How to better detect cases of financial reporting fraud: some new findings from earnings restatements

François Aubert, Jean-François Gajewski and Lamya Kermiche

Chapter 2 in Research Handbook of Investing in the Triple Bottom Line, 2018, pp 29-52 from Edward Elgar Publishing

Abstract: This chapter examines the ability of the managed earnings component metric (MEC) and discretionary accrual-based models to detect financial reporting fraud. By using a comprehensive sample of Accounting and Auditing Enforcement Releases (AAERs) issued by the SEC during the reporting period January 1, 1993 to December 31, 2014, we show that using the innovative managed earnings component metric of a firm as an independent variable (Aubert and Grudnitski, 2012, 2014) – appears to be a more relevant indicator of accounting fraud than cross sectional models based on inspecting abnormal accruals estimated in the literature (Dechow et al., 2011; Hui et al., 2014). Overall, our findings contribute to substantially enhancing prior literature on corporate earnings materially misstated and should be of great interest for regulatory bodies interested in identifying and preventing voluntary financial misreporting such as the US Security and Exchange Commission, which has been continually improving its Accounting Quality Model (AQM or Robocop) fraud detection tool for many years.

Keywords: Business and Management; Economics and Finance; Environment (search for similar items in EconPapers)
Date: 2018
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