Non-fraud Firms Research Articles

The relation between earnings management and financial statement fraud

Abstract This paper provides new evidence on the characteristics of firms that commit financial statement fraud. We examine how previous earnings management impacts the likelihood that a firm will commit financial statement fraud and in doing so develop three new fraud predictors. Using a sample of 54 fraud and 54 non-fraud firms, we find that fraud firms are more likely to have managed earnings in prior years and that earnings management in prior years is associated with a higher likelihood that firms that meet or beat analyst forecasts or that inflate revenue are committing fraud. We further find that fraud firms are more likely to meet or beat analyst forecasts and inflate revenue than non-fraud firms are even when there is no evidence of prior earnings management. This paper contributes to the fraud detection literature and the earnings management literature, and can help practitioners and regulators develop better fraud detection models.

Financial Application of Multi-Instance Learning: Two Greek Case Studies

The problems of bankruptcy prediction and fraud detection have been extensively considered in the financial literature. The objective of this work is twofold. Firstly, we investigate the efficiency of multi-instance learning in bankruptcy prediction. For this reason, a number of experiments have been conducted using representative learning algorithms, which were trained using a data set of 150 failed and solvent Greek firms in the recent period. It was found that multi-instance learning algorithms could enable experts to predict bankruptcies with satisfying accuracy. Secondly, we explore the effectiveness of multi-instance learning techniques in detecting firms that issue fraudulent financial statements (FFS). Therefore, a number of experiments have been conducted using representative learning algorithms, which were trained using a data set of 164 fraud and non-fraud Greek firms. The results show that MIBoost algorithm with Decision Stump as base learner had the best accuracy in comparison with other multi-instance learners and single supervised machine learning techniques.

Making words work: Using financial text as a predictor of financial events

We develop a methodology for automatically analyzing text to aid in discriminating firms that encounter catastrophic financial events. The dictionaries we create from Management Discussion and Analysis Sections (MD&A) of 10-Ks discriminate fraudulent from non-fraudulent firms 75% of the time and bankrupt from nonbankrupt firms 80% of the time. Our results compare favorably with quantitative prediction methods. We further test for complementarities by merging quantitative data with text data. We achieve our best prediction results for both bankruptcy (83.87%) and fraud (81.97%) with the combined data, showing that that the text of the MD&A complements the quantitative financial information.

Is There Penalty for Crime: Corporate Scandal and Management Turnover in China

Corporate fraud scandals have plagued the emerging markets such as China. This paper studies the cost to Chinese firms and their management for committing fraud. We find that the enforcement actions on firms with violation of securities laws from the regulation authorities are not severe. The stock price reactions to revelation of scandals are negative and statistically significant. We particularly examine the management turnover associated with the scandals. We find that fraud firms have higher management turnover than the matching non-fraud firms. However, we track down where the Chairman and CEO land after the turnover, and find a large portion of those leaving the fraud firms move to management positions in other firms and many of them actually even get promotion. Only a very small portion of CEOs and Chairmen receive legal or administrative penalty. We further find that Chairman and CEO with certain political background are less likely to receive legal or administrative penalties. We argue that the low effectiveness of law and lack of reputation mechanism on managerial labor market leads to the rampancy of corporate frauds and stagnancy of stock market development in China. Our findings provide direct evidence that legal system affects the stock market development.

Can financial ratios detect fraudulent financial reporting?

Fraudulent financial reporting is a matter of grave social and economic concern. The Treadway Commission recommended that the Auditing Standards Board require the use of analytical procedures to improve the detection of fraudulent financial reporting. This is an exploratory study to determine if financial ratios of fraudulent companies differ from those of nonfraudulent companies. Fraudulent firms were identified by examining the SEC's Accounting and Auditing Enforcement Releases issued between 1982 and 1999. The fraudulent firms (n=79) were then matched with nonfraudulent firms on the basis of firm size, time period, and industry. Using this matched‐pairs design, ratio analysis for a seven‐year period (i.e. the fraud year −/+ 3 years) was conducted on 21 ratios. Overall, 16 ratios were found to be significant. Of these, only three ratios were significant for three time periods. Of the 16 statistically significant ratios, only five were significant during the period prior to the fraud year. Using discriminant analysis, misclassifications for fraud firms ranged from 58 percent to 98 percent. These results provide empirical evidence of the limited ability of financial ratios to detect and/or predict fraudulent financial reporting.

Audit Firm Tenure and Fraudulent Financial Reporting

The Sarbanes-Oxley Act (2002) required the U.S. Comptroller General to study the potential effects of requiring mandatory audit firm rotation. The General Accounting Office (GAO) concludes in its recently released study of mandatory audit firm rotation that “mandatory audit firm rotation may not be the most efficient way to strengthen auditor independence” (GAO 2003, Highlights). However, the GAO also suggests that mandatory audit firm rotation could be necessary if the Sarbanes-Oxley Act's requirements do not lead to improved audit quality (GAO 2003, 5). We examine the relation between audit firm tenure and fraudulent financial reporting. Comparing firms cited for fraudulent reporting from 1990 through 2001 with both a matched set of non-fraud firms and with the available population of non-fraud firms, we find that fraudulent financial reporting is more likely to occur in the first three years of the auditor-client relationship. We fail to find any evidence that fraudulent financial reporting is more likely given long auditor tenure. Our results are consistent with the argument that mandatory audit firm rotation could have adverse effects on audit quality.

The Difference between Earnings and Operating Cash Flow as an Indicator of Financial Reporting Fraud*

AbstractThis paper examines the relation between earnings and operating cash flow to derive and test an indicator of financial statement fraud. Accrual measurement concepts indicate that financial statement fraud should be associated with high levels of earnings relative to operating cash flow. We demonstrate that the excess of earnings over operating cash flow is extreme in most fraud cases in years immediately prior to the fraud discovery based on a sample of 56 fraud cases from 1978 to 1991. We compare the distribution of the earnings minus operating cash flow variable for fraud firms with that for a sample of 60,453 firm‐years for firms listed on COMPUSTAT. We test a logistic regression model in which the discovery/nondiscovery of fraud is the dependent variable, and earnings minus operating cash flow is the explanatory variable. Other control variables are included in the model based on prior studies. Results are consistent with expectations derived from accrual measurement theory. We then examine the predictive ability of the model using our sample of fraud firms and a sample of nonfraud firms in the same four‐digit SIC code industries. Observations for the fraud firms are for the fiscal year prior to the discovery of fraud. Observations for the nonfraud firms are for the same fiscal years as the fraud firms in the same industries. The predictive ability of the model, including the excess of earnings over operating cash flow, is substantially higher than the predictive ability of the model omitting this variable. We conclude that the earnings‐operating cash flow relation provides important information for those interested in identifying financial statement fraud, especially when considered in conjunction with other factors associated with fraud risk.