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Detecting Fraud: The Role of the Anonymous Reporting Channel

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Abstract

The purpose of this paper is to examine whether anonymous reporting channels (ARCs) are effective in detecting fraud against companies. Fraud, which comprises predominantly asset misappropriation, represents a key operational risk and a major cost to organisations (ACFE, http://www.acfe.com/uploadedFiles/ACFE_Website/Content/rttn/2012-report-to-nations.pdf, 2012; KPMG, http://www.kpmg.com/AU/en/IssuesAndInsights/ArticlesPublications/Fraud-Survey/Documents/fraud-bribery-corruption-survey-2012v2.pdf, 2012). The fraud triangle (incentives, opportunities and attitudes) provides a framework for developing our understanding of how ARCs can increase detection of fraud. Using publicly listed company survey data collected by KPMG in Australia—where ARCs are not mandated—we find a positive association between ARCs and reported fraud. These results indicate that ARCs are effective in detecting fraud. Additional analysis reveals that small firms derive the greatest benefit from adopting ARCs. We also find that independent boards do not directly influence the detection of fraud, but companies with independent boards detect more fraud because they implement ARCs.

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Notes

  1. Part 9.4 AAA of the Act provides some protection for whistleblowers (Corporations Act 2001 (Cwlth)).

  2. Lee and Fargher (2013) similarly argue that the voluntary environment in Australian provides an opportunity to investigate the determinants of whistleblowing policy disclosures in the absence of a requirement for firms to adopt a whistleblowing policy.

  3. The term empirical refers to research that collects data using primarily archival or survey methodology.

  4. The incidence of reported fraud in firms with ARCs is not presented in the 2004, 2008 and 2010 KPMG Fraud Survey reports.

  5. A limitation of these descriptive analyses is that they do not control for other factors associated with fraud detection.

  6. The KPMG Fraud Survey is a biennial survey of fraud self-reported by Australian and New Zealand organisations since the early 1990s. The survey examines the extent and nature of fraud of public and private sector organisations. The latest KPMG Fraud Survey is available at http://www.kpmg.com/AU/en/IssuesAndInsights/ArticlesPublications/Fraud-Survey/Pages/fraud-bribery-corruption-survey-2012.aspx.

  7. Chapple et al. (2009) and Coram et al. (2008) use the 2004 KPMG Fraud Survey data in their published studies. To the authors’ knowledge, no published studies have used the 2006, 2008 or 2010 KPMG Fraud Survey data.

  8. Annual reports were obtained from the ASX website. Corporate governance items and other control variables were collected from the 2004, 2006, 2008 and 2010 annual reports.

  9. The 133 firms that did not report fraud may have experienced undetected fraud.

  10. The KPMG surveys cover four separate survey periods (i.e. 2004 survey captures the period from 1 April 2002 to 31 March 2004; 2006 survey captures the period from 1 April 2004 to 31 January 2006; 2008 survey captures the period from 1 February 2006 to 31 January 2008; 2010 survey captures the period from 1 February 2008 to 31 January 2010).

  11. The KPMG Fraud Survey asks respondents “are you aware of fraud occurring in your organisation during [the survey period]?” (i.e. see question 4.1 of the 2010 KPMG Fraud Survey).

  12. The KPMG Fraud Survey asks respondents “what avenues are available for the reporting of fraud?” and respondents are asked to tick a box indicating whether the avenue allows for anonymous reporting, regardless of whether the avenue is a hotline, email, fax or dropbox, or whether the avenue is internal or external to the organisation (i.e. question 3.2 of the 2010 KPMG Fraud Survey).

  13. As board (audit committee) size was skewed, we used the natural logarithm of board (audit committee) size in principal component analysis.

  14. The proportion of non-executive directors on the audit committee and board includes both independent and non-independent non-executive directors.

  15. For the 17 firms that did not have an audit committee, a value of zero was assigned for the various audit committee characteristics reflected in principal components 1 and 2.

  16. Whether a firm has a whistleblowing policy may also affect the incidence of reported fraud. However, of the 231 companies in the sample, 153 did not clearly state in their annual reports whether they had whistleblowing policies. Thus, we were unable to include this variable in our analysis.

  17. Of the 129,266 instances of fraud reported, more than 99 % related to asset misappropriation. Of the remaining fraud incidences, 12 were incidences of corruption and 52 were incidences of financial statement fraud.

  18. The sample size in Chapple et al. (2009) is 115 Australian and New Zealand publicly listed companies which responded to the 2004 KPMG Fraud Survey. Our study includes 84 respondents and excludes five New Zealand publicly listed companies, three Australian companies that were delisted during the survey period, ten Australian publicly listed companies with missing annual report data and 13 Australian publicly listed companies with missing survey data.

  19. These results contrast with Chapple et al. (2009), who found a negative association between the proportion of independent directors on the audit committee and asset misappropriation, and non-significant associations with all other variables measuring independence in their model. While Chapple et al. (2009) used the 2004 KPMG Fraud Survey data, the present study includes data from the 2004, 2006, 2008 and 2010 KPMG Fraud Surveys.

  20. The pseudo R 2 presented in the analysis is the Cox and Snell R 2. The Nagelkerke R 2 is 37.1 %.

  21. We remove the 15 firms that reported corruption and/or financial statement fraud in addition to asset misappropriation and re-estimate the logistic regression model, ARC remains significant at the 5 % level.

  22. The KPMG Fraud Survey asks respondents “how many fraud incidents in total were detected in that period?” (i.e. question 4.2 of the 2010 KPMG Fraud Survey).

  23. This is not consistent with descriptive statistics that indicated significant differences in corporate governance practices between firms that reported fraud and firms that did not report fraud. After controlling for firm characteristics (i.e. firm size, leverage, industry), corporate governance characteristics are not significant in the regression analysis.

  24. We estimate 11 separate regression models including the individual corporate governance items that comprise INDEPENDENCE and EXPERTISE one at a time. ARC remains significant at the 5 % level in the 11 logistic regression models. After controlling for firm characteristics in the regression analyses, 10 of the 11 governance items are not significant. FINEXPBOARD (proportion of financial experts on the board) is the only item that, when added individually, is associated with fraud, although the influence is marginal.

  25. Although the KPMG Fraud Survey asks respondents to provide the number of employees in their firms, 49 respondents in the sample did not provide this information. To ensure that results were robust to using the natural logarithm of number of employees as an alternate proxy for firm size, we remove the observations with missing employee data and re-estimate the regression analysis. Results are qualitatively similar with ARC positively associated with fraud in a one tailed test.

  26. Small firms (n = 115) had a mean market capitalisation of $99.242 million, a median of $79.600 million and standard deviation of $84.580 million (natural logarithm of market capitalisation \(\bar{x}\)  = 3.978, Md = 4.380, s = 1.357) and large firms (n = 116) had a mean market capitalisation of $6505.900 million, a median of $1678.350 million and standard deviation of $19,219.568 million (natural logarithm of market capitalisation \(\bar{x}\)  = 7.540, Md = 7.425 and s = 1.391).

  27. The KPMG Fraud Survey asks respondents “How long did the fraud continue before being detected?” (i.e. question 5.1 of the 2010 KPMG Survey).

  28. Late respondents are considered to be similar to non-respondents (Oppenheim 1996).

  29. Thirty-three firms completed the KPMG Fraud Survey twice (33 observations), eight firms completed the KPMG Fraud Survey thrice (16 observations) and one completed the KPMG Fraud Survey in all survey periods (i.e. 2004, 2006, 2008 and 2010 Surveys) (3 observations).

  30. After excluding repeat respondents, there were 84 firms that completed the 2004 KPMG Fraud Survey, 40 firms that completed the 2006 KPMG Fraud Survey, 45 firms that completed the 2008 KPMG Fraud Survey and 10 firms that completed the 2010 KPMG Fraud Survey.

  31. We also find EXPERTISE to be positively associated with fraud in the 2004 subsample, but negatively associated with fraud in the non-2004 subsample. Firms with financial and risk expertise on boards (subcommittees) were more likely to detect fraud in 2004, but less likely to detect fraud after 2004.

  32. An analysis of firms in our sample indicate, as expected, that compared to large firms, small firms have less independent boards (audit committees), (small firm \(\bar{x}\)  = −0.528, large firm \(\bar{x}\)  = 0.524, p value < 0.0005) and are less likely to have a code of ethics (small firm \(\bar{x}\)  = 0.713, large firm \(\bar{x}\)  = 0.940, p value < 0.0005).

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Acknowledgements

We would like to thank the late Professor Colin Ferguson for the provision of the KPMG Fraud Survey data.

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  1. Department of Accounting, Deakin University, Burwood, VIC, Australia

    Elka Johansson & Peter Carey

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Correspondence to Elka Johansson.

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Johansson, E., Carey, P. Detecting Fraud: The Role of the Anonymous Reporting Channel. J Bus Ethics 139, 391–409 (2016). https://doi.org/10.1007/s10551-015-2673-6

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