Accounting fraud

This monograph is intended to inform readers about the detection of financial statement fraud, with a primary focus on the analysis of fraud prediction models. Our intended audience includes academic researchers, doctoral candidates, and graduate students in accounting, finance, and economics with an interest in the empirical study of financial statement fraud. We also hope to inform practitioners and regulators who rely on academic research to support their efforts in detecting or preventing fraudulent financial reporting. Our central interest lies in detecting the most severe form of financial misreporting, that is, intentional financial statement fraud. However, we also consider the broader context in which such behavior occurs. For example, we discuss the incentives and opportunities that more generally give rise to financial misreporting, including less severe forms of misreporting such as accrual and real earnings management, the expanding role of auditors in detecting fraud, and how the combination of reporting incentives, constraints, and trade-offs associated with these less egregious practices can, over time, contribute to a progression along what we term the “road to fraud.” Nonetheless, our primary focus remains on the methodological challenges of fraud prediction, including the limitations of prediction models, the metrics used to assess prediction model performance, and potential avenues for future financial statement fraud prediction research.