Auditing Section Research Summaries Space

A Database of Auditing Research - Building Bridges with Practice

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  • Jennifer M Mueller-Phillips
    Finding Needles in a Haystack: Using Data Analaytics to...
    research summary posted June 26, 2017 by Jennifer M Mueller-Phillips, tagged 06.02 Fraud Risk Models, 08.09 Impact of Technology on Audit Procedures 
    Title:
    Finding Needles in a Haystack: Using Data Analaytics to Improve Fraud Predication
    Practical Implications:

    Data analytics can be used to create fraud prediction models that help auditors improve audit planning decisions. It can also be used to help regulators identify firms for potential fraud investigation. In particular, the SEC is investing resources to develop better fraud risk models and the results of this study could be useful. 

    Citation:

    Perols, Johan L., R. M. Bowen, C. Zimmermann, and B. Samba. 2017. “Finding Needles in a Haystack: Using Data Analytics to Improve Fraud Prediction”. The Accounting Review. 92.2 (2017): 221.

    Home:

    http://commons.aaahq.org/groups/e5075f0eec/summary

  • Jennifer M Mueller-Phillips
    Infer, Predict, and Assure: Accounting Opportunities in Data...
    research summary posted September 21, 2015 by Jennifer M Mueller-Phillips, tagged 08.0 Auditing Procedures – Nature, Timing and Extent, 08.09 Impact of Technology on Audit Procedures 
    Title:
    Infer, Predict, and Assure: Accounting Opportunities in Data Analytics.
    Practical Implications:

    This article is important to practitioners as well as academics because they will be using data analytics in accounting and auditing tasks and will need to specify system design characteristics needed to effectively accomplish these tasks. The authors identify several research questions for further study.

    Citation:

    Schneider, G. P., J. Dai, D. J. Janvrin, K. Ajayi, and R. L. Raschke. 2015. Infer, Predict, and Assure: Accounting Opportunities in Data Analytics. Accounting Horizons 29 (3): 719-742.

  • Jennifer M Mueller-Phillips
    Big Data in Accounting: An Overview.
    research summary posted September 21, 2015 by Jennifer M Mueller-Phillips, tagged 01.0 Standard Setting, 01.01 Changes in Reporting Formats, 01.02 Changes in Audit Standards, 08.0 Auditing Procedures – Nature, Timing and Extent, 08.09 Impact of Technology on Audit Procedures, 09.0 Auditor Judgment 
    Title:
    Big Data in Accounting: An Overview.
    Practical Implications:

    The availability of Big Data will precipitate substantive changes in accounting education, research, and practice. In education, in particular accounting and auditing, the use of Big Data will increase the statistical and IT content in curricula, probably breaking the current set of limitations represented in the CPA exam. Research in the more traditional fields in accounting, such as capital markets research, will benefit from dimensional increases in data availability and will be conditional on improvements of the researcher’s skill sets in areas such as modeling, statistics, and text mining. Practice, in particular internal audit departments, will be the leading facilitator of accounting Big Data usage, while attempting to keep abreast or in sync with the developments in corporate data utilization in fields like marketing, supply chain, and customer services.

    Citation:

    Vasarhelyi, M. A., A. Kogan, and B. M. Tuttle. 2015. Big Data in Accounting: An Overview. Accounting Horizons 29 (2): 381-396.

  • Jennifer M Mueller-Phillips
    Toward Effective Big Data Analysis in Continuous Auditing.
    research summary posted September 21, 2015 by Jennifer M Mueller-Phillips, tagged 08.0 Auditing Procedures – Nature, Timing and Extent, 08.09 Impact of Technology on Audit Procedures 
    Title:
    Toward Effective Big Data Analysis in Continuous Auditing.
    Practical Implications:

    The Big Data qualities of Volume, Velocity, Variety, and Veracity contribute to the creation of the following Big Data Gaps: Data Consistency, Data Integrity, Data Identification, Data Aggregation, and Data Confidentiality. These Big Data Gaps create challenges for current CA systems. The paper outlines possible solutions to these gaps along with needed research topics with the aim of increasing the applicability of continuous auditing systems to Big Data. Big Data is a business phenomenon that is here to stay, and CA systems need to adapt to its challenges.

    Citation:

    Zhang, J., X. Yang, and D. Appelbaum. 2015. Toward Effective Big Data Analysis in Continuous Auditing. Accounting Horizons 29 (2): 469-476.

  • Jennifer M Mueller-Phillips
    Big data analytics in financial statement audits.
    research summary posted September 11, 2015 by Jennifer M Mueller-Phillips, tagged 08.0 Auditing Procedures – Nature, Timing and Extent, 08.09 Impact of Technology on Audit Procedures, 10.0 Engagement Management 
    Title:
    Big data analytics in financial statement audits.
    Practical Implications:

    This article provides a concise introduction to Big Data analytics by providing examples of Big Data success stories in non-audit fields and drawing auditing parallels. It then indicates several characteristics of Big Data which should be considered when implementing Big Data analytics, specifically as they relate to audit procedures.

    Citation:

    Cao, M., R. Chychyla, and T. Stewart. 2015. Big data analytics in financial statement audits. Accounting Horizons 29 (2): 423-429.

  • Jennifer M Mueller-Phillips
    Big data as complementary audit evidence.
    research summary posted September 11, 2015 by Jennifer M Mueller-Phillips, tagged 08.0 Auditing Procedures – Nature, Timing and Extent, 08.09 Impact of Technology on Audit Procedures, 09.0 Auditor Judgment, 09.03 Adequacy of Evidence 
    Title:
    Big data as complementary audit evidence.
    Practical Implications:

    Incorporating Big Data into an audit poses several challenges. This article establishes how Big Data analytics satisfy requirements of audit evidence, namely that it is sufficient, reliable, and relevant. The authors bring up practical challenges (such as transferring information, privacy protection, and integration with traditional audit evidence) and provide suggestions for addressing them in incorporating Big Data into audit evidence. They also suggest that Big Data can complement tradition audit evidence at every level of audit evidence: financial statement, individual account, and audit objective.

    Citation:

    Yoon, K., L. Hoogduin, and L. Zhang. 2015. Big data as complementary audit evidence. Accounting Horizons 29 (2): 431-438.

  • Jennifer M Mueller-Phillips
    Behavioral implications of big data’s impact on audit j...
    research summary posted September 11, 2015 by Jennifer M Mueller-Phillips, tagged 08.0 Auditing Procedures – Nature, Timing and Extent, 08.09 Impact of Technology on Audit Procedures, 09.0 Auditor Judgment 
    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.

  • Jennifer M Mueller-Phillips
    Examining the Potential Benefits of Internal Control...
    research summary posted March 9, 2015 by Jennifer M Mueller-Phillips, tagged 07.0 Internal Control, 08.0 Auditing Procedures – Nature, Timing and Extent, 08.09 Impact of Technology on Audit Procedures 
    Title:
    Examining the Potential Benefits of Internal Control Monitoring Technology
    Practical Implications:

    This study makes three primary contributions to the accounting and auditing communities of researchers, practitioners, and regulators. First, it is the first study to document economically significant benefits consistent with COSO’s assertions that formal ICM activities enhance the strength of internal control systems and the efficiency of external examinations of such internal control systems. Second, this study contributes to the literature in accounting information systems (AIS) by documenting specific benefits associated with strategically focused information technology. Finally, it enhances the IT-related auditing literature.

    However, there needs to be further research to examine the link between other types of ICM technology and specific outcomes. Similarly, it remains an open question as to how technology impacts other areas of internal control monitoring. COSO asserts the role of monitoring not only aids the financial reporting process, but also ultimately the organization’s overall system of governance, including operational decision-making. Though this study documents benefit-oriented assurance outcomes, the research area remains fruitful with respect to the impact of ICM technology on other audit quality measures.

    For more information on this study, please contact Adi Masli.

    Citation:

    Masli, A., G. F. Peters, V. J. Richardson, and J. M. Sanchez. 2010. Examining the Potential Benefits of Internal Control Monitoring Technology. The Accounting Review 85 (3): 1001-1034. 

  • Jennifer M Mueller-Phillips
    A Field Study on the Use of Process Mining of Event Logs as...
    research summary posted February 15, 2015 by Jennifer M Mueller-Phillips, tagged 08.0 Auditing Procedures – Nature, Timing and Extent, 08.09 Impact of Technology on Audit Procedures 
    Title:
    A Field Study on the Use of Process Mining of Event Logs as an Analytical Procedure in Auditing
    Practical Implications:

    This paper is the first to demonstrate the value added that process mining of event logs can play in auditing. Using real data drawn from the purchasing process of a global bank we show that process mining can detect information that is of relevance to internal auditors that was missed when those same auditors examined the same data using traditional analytical procedures. These results can be attributed to two distinct differences/advantages of process mining over the standard audit procedures used by the internal auditors:

    1. The richness of the event log, which contains input and meta-data as well as a comprehensive set of attributes and its systematic arrangement by time and originator.
    2. The ability to analyze the entire population instead of being forced to use only a sample.

    The creation of event logs is a complex procedure that may require the use of consultants, but it is likely that ERP vendors will make this process more automated as process mining becomes a vital tool in operational management. Several large audit firms in Europe are beginning to offer process mining as consulting tool and are experimenting with it in external audit engagements.

    For more information on this study, please contact Michael Alles.

    Citation:

    Jans, M., M. Alles and M. Vasarhelyi. 2014. A Field Study on the Use of Process Mining of Event Logs as an Analytical Procedure in Auditing. The Accounting Review. 89 (5): 1751-1773.

  • Jennifer M Mueller-Phillips
    Design and Evaluation of a Continuous Data Level Auditing...
    research summary posted February 15, 2015 by Jennifer M Mueller-Phillips, tagged 08.0 Auditing Procedures – Nature, Timing and Extent, 08.01 Substantive Analytical Review – Effectiveness, 08.08 Projecting Interim Testing Conclusions Year End, 08.09 Impact of Technology on Audit Procedures 
    Title:
    Design and Evaluation of a Continuous Data Level Auditing System
    Practical Implications:

    This paper is intended to prompt auditors to take advantage of easier access to population data in today’s digital business environment. By abandoning sampling auditors can develop much more sophisticated models of behavior that can identify anomalies in ways that were not possible before. Auditors can also be more creative in how they treat data, be it in aggregating it across organizational subunits or in larger and smaller time units. Most innovative of all, auditors and/or managers have the ability to continually update their expectation models by investigating errors and anomalies in real time and correcting them, so that the model is not based on flawed data. We find that such error correction greatly improves the accuracy of analytical procedures. Perhaps the most important finding, however, is that almost all the various expectation models we used gave similarly strong results which implies that what really matters is the size of the data set. Once auditors move away from sampling they will find that population data provides great statistical power when developing analytical procedures that reduces the reliance on finding just the right such procedure.

    For more information on this study, please contact Alexander Kogan.

    Citation:

    Kogan, A., M. Alles, M. Vasarhelyi and J. Wu. 2014. Design and Evaluation of a Continuous Data Level Auditing System. Auditing: A Journal of Practice and Theory. 33 (4): 221-245.

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