice date for auditor changes. These findings offer valuable insights to other countries seeking to enhance their audit quality while minimising costs.
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Given its opacity and the timing of its closure, the tax expense represents a theoretically and intuitively plausible mechanism for managers to manipulate earnings to achieve performance benchmarks (i.e., last chance earnings management or LCEM). Although empirical analyses of effective tax rates are consistent with the existence of this behavior, its consequences are unclear. We investigate whether LCEM is associated with lower financial reporting quality. Contrary to our expectations, we fail to find evidence that LCEM is associated with tax‐related misstatements, tax‐related comment letters, or tax accrual quality with scaled confidence intervals reliably near zero. In cross‐sectional tests, we also fail to find a consistent association in subsamples where LCEM is more likely to represent impaired financial reporting quality. Collectively, our results should caution researchers using LCEM as a proxy for impaired financial reporting quality.
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Research Question/Issue This study investigates director departures surrounding the actual commencement of noncompliance events when public perception of the wrongdoing is less likely to exist. Research Findings/Insights Using a manually constructed nonaccounting noncompliance dataset of the Securities and Exchange Commission’s enforcement actions and hand‐collected information on directors’ status and characteristics, this study finds that firms not complying with securities laws experienced significantly higher unexpected director departures than control firms during the period in which the noncompliance began. Outside directors, in particular, tend to leave in the pre‐noncompliance period but not in the post‐noncompliance phase. The findings are robust across propensity score–matched tests, conditional logistic regression, and when controlling for CEO turnover. Further exploration of the characteristics of departing directors provides insights into the dynamics of the internal governance mechanism. It shows that directors with a background in an area of specialized expertise tend to leave noncompliant firms. The evidence also suggests that power struggles between departing directors and managers in noncompliant firms might contribute to director departure. Theoretical/Academic Implications This study extends the literature aimed at unraveling internal governance mechanisms around firms’ negative events. Since there are several important points along the timeline of a negative event, providing evidence on director behavior around these points can offer deeper insights into internal governance mechanisms. Practitioner/Policy Implications This study provides unique evidence that there is an abnormal departure rate of directors before the commencement of firms’ wrongdoings. This departure is consistent with explanations that directors with an information advantage from a special background are likely to foresee that problems or power struggles between directors and managers are likely to induce the departure of a director who is in a relatively weak position. The findings offer insights for policy makers, suggesting that regulators may need to reflect upon the shortcomings of the current governance system and how to hold management accountable, rather than putting heavy emphasis on developing doctrines for directors’ duties.
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Purpose This paper aims to integrate the latent semantic features of annual report text with accounting indicators to construct a financial fraud identification model, and quantitatively analyze the impact of different corporate risks on financial fraud behavior in different industries, providing a reference for identifying financial fraud. Design/methodology/approach This paper obtains 3,860 corporate annual report samples and accounting indicators from 2001 to 2020 through crawlers and the CSMAR database as our experimental subjects. By integrating latent semantic features with accounting indicators and textual language features, a new indicator system group is constructed. Based on this indicator system group, multiple model identification effects are compared and a stacking-based enterprise financial fraud identification model is constructed. In addition, an econometric model is established to verify the impact of latent semantic features related to enterprises on corporate financial fraud. Findings The experimental results show that the constructed stacking-based enterprise financial fraud identification model performs better than other machine learning models and can effectively identify financial fraud. The econometric model established for the latent semantic information of annual reports explains the impact of different corporate trends on fraud behavior in different industries. Originality/value This paper combines the textual latent semantic features of annual reports with accounting indicators, expands the scope of data analysis, introduces the idea of ensemble learning, updates the financial fraud identification algorithm and constructs an econometric model for further analysis, providing a reference for financial fraud identification.
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This study investigates the use of textual risk disclosures in annual reports to detect accounting fraud. We developed an indicator system based on Securities and Exchange Commission (SEC) guidelines to evaluate the quality of risk disclosures. An analysis of 41,343 financial reports from US listed companies revealed that textual risk disclosures enhance fraud detection accuracy and function as an early warning system. The performance of these disclosures surpasses traditional analyses of the Management Discussion and Analysis section. Our findings highlight the value of textual risk disclosures in identifying accounting fraud and underscore the crucial role of regulatory guidelines in ensuring financial integrity.
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This study aims to examine the influence of external pressure, ineffective supervision, audit opinion, and change of directors on financial statement fraud in banking companies listed on the Indonesia Stock Exchange for the 2018–2022 period. The research sample was selected using the purposive sampling method from the annual reports of 29 banking companies, and the data were analyzed using logistic regression with SPSS version 26. The results showed that ineffective supervision significantly influenced financial statement fraud, while external pressure, audit opinions, and changes in directors had no significant effect. These findings imply the need for banking company managers to enhance supervision effectiveness to minimize the potential for financial statement fraud that could harm external parties.
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The severe impact of financial statement fraud (FSF), particularly in large corporations, remains a significant challenge globally, often arising due to weak internal controls and the pressure on employees to meet financial targets. This study explores the applicability of the New Fraud Diamond Model on financial statement fraud (FSF) in energy companies listed on the Indonesian Stock Exchange (IDX) from 2019 until 2023. The sample comprises 238 companies selected through purposive sampling. The research results indicate that financial stability and financial targets positively influence FSF, while effective monitoring has a negative effect. Other variables show no significant impact. The findings provide practical implications for regulators and companies to strengthen governance mechanisms, enhance monitoring effectiveness, and align financial targets with long-term goals to mitigate fraud risks, thereby improving overall corporate accountability and financial market stability.
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Objective: Fraudulent financial statements are among the least frequent types of fraud globally but result in the highest median losses for companies. This study aims to develop a strategy model for detecting potential fraudulent financial statements in Indonesia’s State-Owned Enterprises (B.U.M.N.) by analyzing the Fraud Heptagon Theory, which includes stimulus, ability, collusion, opportunity, rationalization, ego, and big data analytics. Theoretical Framework: The study incorporates risk management and the audit committee as moderating variables to evaluate their roles in mitigating fraudulent financial reporting. Fraudulent financial statements were measured using the F-Score Model, emphasizing Goal 16 of the Sustainable Development Goals (SDGs): Peace, Justice, and Strong Institutions. Method: A total of 126 samples from 2018–2022 were obtained through purposive sampling. Data analysis employed Warp PLS 7.0 with a Structural Equation Modeling (SEM-PLS) approach. Results and Discussion: The findings reveal that most Fraud Heptagon Theory elements do not significantly affect fraudulent financial statements, except for financial pressure, which acts as a stimulus proxy. While big data analytics enhances risk management, it does not directly mitigate fraudulent reporting. The audit committee moderates the collusion relationship with fraudulent financial reporting, albeit with limited overall impact. Research Implications: This study offers a framework for stakeholders to leverage innovative technologies and governance strategies to improve financial transparency and accountability, aligning corporate practices with SDGs. Originality/Value: This research integrates the Fraud Heptagon Theory with big data analytics and SDGs, proposing a novel strategy model for detecting fraudulent financial statements in State-Owned Enterprises. It highlights the dynamic role of advanced technologies and governance in fraud detection.
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Fraudulent transactions in the Bitcoin ecosystem wield substantial influence over both the economy and the level of trust within a blockchain network. The identification of fraudulent transactions is a crucial task within the financial system. However, existing detection methods predominantly rely on either an individual model or a single bagging or boosting ensemble model, leading to inadequate prediction accuracy and limited interpretability. To address this limitation, a hybrid ensemble model that integrates bagging (random forest (RF)) and boosting (categorical boosting (CatBoost)) is proposed, in which strong classifiers -CatBoost is used to replace the weak classifiers in RF, thus effectively improving the prediction performance. Empirical findings demonstrate the proposed hybrid ensemble framework can consistently yields the highest accuracy. Furthermore, we introduce extreme gradient boosting as a surrogate model that can obtain more accurate relations between actual labels and the predictions, compensating for the challenges of understanding complex models. Then, the visualization package based on Shapley additive explanations (SHAP) value is adopted for the interpretability analysis on the surrogate model, which contributes to the field of fraud detection by revealing the potential influencing factors behind the predicted results and providing unique insights into how fraud detection behavior can be detected.
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With the rapid development of the capital market, financial fraud cases are becoming increasingly common. The evolving fraud strategies pose significant threats to financial regulation, market order, and the interests of ordinary investors. In order to combine the generalization performance of different machine learning methods and improve the effectiveness of financial fraud prediction, this paper proposes a novel financial fraud prediction framework based on stacking ensemble learning. This framework, based on data from listed companies, comprehensively considers financial ratio indicators and non-financial indicators. It uses the stacking ensemble technique to integrate numerous base models of machine learning algorithms for predicting financial fraud. Furthermore, our proposed framework has high versatility and is suitable for various tasks related to financial fraud prediction, addressing the problem of model selection difficulties in previous research due to different scenarios and data. We also conduct case studies on specific companies and industries, confirming the significant interpretability and practical applicability of our proposed framework. The results show that the recall rate and Area Under Curve (AUC) of our framework reach 0.8246 and 0.8146, respectively, surpassing mainstream machine learning models such as XGBoost and LightGBM in existing studies. This research is of great significance for predicting the increasing number of financial fraud cases, providing a reliable tool for financial regulatory institutions and investors.
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Financial statement fraud is a serious threat to the stability of the financial market. Therefore, effective detection methods are crucial to prevent significant losses to investors and damage to companies’ reputations. This study aims to explore the performance of different machine learning models in identifying financial statement fraud, and to analyze the impact of key financial indicators on the model performance. The study adopts the data of financial statement frauds disclosed by SEC for the period 2016-2019 (disclosed between 2021-2023), selects fifteen financial indicators as features and applies five classification models, including Decision Tree, Logistic Regression, Support Vector Machine, Random Forest, and Extreme Gradient Boosting, for training and testing. To address the issue of data imbalance, the Synthetic Minority Oversampling Technique (SMOTE) is employed. The results indicate that Extreme Gradient Boosting and SVM outperform other models in financial fraud identification, though SVM shows some risk of overfitting. Random Forest exhibits relatively stable performance. At the financial indicator level, IBD/TIC (Interest-Bearing Debt/Total Invested Capital), QR (Quick Ratio), APTR (Accounts Payable Turnover Ratio), GP (Goodwill Proportion), and GW(Goodwill) have a greater impact on the identification results of most models, reflecting their important roles in identifying financial fraud. This study’s contribution focuses on the interpretability of key financial indicators enhances model transparency, providing actionable insights for real-world fraud detection applications. The findings of this study contribute to the development of more effective financial statement fraud detection systems, and provide valuable insights for auditors, financial analysts, and regulators. By integrating model performance with indicator-level analysis, this research bridges theoretical advancements with practical implementation.
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Subject. This article examines the relationship between possible financial indicators and financial statements items, which makes it possible to form a set of monitored indicators, the monitoring of which makes it possible to continuously assess the risk of material misstatement of accounting information and respond to it accordingly. Objectives. The article aims to substantiate the selection of monitored financial indicators used in analytical audit procedures that can help assess the risk of material misstatement of accounting information in a continuous manner. Methods. For the study, we used the methods of logical analysis and synthesis. Results. The study of the relationship between possible financial indicators and financial statements items helped form a set of indicators, monitoring the rate of change of which in the process of online audit makes it possible to continuously assess the risk of material misstatement of accounting information and respond to it accordingly. The article offers a list of monitored financial indicators. Conclusions. The use of analytical procedures consisting in monitoring the proposed financial indicators will help assess the risk of material misstatement of financial results and balance sheet assets, which will make it possible to respond to it in a timely manner.
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Ежедневно в стране принимаются множество финансовых решений, которые основываются на финансовой информации. Главным источником такой информации являются данные бухгалтерской (финансовой) отчетности. Однако многие компании действуют на основании стратегии оппортунизма, то есть получают выгоду от искусственно созданной информационной асимметрии. Компании могут оказывать влияние на решения, принимаемые банками, инвесторами, рейтинговыми агентствами, контрагентами и другими участниками экономической деятельности, путем сознательного введения в заблуждение пользователей отчетности. Данные могут искажаться такими приемами, как вуалирование, манипулирование и мошенничество. Наиболее трудно выявляемым способом является манипулирование. Существуют иностранные методики выявления фактов манипулирования, но из-за специфики построения отчетности российских компаний данные методики не отражают фактического состояния проблемы и зачастую не могут быть применены. Одним из показателей, который дает свободу действий, является прибыль. Проанализировав рассчитанные показатели, была подтверждена возможность упорядочивания различных стратегий манипулирования с помощью коэффициентов начисления. В статье предложена методика выявления не только фактов, но и направлений манипулирования данными бухгалтерской (финансовой) отчетности. Выявлены направления манипулирования в зависимости от различных групп стейкхолдеров, данный подход позволяет определить этап, на котором возникает манипулирование. Подход строится на применении алгоритма кластеризации данных, который позволяет абстрагироваться от конкретной компании, оценить всю отрасль и выделить отраслевые ядра манипулирования. Комплексная проверка гипотезы и апробация методики осуществлялась на основании данных отчетности строительных компаний, а в дальнейшем может быть применена к любой сфере деятельности. Every day in the country a lot of financial decisions are made, which are based on financial information. The main source of such information is the data of accounting (financial) statements. However, many companies operate on the basis of the strategy of opportunism, benefit from artificially created information asymmetry. Companies can influence decisions made by banks, investors, rating agencies, counterparties and other economic actors, by deliberately misleading users of reporting. Data can be distorted by techniques such as veiling, manipulation and fraud. The most difficult to detect is manipulation. There are foreign methods for revealing the facts of manipulation, but because of the specifics of reporting by Russian companies, these methods do not reflect the actual state of the problem and can often not be applied. One of the indicators that give freedom of action is profit. After analyzing the calculated indicators, it was confirmed the possibility of ordering various strategies of manipulation with the help of the accrual coefficients. The article proposes a methodology for revealing not only the facts, but also the directions of manipulating the data of the accounting (financial) statements. The directions of manipulation are revealed depending on different groups of stakeholders, this approach makes it possible to determine the stage at which manipulation occurs. The approach is based on the application of the data clustering algorithm, which allows you to abstract from a specific company, evaluate the entire industry and identify the industry’s core manipulation. Complex testing of the hypothesis and approbation of the methodology was carried out on the basis of reporting data of construction companies, and in the future can be applied to any field of activity.
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Auditors perform preliminary analytical procedures to identify unusual or inconsistent relationships between expectations and recorded balances. The results of preliminary analytical procedures help auditors assess the risk that financial statements are materially misstated due to fraud. Via a survey of practicing auditors, we find that auditors rely heavily on prior-year balances and relations within the client’s financial data as benchmarks when developing expectations. Even though auditing standards describe additional benchmarks, which are less susceptible to management manipulation (e.g., industry trends), our survey results indicate that auditors are less apt to employ these benchmarks. Meanwhile, our empirical analyses of revenue frauds reveal that benchmarks derived from industry data, nonfinancial measures, and cash flows outperform both prior-year balances and relations within the client’s financial data. Of the benchmarks we examine, the difference between a company’s revenue growth and the revenue growth of its industry has historically been the best fraud indicator. Data Availability: Data are available from the authors upon request. JEL Classifications: M40; M41; M42; M48.
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Synopsis The research problem This study examines whether the effect of litigation risk on audit quality changes when auditors face high versus low regulatory risk under the Public Company Accounting Oversight Board (PCAOB) inspection regime. Motivation The establishment of the PCAOB under the Sarbanes–Oxley Act marked a fundamental change in the regulatory environment for the auditors. At the core of the PCAOB’s oversight of the audits of public companies are the inspections of individual audit engagements. While prior studies have found a positive effect of the PCAOB inspection program on audit quality, little is known about whether and how the regulatory risk imposed by PCAOB inspections influences the effect of litigation risk on audit quality. To the extent that both regulatory oversight and litigation threat share the common objective of motivating auditors to exert sufficient effort and perform high-quality audits, we are motivated to examine whether and how the stringent regulatory environment under the PCAOB regime affects auditors’ perception of, and response to, litigation risk. Hypothesis We posit that the significant and constant regulatory threat imposed by PCAOB inspections may change auditors’ perception of litigation, which is more remote and less frequent relative to regulatory inspections, such that litigation risk has a smaller effect on audit quality/effort when auditors face high versus low regulatory risk arising from the PCAOB inspections. However, there also exists opposing arguments that would suggest a nondecreasing effect of litigation risk on audit quality in the presence of high regulatory risk. Thus, we present our hypothesis in the null form: the effects of litigation risk on audit quality are not associated with regulatory risk under the PCAOB inspection regime. Target population Researchers, audit practitioners, regulatory authorities, policymakers, and firms. Adopted methodology We employ multivariate regression analysis featuring the ordinary least squares (OLS) estimation to test our hypothesis. In additional tests, we also use the probit estimation for binary dependent variables. Analyses Using a sample of 34,559 client-firm year observations for the period between 2005 and 2019, we estimate a multivariate regression model to examine whether and how the audit deficiencies identified in the PCAOB inspections influence the effect of litigation risk on audit quality exhibited at the client level. Findings Our main findings show that, while regulatory risk (proxied by PCAOB-identified audit deficiencies) and litigation risk (proxied by lawsuits filed against auditors/firms) each has a positive effect on audit quality, the interaction term of the two is negatively associated with audit quality. This rejects our null hypothesis and indicates that litigation risk has a smaller motivational effect when the auditors are faced with greater regulatory risk. Similar results are obtained using audit fees, financial restatements, and the propensity to report small profits as the alternative measures of audit quality. We further validate those results with alternative measures of regulatory risk and litigation risk. Our empirical evidence corroborates the views of audit practitioners, surveyed in Westermann et al. (2019), that auditors are increasingly concerned about regulatory risk, as opposed to litigation risk, under the PCAOB regime.
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We examine whether auditor political connections are associated with the SEC's oversight of audit clients . Specifically, we test whether auditors' political action committee contributions are associated with three SEC oversight actions: comment letters, investigations, and Accounting and Auditing Enforcement Releases (AAERs). Consistent with higher political connections inducing heightened scrutiny from the SEC, we find that the clients of auditors with higher political connections are more likely to receive comment letters and face SEC investigations. However, conditional on SEC investigation, we find no association between auditor political connections and the issuance of AAERs. We consider heightened attention from investors and analysts toward audit clients as one possible mechanism leading to increased SEC scrutiny because auditor political connections could be perceived as a red flag. Using EDGAR downloads and the number of earnings forecast revisions, we document evidence consistent with the existence of this mechanism. These findings add to our understanding of how auditor political connections could influence SEC oversight over audit clients.
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Abstract The Detection of Earnings Manipulation The paper profiles a sample of earnings manipulators, identifies their distinguishing characteristics,and estimates a model for detecting manipulation. The model’s variables are designed to capture either the effects of manipulation or preconditionsthat may prompt firms to engage in such activity. The results suggest a systematic relation between the probability of manipulation and financial statement variables. The evidence is consistent with accounting data being useful in detecting manipulation and assessing the reliability of accounting earnings. In holdout sample tests, the model identifies approximately half of the companies involved
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This paper was nominated for the American Accounting Association's Seminal Contributions to the Accounting Literature Award (See Related Research). As the first published precursor to the Sarbanes-Oxley Act of 2002, Section 704: Study of Enforcement Actions, it explores three questions related to the SEC's accounting enforcement program: (1) what types of accounting and auditing problems motivate enforcement actions, (2) what are the consequences of investigations on targets' financial statements, managers, and auditors, and (3) how do investors and other market agents view the SEC's actions? The SEC enforcement program, which consists of investigations and subsequent injunctive actions or administrative proceedings against offending registrants and auditors, is designed " to concentrate on particular problem areas and to anticipate emerging problems" (SEC,1989,p.1). The potential for SEC enforcement action provides incentives for corporate officers and independent CPAs to avoid unacceptable practices whose "effective prosecution is essential to preserving the integrity of the disclosure system" (SEC, 1989,p.81). The SEC summarizes its accounting-based enforcement actions in the Accounting and Auditing Enforcement Releases (AAERs). We examined 224 AAERs, issued between April 1982 and April 1989, describing the results of investigations against 188 firms. In the sample period, the SEC most often pursued overstatements of accounts receivable and inventories resulting from premature revenue recognition and delayed write-off, respectively. These two accounts make up 70% of the investigations. The income effects of these financial disclosure violations average more than 50% of reported income. We find that the disclosure of these reporting violations changed expectations of targets' future earnings as reflected in financial analysts' reduced earnings estimated after the disclosures.Disclosures and investigations of reporting violations have other consequences. Typically, targets' managers settle enforcement actions by consenting to an injunction that prohibits future violations of securities laws. Subsequently, more than 72% of the enforcement targets fired or forced the resignations of top managers and 81% were sued by their shareholders. In 42% of our sample, the SEC also censured the target's auditor; criticisms and penalties were more likely for smaller audit firms. In exploring how market agents react to the enforcement process, we focus on market returns around disclosures of alleged reporting violations, investigations, and final settlements. Disclosures of reporting violations are associated with average two-day abnormal returns of -13%; the magnitude of these returns is highly correlated with the earnings impact of the disputed accounting. We also observe abnormal returns of -6% at disclosures of investigations, even when the accounting errors were announced earlier. These negative returns imply substantial incentives for managers to avoid these investigation. We do not observe any changes in targets, share values at the investigations' final settlement. Section 2 describes the SEC enforcement process. Section 3 documents the effects of the SEC investigations and settlements on firms' financial statement, managers, and auditors. Section 4 addresses the stock market's reactions to the disclosure of reporting violations, investigations, and settlements. Section 5 provides conclusions and policy implications.
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We analyze a sample of firms accused of fraudulently overstating their earnings and examine the extent, if any, to which they paid additional income taxes on the allegedly fraudulent earnings. Based on restatements of current tax expense adjusted for the tax benefits of stock options, the evidence indicates that many firms included the overstated financial accounting income on their tax returns, thus overpaying their taxes in the process of inflating their accounting earnings. We estimate that the median firm sacrificed eight cents in additional income taxes per dollar of inflated pre-tax earnings. In aggregate, we estimate that the firms in our sample paid 320millionintaxesonoverstatedearningsofabout320 million in taxes on overstated earnings of about 3.36 billion. These results indicate how far managers of firms are willing to go to when allegedly inflating earnings.
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Although leading indicators are becoming increasingly important for equity valuation, disclosures of such indicators suffer from the absence of GAAP related guidance on content and presentation. We explicitly examine (i) whether one leading indicator—order backlog—predicts future earnings, and (ii) whether market participants correctly incorporate such predictive ability in determining share prices. We find that the stock market overweights the contribution of order backlog in predicting future earnings, and a hedge strategy that exploits such overweighting generates significant future abnormal returns. However, such mispricing is not due to analysts' inability to incorporate order backlog into their earnings forecasts.
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Ritter and Loughran~(1995a) and Spiess and Affleck-Graves~ (1995) document that firms issuing seasoned equity offerings (SEOs) severely underperform the stock market within five years after the offering. Our paper examines the hypothesis that SEO investors are too optimistic because they naively extrapolate earnings trends without fully adjusting for observable discretionary managerial reporting choices. We find that aggressive firms, which report high pre-SEO earnings at the expense of post-SEO earnings by taking high pre-issue discretionary current accruals, subsequently perform worse in terms of abnormal stock returns and industry-adjusted net income. Aggressive quartile firms earn a highly significant --48% four-year compounded abnormal return; conservative quartile firms earn an insignificant --7% four-year compounded abnormal return. In contrast with the pre-SEO discretionary current accruals, the non- discretionary current accruals and both discretionary and non- discretionary long-term accruals do not predict post-SEO returns reliably.
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This study investigates firms subject to accounting enforcement actions by the Securities and Exchange Commission for alleged violations of Generally Accepted Accounting Principles. We investigate: (i) the extent to which the alleged earnings manipulations can be explained by extant earnings management hypotheses; (ii) the relation between earnings manipulations and weaknesses in firms' internal governance structures; and (iii) the capital market consequences experienced by firms when the alleged earnings manipulations are made public. We find, that an important motivation for earnings manipulation is the desire to attract external financing at low cost. We show that this motivation remains significant after controlling for contracting motives proposed in the academic literature. We also find that firms manipulating earnings are: (i) more likely to have boards of directors dominated by management; (ii) more likely to have a Chief Executive Officer who simultaneously serves as Chairman of the Board; (iii) more likely to have a Chief Executive Officer who is also the firm's founder; (iv) less likely to have an audit committee; and (v) less likely to have an outside blockholder. Finally, we document that firms manipulating earnings experience significant increases in their costs of capital when the manipulations are made public.
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This paper investigates the press's role as a monitor or "watchdog" for accounting fraud. I find that the press fulfills this role by rebroadcasting information from other information intermediaries (analysts, auditors, and lawsuits) and by undertaking original investigation and analysis. Articles based on original analysis provide new information to the markets while those that rebroadcast allegations from other intermediaries do not. Consistent with a dual role for the press, I find that business-oriented press is more likely to undertake original analysis while nonbusiness periodicals focus primarily on rebroadcasting. I also investigate the determinates of press coverage, finding systematic biases in the types of firms and frauds for which articles are published. In general, the press covers firms and frauds that will be of interest to a broad set of readers and situations that are lower cost to identify and investigate.
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We examine the penalties imposed on the 585 firms targeted by SEC enforcement actions for financial misrepresentation from 1978-2002, which we track through November 15, 2005. The penalties imposed on firms through the legal system average only 23.5millionperfirm.Thepenaltiesimposedbythemarket,incontrast,arehuge.Ourpointestimateofthereputationalpenaltywhichwedefineastheexpectedlossinthepresentvalueoffuturecashflowsduetolowersalesandhighercontractingandfinancingcostsisover7.5timesthesumofallpenaltiesimposedthroughthelegalandregulatorysystem.Foreachdollarthatafirmmisleadinglyinflatesitsmarketvalue,onaverage,itlosesthisdollarwhenitsmisconductisrevealed,plusanadditional23.5 million per firm. The penalties imposed by the market, in contrast, are huge. Our point estimate of the reputational penalty-which we define as the expected loss in the present value of future cash flows due to lower sales and higher contracting and financing costs - is over 7.5 times the sum of all penalties imposed through the legal and regulatory system. For each dollar that a firm misleadingly inflates its market value, on average, it loses this dollar when its misconduct is revealed, plus an additional 3.08. Of this additional loss, 0.36isduetoexpectedlegalpenaltiesand0.36 is due to expected legal penalties and 2.71 is due to lost reputation. In firms that survive the enforcement process, lost reputation is even greater at $3.83. In the cross section, the reputation loss is positively related to measures of the firm's reliance on implicit contracts. This evidence belies a widespread belief that financial misrepresentation is disciplined lightly. To the contrary, reputation losses impose substantial penalties for cooking the books. Copyright 2008, Michael G. Foster School of Business, University of Washington, Seattle, WA 98195.
Article
In this study, I examine the association between the credibility of the financial reporting system and the quality of governance mechanisms. I use a sample of 87 firms identified by the SEC as fraudulently manipulating their financial statements. Consistent with prior research, results indicate that fraud firms have poor governance relative to a control sample in the year prior to fraud detection. Specifically, fraud firms have fewer numbers and percentages of outside board members, fewer audit committee meetings, fewer financial experts on the audit committee, a smaller percentage of Big 4 auditing firms, and a higher percentage of CEOs who are also chairmen of the board of directors. However, the results indicate that fraud firms take actions to improve their governance, and three years after fraud detection these firms have governance characteristics similar to the control firms in terms of the numbers and percentages of outside members on the board, but exceed the control firms in the number of audit committee meetings. I also investigate whether the improved governance influences informed capital market participants. The results indicate that analyst following and institutional holdings do not increase in fraud firms, suggesting that credibility was still a problem for these firms. However, the results also indicate that firms that take actions to improve governance have superior stock price performance, even after controlling for earnings performance. This suggests that investors appear to value governance improvements.
Article
This paper suggests a new measure of one aspect of the quality of working capital accruals and earnings. One role of accruals is to shift or adjust the recognition of cash flows over time so that the adjusted numbers (earnings) better measure firm performance. However, accruals require assumptions and estimates of future cash flows. We argue that the quality of accruals and earnings is decreasing in the magnitude of estimation error in accruals. We derive an empirical measure of accrual quality as the residuals from firm-specific regressions of changes in working capital on past, present, and future operating cash flows. We document that observable firm characteristics can be used as instruments for accrual quality (e.g., volatility of accruals and volatility of earnings). Finally, we show that our measure of accrual quality is positively related to earnings persistence.
Article
This paper examines whether auditor fees are associated with earnings management and the market reaction to the disclosure of auditor fees. Using data collected from proxy statements, we present evidence that non-audit fees are positively associated with small positive earnings surprises, the magnitude of absolute discretionary accruals, and the magnitude of income-increasing and income-decreasing discretionary accruals. In contrast, audit fees are negatively associated with these earnings management indicators. These results are robust to a variety of alternative variable definitions and model specifications. Specifically, contrary to the claims of Ashbaugh et al. (2002), the results are robust to the use of performance-matched discretionary accruals. Moreover, contrary to the claims of Francis and Ke (2002), the results for small positive earnings surprises are robust regardless of whether the comparison group is all other earnings surprises or small negative earnings surprises. Our final set of results provide evidence of a significant negative association between non-audit fees and share values on the date the fees were disclosed, although the effect is small in economic terms.
Article
This paper examines whether auditor fees are associated with earnings management and the market reaction to the disclosure of auditor fees. Using data collected from proxy statements, we present evidence that nonaudit fees are positively associated with small earnings surprises and the magnitude of discretionary accruals, while audit fees are negatively associated with these earnings management indicators. We also find evidence of a negative association between nonaudit fees and share values on the date the fees were disclosed, although the effect is small in economic terms.
Article
We consider some nonnormal regression situations in which there are many regressor varibles, and it is desired to determine good fitting models, according to the value of the likelihood ratio statistic for tests of submodels against the full model. Efficient computational algorithms for the normal linear model are adopted for use with nonnormal models. Even with as many as 10-15 regressor variables present, we find it is often possible to determine all of the better fitting models with relatively small amounts of computer time. The use of the procedures is illustrated on exponential, Poisson and binary regression models.
Article
This study empirically tests the prediction that the inclusion of larger proportions of outside members on the board of directors significantly reduces the likelihood of financial statement fraud. Results from logit regression analysis of 75 fraud and 75 no-fraud firms indicate that no-fraud firms have boards with significantly higher percentages of outside members than fraud firms; however, the presence of an audit committee does not significantly affect the likelihood of financial statement fraud. Additionally, as outside director ownership in the firm and outside director tenure on the board increase, and as the number of outside directorships in other firms held by outside directors decreases, the likelihood of financial statement fraud decreases.
Article
We provide new evidence that the inferior returns to growth stocks relative to value stocks are the result of expectational errors about future earnings performance. Our evidence demonstrates that growth stocks exhibit an asymmetric response to earnings surprises. We show that while growth stocks are at least as likely to announce negative earnings surprises as positive earnings surprises, they exhibit an asymmetrically large negative price response to negative earnings surprises. After controlling for this asymmetric price response, we find no remaining evidence of a return differential between growth and value stocks. We conclude that the inferior return to growth stocks is attributable to overoptimistic expectational errors that are corrected through subsequent negative earnings surprises.
Article
This paper investigates the incentives and the penalties related to earnings overstatements primarily in firms that are subject to accounting enforcement actions by the Securities and Exchange Commission (SEC). I find (1) that managers in treatment firms are more likely to sell their holdings and exercise stock appreciation rights in the period when earnings are overstated than are managers in control firms, and (2) that the sales occur at inflated prices. I do not find evidence that earnings overstatement in these firms is motivated by concerns about debt covenant violations or the cost of external financing. The evidence suggests that the monitoring of managers' trading behavior can be informative about the likelihood of earnings overstatement. Many economists believe that insider trading is an efficient method of compensating managers for their efforts. These economists argue that reputation losses would preclude managers from making profitable trades before periods of poor corporate performance. Consequently, this paper also investigates the employment and monetary penalties imposed on managers after the earnings overstatement is publicly discovered. This evidence reveals that (1) managers' employment losses subsequent to discovery are similar in firms that do and do not overstate earnings and (2) that the SEC is not likely to impose trading sanctions on managers in firms with earnings overstatement unless the managers sell their own shares as part of a firm security offering. The evidence suggests that neither employment or SEC-imposed monetary losses are effective in preventing the managers in these firms with extreme earnings overstatements from selling their stake in their firms in the face of declining performance.
Article
The balance sheet accumulates the effects of previous accounting choices, so the level of net assets partly reflects the extent of previous earnings management. We predict that managers' ability to optimistically bias earnings decreases with the extent to which the balance sheet overstates net assets relative to a neutral application of GAAP. To test this prediction, we examine the likelihood of reporting various earnings surprises for 3,649 firms during 1993-1999. Consistent with our prediction, we find that the likelihood of reporting larger positive or smaller negative earnings surprises decreases with our proxy for overstated net asset values.
Article
We assess the usefulness of deferred tax expense in detecting earnings management. Assuming greater discretion under GAAP than under tax rules, and assuming managers exploit such discretion to manage income upward primarily in ways that do not affect current taxable income, then such earnings management will generate book-tax differences that increase deferred tax expense. Our results provide evidence consistent with deferred tax expense generally being incrementally useful beyond total accruals and abnormal accruals derived from two Jones-type models in detecting earnings management to avoid an earnings decline and to avoid a loss. Only total accruals is incrementally useful in detecting earnings management to meet analysts' earnings forecasts. Deferred tax expense is more accurate than the accrual measures in classifying firm-years as successfully avoiding a loss, whereas no one measure is more accurate in classifying firm-years as avoiding an earnings decline or meeting analysts' forecasts.
Article
The dramatic increase in the number of restatements filed over the past years has been attributed to numerous causes, including the complexity of the accounting standards, internal control reviews, changes in materiality thresholds, the overly conservative nature of auditors, earnings management, increased transaction complexity, and the second guessing of management judgments, by a variety of interested parties. However, empirical evidence on the underlying causes of restatements has been lacking. This study provides such evidence by directly addressing the questions of: (1) to what causes are restatements attributed, (2) to what characteristics of the accounting standards are restatements attributed, and (3) has the materiality threshold for restatements has fallen over the years? Relying on the restating companies’ disclosures about restatements, we find that companies most often attribute restatements to basic internal company errors unrelated to any specific characteristic of the accounting standards. We also find that, for those restatements attributed to some characteristic of the accounting standards, the primary contributing factor is the lack of clarity in applying the standards and/or the proliferation of the literature due to the lack of clarity in the original standard. These findings should be of interest to standard setters and regulators in addressing the proliferation of restatements and to academics in using restatements as proxies for constructs of interest in research.
Article
This study identifies the contemporaneous risk factors empirically related to financial statement fraud. Extant research identifies a number of individual factors related to fraud in various settings. In this study we examine an array of potential fraud risk factors in order to identify a comprehensive set of coexistent factors that are consistently linked to the incidence of financial statement fraud. Further, using the identified fraud risk factors, we construct a robust fraud prediction model. The analysis yields a number of significant factors related to pressure and opportunity. Using the significant fraud risk factors we then construct a fraud prediction model. The model correctly classifies fraud and no-fraud firms approximately 69.77 percent of the time, a substantial improvement over other fraud prediction models.
Article
We measure the power of some simple financial statement analysis techniques for identifying instances of significant earnings overstatements, and then contrast the results with those from several measures of unexpected accruals. Our results suggest that relative to a group of matched control firms, those firms identified by the SEC as having overstated earnings outside the boundaries of GAAP have significantly different financial statement characteristics. We also find that a simple measure of accruals, supplemented by a few financial statement indicators, has greater success in identifying these earnings overstatements than measures of unexpected accruals on which researchers typically rely. Because SEC enforcement actions likely represent the most extreme forms of upwards earnings management, they are a reflection of where most practical concerns are directed about the existence of accounting manipulation. Our results highlight a lack of power among widely used measures of unexpected accruals, consistent with the view that methods based on the approach of Jones (1991) are primarily a response to researchers' concerns with type I errors, rather than the type II errors which we characterize as being of primary practical concern. We conclude that future research directed at improved measures of earnings management for practical purposes might profitably focus on insights from financial statement analysis rather than further incremental refinement of models used to identify unexpected accruals.
Article
In this study, I examine the association between the credibility of the financial reporting system and the quality of governance mechanisms. I use a sample of 87 firms identified by the SEC as fraudulently manipulating their financial statements. Consistent with prior research, results indicate that fraud firms have poor governance relative to a control sample in the year prior to fraud detection. Specifically, fraud firms have fewer numbers and percentages of outside board members, fewer audit committee meetings, fewer financial experts on the audit committee, a smaller percentage of Big 4 auditing firms, and a higher percentage of CEOs who are also chairmen of the board of directors. However, the results indicate that fraud firms take actions to improve their governance and that three years after fraud detection these firms have governance characteristics similar to the control firms in terms of the numbers and percentages of outside members on the board, but exceed the control firms in the number of audit committee meetings. I also investigate whether the improved governance influences informed capital market participants. The results indicate that analyst following and institutional holdings do not increase in fraud firms, suggesting that credibility was still a problem for these firms. However, the results also indicate that firms that take actions to improve governance have superior stock price performance, even after controlling for earnings performance. This suggests that governance improvements appear to be valued by investors.
Article
This paper examines the extent, if any, to which firms pay additional income taxes on allegedly fraudulent earnings. Our sample consists of firms that restated their financial statements in conjunction with SEC allegations of accounting fraud during the years 1996 to 2002. By examining firms that were accused of fraud by the SEC we obtain a relatively clean sample of earnings overstatements and avoid having to rely on models of earnings management. By further focusing on restatements, we are able to estimate how much income tax was paid on the overstated earnings. The estimates in this paper represent the most direct evidence to date that firms are willing to sacrifice substantial cash to inflate their accounting earnings. Our detailed analysis of a sample of firms admitting to large earnings overstatements indicates that the mean firm sacrificed eleven cents in additional income taxes per dollar of inflated pre-tax earnings. In aggregate, the firms in our sample paid 320millionintaxesonoverstatedearningsofabout320 million in taxes on overstated earnings of about 3.36 billion. These results illustrate the stark trade-off faced by firms and managers contemplating earnings manipulation - the choice between (non-cash) accounting earnings and (cash) taxes.
Article
This study investigates firms subject to accounting enforcement actions by the Securities and Exchange Commission for alleged violations of Generally Accepted Accounting Principles. We investigate: (i) the extent to which the alleged earnings manipulations can be explained by extant earnings management hypotheses; (ii) the relation between earnings manipulations and weaknesses in firms' internal governance structures; and (iii) the capital market consequences experienced by firms when the alleged earnings manipulations are made public. We find that an important motivation for earnings manipulation is the desire to attract external financing at low cost. We show that this motivation remains significant after controlling for contracting motives proposed in the academic literature. We also find that firms manipulating earnings are: (i) more likely to have boards of directors dominated by management; (ii) more likely to have a Chief Executive Officer who simultaneously serves as Chairman of the Board; (iii) more likely to have a Chief Executive Officer who is also the firm's founder, (iv) less likely to have an audit committee; and (v) less likely to have an outside blockholder. Finally, we document that firms manipulating earnings experience significant increases in their costs of capital when the manipulations are made public.
Article
It is well-established that the realized returns of ?growth? stocks have been low relative to other stocks. We show that this phenomenon is explained by a large and asymmetric response to negative earnings surprises for growth stocks. After controlling for this effect, there is no longer evidence of a stock return differential between growth stocks and other stocks. Our evidence is more consistent with investors having naively optimistic expectations about the prospects of growth stocks (e.g., Lakonishok, Shleifer, and Vishny, 1994) than with the existence of unidentified risk factors that are lower for growth stocks (e.g., Fama and French, 1992).
Article
This paper evaluates alternative models for detecting earnings management. The paper restricts itself to models that assume the construct being managed is discretionary accruals, since such models are commonly used in the extant accounting literature. Existing models range from simple models in which discretionary accruals are measured as total accruals, to more sophisticated models that separate total accruals into a discretionary and a non-discretionary component. Prior to this paper, there had been no systematic evidence bearing on the relative performance of these alternative models at detecting earnings management. This paper evaluates the relative performance of the competing models by comparing the specification and power of commonly used test statistics across the measures of discretionary accruals generated by each model. The specification of the test statistics is evaluated by examining the frequency with which they generate type I errors for a random sample of firm-years and for samples of firm-years with extreme financial performance. We focus on samples with extreme financial performance because the stimuli investigated in previous research are frequently correlated with financial performance. The first sample of firms are targeted by the Securities and Exchange Commission for allegedly overstating annual earnings and the second sample is created by artificially introducing earnings management into a random sample of firms.
Article
This paper examines the implications of the off-balance-sheet treatment of operating leases for future earnings and stock returns. The property rights granted by an operating lease contract generate both future benefits (off-balance-sheet capital investment) and future obligations (off-balance-sheet financing liabilities) for the lessee. The change in the off-balance-sheet capital investment can be viewed as a form of growth in net operating assets and also a form of off-balance-sheet accruals. By examining the footnote disclosure on operating leases, this paper shows that, after controlling for current earnings, greater off-balance-sheet operating lease activities lead to lower future earnings. This finding is consistent with diminishing marginal returns to investment in operating lease activities. Additional tests show that investors incorrectly estimate the implications of off-balance-sheet lease activities for future earnings. A long-short investment strategy that exploits this misestimation generates significant future abnormal stock returns. These results suggest that the accrual anomaly documented in prior research extends to off-balance-sheet lease accruals.
Article
We examine the penalties imposed on all 585 firms that were targeted by SEC enforcement actions for financial misrepresentation from 1978 - 2002, which we track through November 15, 2005. The penalties imposed on firms through the legal system average only 23.5millionperfirm.Thepenaltiesimposedbythemarket,incontrast,arehuge.Ourpointestimateofthereputationalpenaltywhichwedefineastheexpectedlossinthepresentvalueoffuturecashflowsduetolowersalesandhighercontractingandfinancingcostsisover7.5timesthesumofallpenaltiesimposedthroughthelegalandregulatorysystem.Foreachdollarthatafirmmisleadinglyinflatesitsmarketvalue,onaverage,itlosesthisdollarwhenitsmisconductisrevealed,plusanadditional23.5 million per firm. The penalties imposed by the market, in contrast, are huge. Our point estimate of the reputational penalty - which we define as the expected loss in the present value of future cash flows due to lower sales and higher contracting and financing costs - is over 7.5 times the sum of all penalties imposed through the legal and regulatory system. For each dollar that a firm misleadingly inflates its market value, on average, it loses this dollar when its misconduct is revealed, plus an additional 3.08. Of this additional loss, 0.36isduetoexpectedlegalpenaltiesand0.36 is due to expected legal penalties and 2.71 is due to lost reputation. In firms that survive the enforcement process, lost reputation is even greater at $3.83. In the cross-section, the reputational penalty is positively related to measures of the firm's reliance on implicit contracts. This evidence belies a widespread belief that financial misrepresentation is disciplined lightly. To the contrary, reputation losses impose substantial penalties for cooking the books.
Article
This paper extends the work of Sloan (1996. The Accounting Review 71, 289) by linking accrual reliability to earnings persistence. We construct a model showing that less reliable accruals lead to lower earnings persistence. We then develop a comprehensive balance sheet categorization of accruals and rate each category according to the reliability of the underlying accruals. Empirical tests generally confirm that less reliable accruals lead to lower earnings persistence and that investors do not fully anticipate the lower earnings persistence, leading to significant security mispricing. These results suggest that there are significant costs associated with incorporating less reliable accrual information in financial statements.
Article
Studies examining managerial accounting decisions postulate that executives rewarded by earnings-based bonuses select accounting procedures that increase their compensation. The empirical results of these studies are conflicting. This paper analyzes the format of typical bonus contracts, providing a more complete characterization of their accounting incentive effects than earlier studies. The test results suggest that (1) accrual policies of managers are related to income-reporting incentives of their bonus contracts, and (2) changes in accounting procedures by managers are associated with adoption or modification of their bonus plan.
Article
We survey and interview more than 400 executives to determine the factors that drive reported earnings and disclosure decisions. We find that managers would rather take economic actions that could have negative long-term consequences than make within-GAAP accounting choices to manage earnings. A surprising 78% of our sample admits to sacrificing long-term value to smooth earnings. Managers also work to maintain predictability in earnings and financial disclosures. We also find that managers make voluntary disclosures to reduce information risk and boost stock price but at the same time, try to avoid setting disclosure precedents that will be difficult to maintain.
Article
We examine the specification and power of tests based on performance-matched discretionary accruals, and make comparisons with tests using traditional discretionary accrual measures (e.g., Jones and modified-Jones models). Performance matching on return on assets controls for the effect of performance on measured discretionary accruals. The results suggest that performance-matched discretionary accrual measures enhance the reliability of inferences from earnings management research when the hypothesis being tested does not imply that earnings management will vary with performance, or where the control firms are not expected to have engaged in earnings management.
Article
Ascertaining which enforcement mechanisms work to protect investors has been both a focus of recent work in academic finance and an issue for policy-making at international development agencies. According to recent academic work, private enforcement of investor protection via both disclosure and private liability rules goes hand in hand with financial market development, but public enforcement fails to correlate with financial development and, hence, is unlikely to facilitate it. Our results confirm the disclosure result but reverse the results on both liability standards and public enforcement. We use securities regulators’ resources to proxy for regulatory intensity of the securities regulator. When we do, financial depth regularly, significantly, and robustly correlates with stronger public enforcement. In horse races between these resource-based measures of public enforcement intensity and the most common measures of private enforcement, public enforcement is overall as important as disclosure in explaining financial market outcomes around the world and more important than private liability rules. Hence, policymakers who reject public enforcement as useful for financial market development are ignoring the best currently available evidence.
Article
My paper presents a model to detect earnings management among firms experiencing extreme financial performance, and compares the model's performance to that of discretionary accrual models. I found that the model provides timely assessments of the likelihood of manipulation, and that model-based trading strategies earn significant abnormal returns. I also present evidence suggesting that the specification of discretionary accrual models could be enhanced by adding lagged total accruals and a measure of past price performance as explanators. The evidence arises from studying actual instances of earnings management. Its implications are in line with the Guay et al. (1996, p. 104) conjecture that accrual models which take into account managers' incentives, and recognize that discretionary accruals reverse, have a better chance of identifying discretionary accruals. The results have implications for researchers investigating managers' accrual decisions in contexts such as security offerings and financial distress, where extreme performance limits the usefulness of accrual models.
Article
Assistant Professor of Finance, New York University. The author acknowledges the helpful suggestions and comments of Keith V. Smith, Edward F. Renshaw, Lawrence S. Ritter and the Journal' reviewer. The research was conducted while under a Regents Fellowship at the University of California, Los Angeles.
Article
This study empirically tests the prediction that the inclusion of larger proportions of outside members on the board of directors significantly reduces the likelihood of financial statement fraud. Results from logit regression analysis of 75 fraud and 75 no-fraud firms indicate that no-fraud firms have boards with significantly higher percentages of outside members than fraud firms; however, the presence of an audit committee does not significantly affect the likelihood of financial statement fraud. Additionally, as outside director ownership in the firm and outside director tenure on the board increase, and as the number of outside directorships in other firms held by outside directors decreases, the likelihood of financial statement fraud decreases.
Article
ABSTRACT This study examines whether auditors can effectively use nonfinancial measures (NFMs) to assess the reasonableness of financial performance and, thereby, help detect financial statement fraud (hereafter, fraud). If auditors or other interested parties (e.g., directors, lenders, investors, or regulators) can identify NFMs (e.g., facilities growth) that are correlated with financial measures (e.g., revenue growth), inconsistent patterns between the NFMs and financial measures can be used to detect firms with high fraud risk. We find that the "difference" between financial and nonfinancial performance is significantly greater for firms that committed fraud than for their nonfraud competitors. We also find that this difference is a significant fraud indicator when included in a model containing variables that have previously been linked to the likelihood of fraud. Overall, our results provide empirical evidence suggesting that NFMs can be effectively used to assess fraud risk. Copyright (c), University of Chicago on behalf of the Accounting Research Center, 2009.
Article
This paper suggests a new measure of one aspect of the quality of working capital accruals and earnings. One role of accruals is to shift or adjust the recognition of cash flows over time so that the adjusted numbers (earnings) better measure firm performance. However, accruals require assumptions and estimates of future cash flows. We argue that the quality of accruals and earnings is decreasing in the magnitude of estimation error in accruals. We derive an empirical measure of accrual quality as the residuals from firm-specific regressions of changes in working capital on past, present, and future operating cash flows. We document that observable firm characteristics can be used as instruments for accrual quality (e.g., volatility of accruals and volatility of earnings). Finally, we show that our measure of accrual quality is positively related to earnings persistence.
Article
Recent studies document that firms conducting seasoned equity offerings experience poor stock price and earnings performance in the post-offering period. I investigate whether earnings management around the time of the offering can explain a portion of the poor performance. Consistent with this explanation, I show that earnings management during the year around the offering predicts both earnings changes and market-adjusted stock returns in the following year. These findings suggest that the stock market temporarily overvalues issuing firms and is subsequently disappointed by predictable declines in earnings caused by earnings management.
Article
We provide evidence that CEO cash compensation is relatively less sensitive to pension expense than pension income, suggesting that compensation committees shield CEO cash compensation from pension expense amounts. We also provide evidence that managers use relatively higher expected rate of return estimates when reporting pension income, suggesting that managers select income-increasing accounting estimates in response to compensation committees’ greater emphasis on pension income in CEO cash compensation determinations. Pension cost amounts represent a unique setting to examine such behavior as their effect on CEO cash compensation can be detrimental or beneficial, but arise from the same underlying economic activity.
Article
This paper examines the abnormal accruals of a sample of 94 firms that reported debt covenant violations in annual reports. We expect debt covenant restrictions to influence accounting choices in the year preceding and the year of violation. Time-series and cross-sectional models are used to estimate ‘normal’ accruals. In the year prior to violation, both models indicate that ‘abnormal’ total and working capital accruals are significantly positive. In the year of violation, there is evidence of positive abnormal working capital accruals after controlling for management changes and auditor going concern qualifications.
Article
This paper investigates the press's role as a monitor or "watchdog" for accounting fraud. I find that the press fulfills this role by rebroadcasting information from other information intermediaries (analysts, auditors, and lawsuits) and by undertaking original investigation and analysis. Articles based on original analysis provide new information to the markets while those that rebroadcast allegations from other intermediaries do not. Consistent with a dual role for the press, I find that business-oriented press is more likely to undertake original analysis while nonbusiness periodicals focus primarily on rebroadcasting. I also investigate the determinates of press coverage, finding systematic biases in the types of firms and frauds for which articles are published. In general, the press covers firms and frauds that will be of interest to a broad set of readers and situations that are lower cost to identify and investigate. Copyright University of Chicago on behalf of the Institute of Professional Accounting, 2006.
Article
Seasoned equity issuers can raise reported earnings by altering discretionary ac- counting accruals. We find that issuers who adjust discretionary current accruals to report higher net income prior to the o⁄ering have lower post-issue long-run abnormal stock returns and net income. Interestingly, the relation between discretionary current accruals and future returns (adjusted for firm size and book-to-market ratio) is stronger and more persistent for seasoned equity issuers than for non-issuers. The evidence is consistent with investors naively extrapolating pre-issue earnings without fully adjusting for the potential manipulation of reported earnings. ( 1998 Elsevier Science S.A. All rights reserved. JEL classification: G14; G24; G32; M41