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An International Meeting of American Accounting
Association
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Using Deferred Tax Data to Detect Fraud |
Lili Sun
Rutgers - The State University of New Jersey
Michael Ettredge
University of Kansas
Picheng Lee
Pace University
Asokan Anandarajan
New Jersey Institute of Technology
Abstract: The paper examines whether deferred tax data can be used to develop red flag signals of fraud. We use a sample of 105 AAER fraud firms, and 105 control firms matched by year, asset size, and two-digit SIC code. Tax variables examined include book income minus taxable income (BMT), the change in BMT (BMTCHG), deferred tax expense (DTE), and the change in DTE (DTECHG). Our results indicate that among firms reporting positive pretax book income, BMT and DTE are significantly associated with fraud. Although tax-change-related variables BMTCHG and DTECHG are insignificant, models incorporating their interactions with an indicator for positive book income have significantly better fit than base model. This suggests that BMTCHG and DTECHG also provide evidence of fraud occurrence. In summary, this study identifies several new tax-related variables which are not currently in the red flag checklists recommended by Statement of Auditing Standards No. 99.