IDEAS home Printed from https://ideas.repec.org/a/kob/tjrevi/dec2014v4p1-25.html
   My bibliography  Save this article

Assessing the Risk of Fraud at Olympus and Identifying an Effective Audit Plan

Author

Listed:
  • Hironori Fukukawa

    (Graduate School of Commerce and Management, Hitotsubashi University, JAPAN)

  • Theodore J. Mock

    (School of Business Administration, University of California, Riverside, USA)

  • Rajendra P. Srivastava

    (School of Business, The University Of Kansas, USA)

Abstract

This paper introduces an approach to the assessment of financial statement fraud risk and audit program planning and illustrates its application by simulating its use in the 1999 audit of Olympus. The approach incorporates a rigorous approach to assessing risk and current standards and conventions to fraud risk assessment not in practice during the period when a substantial financial statement fraud occurred at Olympus. The approach described in this paper illustrates a ‘what-if’ analysis that suggests the possible effectiveness of using updated standards, practice and research on detecting financial statement fraud.In the proposed approach, which is based on the Theory of Belief Functions, auditors follow three steps: (1) fraud risk assessment at the overall financial statement level, (2) fraud risk assessment at an account level, and (3) assessment of account, transaction and evidence schemes used to perpetrate fraud. In the evidential network, formal auditor belief assessments concerning evidence obtained in each audit step are aggregated by using Dempster’s rule. High aggregated assessments of belief-in-fraud or plausibility-of-fraud which exceed the thresholds established by the audit firm requires the auditors to engage in further investigation, to heighten the level of professional skepticism, and, where appropriate, to adopt a forensic audit approach.The results of analyzing the 1999 audit of Olympus demonstrate that the applications of current standards applied jointly with our approach would have likely both indicated a high plausibility and belief that fraud existed and would have likely directed the audit team to effective forensic audit procedures.

Suggested Citation

  • Hironori Fukukawa & Theodore J. Mock & Rajendra P. Srivastava, 2014. "Assessing the Risk of Fraud at Olympus and Identifying an Effective Audit Plan," The Japanese Accounting Review, Research Institute for Economics & Business Administration, Kobe University, vol. 4, pages 1-25, December.
  • Handle: RePEc:kob:tjrevi:dec2014:v:4:p:1-25
    as

    Download full text from publisher

    File URL: https://www.rieb.kobe-u.ac.jp/tjar/article/vol4/pdf/1.Fukukawa_Mock_and_Srivastava.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Srivastava, Rajendra P., 2011. "An introduction to evidential reasoning for decision making under uncertainty: Bayesian and belief function perspectives," International Journal of Accounting Information Systems, Elsevier, vol. 12(2), pages 126-135.
    2. Mock, Theodore J. & Sun, Lili & Srivastava, Rajendra P. & Vasarhelyi, Miklos, 2009. "An evidential reasoning approach to Sarbanes-Oxley mandated internal control risk assessment," International Journal of Accounting Information Systems, Elsevier, vol. 10(2), pages 65-78.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Adi Masli & Matthew G. Sherwood & Rajendra P. Srivastava, 2018. "Attributes and Structure of an Effective Board of Directors: A Theoretical Investigation," Abacus, Accounting Foundation, University of Sydney, vol. 54(4), pages 485-523, December.
    2. Heise, David & Strecker, Stefan & Frank, Ulrich, 2014. "ControlML: A domain-specific modeling language in support of assessing internal controls and the internal control system," International Journal of Accounting Information Systems, Elsevier, vol. 15(3), pages 224-245.
    3. Jans, Mieke & Lybaert, Nadine & Vanhoof, Koen, 2010. "Internal fraud risk reduction: Results of a data mining case study," International Journal of Accounting Information Systems, Elsevier, vol. 11(1), pages 17-41.
    4. Abernathy, John L. & Barnes, Michael & Stefaniak, Chad, 2013. "A summary of 10 years of PCAOB research: What have we learned?," Journal of Accounting Literature, Elsevier, vol. 32(1), pages 30-60.
    5. Srivastava, Rajendra P., 2011. "An introduction to evidential reasoning for decision making under uncertainty: Bayesian and belief function perspectives," International Journal of Accounting Information Systems, Elsevier, vol. 12(2), pages 126-135.
    6. Desai, Vikram & Bucaro, Anthony C. & Kim, Joung W. & Srivastava, Rajendra & Desai, Renu, 2023. "Toward a better expert system for auditor going concern opinions using Bayesian network inflation factors," International Journal of Accounting Information Systems, Elsevier, vol. 49(C).
    7. Shi Qiu & Yuansheng Luo & Hongwei Guo, 2021. "Multisource evidence theory‐based fraud risk assessment of China's listed companies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1524-1539, December.
    8. Dieter De Smet & Anne-Laure Mention, 2011. "Improving auditor effectiveness in assessing KYC/AML practices: Case study in a Luxembourgish context," Managerial Auditing Journal, Emerald Group Publishing, vol. 26(2), pages 182-203, January.

    More about this item

    Keywords

    Financial Statement Fraud; Forensic Audit Procedures; Design Science; Theory of Belief Functions;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • M42 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Auditing
    • M48 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Government Policy and Regulation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kob:tjrevi:dec2014:v:4:p:1-25. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: TJAR Editorial Office (email available below). General contact details of provider: https://edirc.repec.org/data/rikobjp.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.