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Fraud dynamics and controls in organizations

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  • Davis, Jon S.
  • Pesch, Heather L.

Abstract

This paper develops an agent-based model to examine the emergent dynamic characteristics of fraud in organizations. In the model, individual heterogeneous agents, each of whom can have motive and opportunity to commit fraud and a pro-fraud attitude, interact with each other. This interaction provides a mechanism for cultural transmission through which attitudes regarding fraud can spread. Our benchmark analysis identifies two classes of organizations. In one class, we observe fraud tending toward a stable level. In the other class, fraud dynamics are characterized by extreme behaviors; organizations with mostly honest behavior suddenly change their state to mostly fraudulent behavior and vice versa. These changes seem to occur randomly over time. We then modify our model to examine the effects of various mechanisms thought to impact fraud in organizations. Each of these mechanisms has different impacts on the two classes of organizations in our benchmark model, with some mechanisms being more effective in organizations exhibiting stable levels of fraud and other mechanisms being more effective in organizations exhibiting unstable extreme behavior. Our analysis and results have general implications for designing programs aimed at preventing fraud and for fraud risk assessment within the audit context.

Suggested Citation

  • Davis, Jon S. & Pesch, Heather L., 2013. "Fraud dynamics and controls in organizations," Accounting, Organizations and Society, Elsevier, vol. 38(6), pages 469-483.
    • Handle: RePEc:eee:aosoci:v:38:y:2013:i:6:p:469-483
    DOI: 10.1016/j.aos.2012.07.005
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    References listed on IDEAS

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    1. Keith L. Jones & Gopal V. Krishnan & Kevin D. Melendrez, 2008. "Do Models of Discretionary Accruals Detect Actual Cases of Fraudulent and Restated Earnings? An Empirical Analysis," Contemporary Accounting Research, John Wiley & Sons, vol. 25(2), pages 499-531, June.
    2. Bearden, William O & Netemeyer, Richard G & Teel, Jesse E, 1989. "Measurement of Consumer Susceptibility to Interpersonal Influence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 15(4), pages 473-481, March.
    3. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    4. Merle Erickson & Michelle Hanlon & Edward L. Maydew, 2006. "Is There a Link between Executive Equity Incentives and Accounting Fraud?," Journal of Accounting Research, Wiley Blackwell, vol. 44(1), pages 113-143, March.
    5. David R. Finley, 1994. "Game Theoretic Analysis of Discovery Sampling for Internal Fraud Control Auditing," Contemporary Accounting Research, John Wiley & Sons, vol. 11(1), pages 91-114, June.
    6. Robert Axelrod, 1997. "Advancing the Art of Simulation in the Social Sciences," Working Papers 97-05-048, Santa Fe Institute.
    7. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    8. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    9. Robert Axtell & Robert Axelrod & Joshua M. Epstein & Michael D. Cohen, 1995. "Aligning Simulation Models: A Case Study and Results," Working Papers 95-07-065, Santa Fe Institute.
    10. Holtfreter, Kristy, 2005. "Is occupational fraud "typical" white-collar crime? A comparison of individual and organizational characteristics," Journal of Criminal Justice, Elsevier, vol. 33(4), pages 353-365.
    11. Juin‐jen Chang & Ching‐chong Lai, 2002. "Is the Efficiency Wage Efficient? The Social Norm and Organizational Corruption," Scandinavian Journal of Economics, Wiley Blackwell, vol. 104(1), pages 27-47, March.
    12. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
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    1. Roberto Pietra & Andrea Melis, 2016. "“Governance and corruption: is history repeating itself?” Fostering a debate and inviting contributions from a multidisciplinary perspective," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 20(4), pages 689-701, December.
    2. Monica Ramos Montesdeoca & Agustín J. Sánchez Medina & Felix Blázquez Santana, 2019. "Research Topics in Accounting Fraud in the 21st Century: A State of the Art," Sustainability, MDPI, vol. 11(6), pages 1-31, March.
    3. Aziza Laguecir & Bernard Leca, 2018. "Strategies of visibility in contemporary surveillance settings: Insights from misconduct concealment in financial markets, Critical Perspectives on Accounting," Post-Print hal-01914996, HAL.
    4. Mark E. Lokanan & Prerna Sharma, 2023. "Two Decades of Accounting Fraud Research: The Missing Meso-Level Analysis," SAGE Open, , vol. 13(3), pages 21582440231, September.
    5. Christina Philippou, 2024. "Expert Perceptions on Anti-bribery and Corruption Policies in Sports Governing Bodies: Implications for Ethical Climate Theory," Journal of Business Ethics, Springer, vol. 193(2), pages 427-440, August.
    6. Kuang, Yu Flora & Lee, Gladys, 2017. "Corporate fraud and external social connectedness of independent directors," Journal of Corporate Finance, Elsevier, vol. 45(C), pages 401-427.
    7. Wang, Yang & Ashton, John K. & Jaafar, Aziz, 2023. "Financial statement fraud, recidivism and punishment," Emerging Markets Review, Elsevier, vol. 56(C).
    8. Balakrishnan, Ramji & Penno, Mark, 2014. "Causality in the context of analytical models and numerical experiments," Accounting, Organizations and Society, Elsevier, vol. 39(7), pages 531-534.
    9. Liu, Chenyong & Ryan, David & Lin, Guoyu & Xu, Chunhao, 2023. "No rose without a thorn: Corporate teamwork culture and financial statement misconduct," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    10. Laguecir, Aziza & Leca, Bernard, 2019. "Strategies of visibility in contemporary surveillance settings: Insights from misconduct concealment in financial markets," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 62(C), pages 39-58.

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