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Detecting and Predicting Accounting Irregularities: A Comparison of Commercial and Academic Risk Measures

43 Pages Posted: 2 Feb 2010 Last revised: 5 Feb 2015

Richard A. Price III

University of Oklahoma

Nathan Y. Sharp

Texas A&M University - Department of Accounting

David A. Wood

Brigham Young University - School of Accountancy

Multiple version iconThere are 2 versions of this paper

Date Written: 2011

Abstract

Although a substantial body of academic research is devoted to developing and testing risk proxies that detect accounting irregularities, the academic literature has paid little attention to commercially developed risk measures. This is surprising given the general consensus that academic risk measures have relatively poor construct validity. We compare the commercially developed Accounting and Governance Risk (AGR) and Accounting Risk (AR) measures with academic risk measures to determine which best detects financial misstatements that result in Securities and Exchange Commission enforcement actions, egregious accounting restatements, and shareholder lawsuits related to accounting improprieties. We find that the commercially developed risk measures outperform the academic risk measures in all head-to-head tests for detecting misstatements. The commercial measures also perform as well as or better than the academic measures in new tests that predict future accounting irregularities using numbers reported one year before the misreporting even begins. Our results suggest commercially developed risk proxies may be useful to practitioners and academics trying to detect or predict accounting irregularities.

Keywords: accounting irregularities, detecting fraud, predicting fraud, risk measures, commercial risk ratings

JEL Classification: M41, G30, K22

Suggested Citation

Price, Richard A. and Sharp, Nathan Y. and Wood, David A., Detecting and Predicting Accounting Irregularities: A Comparison of Commercial and Academic Risk Measures (2011). Accounting Horizons, Vol. 25, No. 4, 2011. Available at SSRN: https://ssrn.com/abstract=1546675 or http://dx.doi.org/10.2139/ssrn.1546675

Richard Price

University of Oklahoma ( email )

307 W Brooks
Norman, OK 73019
United States
405-325-5759 (Phone)

Nathan Sharp (Contact Author)

Texas A&M University - Department of Accounting ( email )

4353 TAMU
College Station, TX 77843-4353
United States
979-845-0338 (Phone)

David Wood

Brigham Young University - School of Accountancy ( email )

518 TNRB
Brigham Young University
Provo, UT 84602
United States
801-422-8642 (Phone)
801-422-0621 (Fax)

HOME PAGE: http://marriottschool.byu.edu/employee/employee.cfm?emp=daw44

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