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    Behavioral implications of big data’s impact on audit j...
    research summary posted September 11, 2015 by Jennifer M Mueller-Phillips, last edited September 11, 2015, tagged 08.0 Auditing Procedures – Nature, Timing and Extent, 08.09 Impact of Technology on Audit Procedures, 09.0 Auditor Judgment 
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    Title:
    Behavioral implications of big data’s impact on audit judgment and decision making and future research directions.
    Practical Implications:

    The authors outline potential pitfalls in the use of big data noted in auditing and psychology literature. Specifically, they focus on areas in which auditor decision making may be negatively influenced. They note that big data may lead to inefficient and/or incorrect decisions resulting from having too much information, not being able to determine what is relevant to the decision, not finding correct patterns in the data/finding incorrect patterns, and having data which may be too ambiguous to be used effectively. They then outline potential solutions to these problems, such as having decision aids, fitting the task to the system to auditor experience level, and providing contextual (“big picture”) training.

    Citation:

    Brown-Liburd, H., H. Issa, and D. Lombardi. 2015. Behavioral implications of big data’s impact on audit judgment and decision making and future research directions. Accounting Horizons 29(2): 451-468.

    Keywords:
    Big data, audit judgment, data analytics, information processing weaknesses
    Purpose of the Study:

    Big datahigh-volume, high-velocity, and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision makinghas been the new trendy topic in the future of auditing. This paper outlines potential implications on the actions of the auditor resulting from the use of big data, specifically drawing from literature on psychology and auditing.

    Design/Method/ Approach:

    This paper summarizes the current literature in psychology and auditing specifically to bring to light potential issues resulting from incorporation of big data in auditing. No data is used and no analyses are performed.

    Findings:

    The authors find four primary areas where research in auditing and psychology indicate potential negative effects of big data on audit performance, specifically in auditor judgment and decision making:

    • Auditors may make inefficient decisions, struggle to differentiate relevant information, struggle to identify relationships between detail and overall trends, and disregard large portions of information (information overload).
    • Auditors may make poorer decisions due to the excess of irrelevant information innate in big data. They may be unable to filter relevant information from the noise, thus being less efficient in analyzing data and potentially using irrelevant information in decision making (information relevance).
    • The sheer magnitude of data to analyze may force auditors to become worse at recognizing patterns, applying knowledge to the audit task, weighting evidence, or extrapolating patterns into longer times series (pattern recognition).
    • Auditorsif they have a low tolerance for ambiguitymay neglect information once a simple solution or response is identified, potentially ignoring relevant but more complex information (ambiguity).

    The authors then provide examples of solutions to these problems, such as 1) providing decision models 2) having inexperienced auditors use expert systems (requires minimal auditor interpretation) 3) provide auditors with more contextual experience and training so they can interpret patterns in big data 4) leverage predictive models that can indicate areas of increased risk.

    Category:
    Auditing Procedures - Nature - Timing and Extent, Auditor Judgment
    Sub-category:
    Impact of Technology on Audit Procedures Confirmation – Process and Evaluation of Responses