Literature Review |
Corresponding author: Xiaoxing Li ( x4.li@vu.nl ) Academic editor: Anna Gold
© 2022 Xiaoxing Li.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits to copy and distribute the article for non-commercial purposes, provided that the article is not altered or modified and the original author and source are credited.
Citation:
Li X (2022) Behavioral challenges to professional skepticism in auditors’ data analytics journey. Maandblad voor Accountancy en Bedrijfseconomie 96(1/2): 27-36. https://doi.org/10.5117/mab.96.78525
|
The aims of this paper are to inform audit practice and academia about the potential behavioral challenges to the application of auditors’ professional skepticism when using audit data analytics (ADA) and to discuss future research opportunities. This is accomplished by reviewing relevant audit research and discussing the potential challenges from five perspectives, including auditors’ attitudes toward ADA, data characteristics, anomalies identified by ADA, auditors’ mindsets, and social contexts and interactions involved in ADA practice. Although applying ADA brings many benefits to audit practice, they simultaneously raise many challenges to the application of appropriate levels of auditor professional skepticism. Being aware of and prepared for those potential behavioral challenges is critical to maximize the benefits of ADA to professional skepticism and ultimately audit quality.
Audit data analytics (ADA), behavioral challenges, professional skepticism
This paper is relevant for audit practice by highlighting and informing the audit profession about the potential behavioral challenges to the application of professional skepticism when using ADA. Possible mitigation methods provided by academic literature to audit practice are also discussed in this paper.
Audit firms around the globe have invested heavily into a variety of audit technologies (e.g.,
ADA are expected to facilitate more effective and efficient auditor judgment (e.g.,
Of particular interest in the current paper, ADA are expected to improve the appropriate application of auditors’ professional skepticism, ultimately improving audit quality. Auditing standards such as ISQM 1 (
Besides potential benefits, research shows that ADA may also bring challenges to the appropriate application of professional skepticism (e.g.,
First, forming an appropriate attitude about ADA is important since both under-reliance and overreliance on ADA may impede the appropriate exercise of professional skepticism (section 2). Second, auditors should be aware of how the data characteristics (e.g., data reliability and data relevance) may influence their interpretations of audit evidence obtained from ADA, potentially distorting the appropriate exercise of professional skepticism (section 3). Research further identifies that the anomalies identified by ADA may influence auditors’ application of professional skepticism (e.g., the larger number of anomalies, false positives, and false negatives) (section 4). Next, auditors need to adopt appropriate mindsets when using ADA since mindsets can influence their judgment quality (section 5). Finally, the social contexts and interactions between auditors and other stakeholders in the ADA journey may also influence the exercise of professional skepticism (section 6). I conclude the paper with a summary and discussion in section 7.
Attitude is usually defined as “an evaluative integration of cognitions and affects experienced in relation to an object” (
One example of a potentially inappropriate attitude in this regard is auditors’ exhibition of algorithm aversion in their use of ADA. Specifically, advanced ADA algorithms (e.g., artificial intelligence) employ machine learning techniques to integrate, model, and analyze large and diverse datasets, thereby assisting auditors with some challenging tasks, such as evaluating complex accounting estimates, assessing fraud risk, and estimating the financial distress related to going concern opinions (e.g.,
While under-reliance on ADA can be problematic, it is equally important for auditors to avoid overreliance on ADA (
As a result, it is critical for auditors to adopt an appropriately balanced attitude toward ADA. The auditing literature has identified some possible solutions to increase auditors’ reliance on audit technologies in general or audit evidence from ADA, such as increasing transparency of those audit technologies (
Further research could examine behavioral interventions that can be used to enhance auditors’ appropriate reliance on ADA. Specifically, future research may explore what features can be added to current ADA tools to prime auditors’ appropriate level of reliance when using those tools.
In this section, I discuss how auditors’ perceptions of the reliability and relevance of data inputs processed by ADA may influence their evaluations of audit evidence obtained from ADA and hence influence their application of professional skepticism.
The data characteristics that may influence auditors’ perceptions of data reliability discussed in this section are data sources and data structure.
Client-internal data sources, such as client transaction records, ledger accounts, and general ledgers, will probably continue to be the primary data sources for audit testing under ADA approaches. However, external data from multiple sources, such as industry data from third-party data providers or big data from social media platforms, can also be processed in ADA testing to complement current internal data (e.g.,
Encouragingly, data obtained from sources outside the client entity may be perceived as more independent and reliable, and therefore the audit evidence obtained from external data may be regarded as being of higher reliability (e.g.,
Future research could examine how auditors perceive data source reliability, given varying data sources, and how such perceived reliability influences their application of professional skepticism. In particular, further research could examine whether and how incorporating external data into analyses enhances or dampens professional skepticism.
ADA allow auditors to incorporate both structured and unstructured data. Structured data, such as financial statements, journal entries, and general ledgers, have standardized ways of presentation and interpretation, while unstructured data, such as emails, usually lack those standardizations. Some unstructured data could reveal rich information capturing nuances in personal emotions and motivations (e.g.,
However, unstructured data are inherently more ambiguous and hence open to multiple interpretations, increasing the perceived difficulty of generating plausible explanations for the fluctuations in this type of data (e.g.,
Further research is recommended to examine auditors’ preferred choices of selecting structured versus unstructured data for their analyses. Research could also provide empirical evidence on auditors’ current practice of incorporating unstructured data into ADA testing.
Besides data reliability, data relevance is another critical determinant of the appropriateness of audit evidence (
Concluding, auditors need to pay close attention to distinguishing more relevant data from less relevant data before inputting them into ADA tests. As the volume and complexity of data increase dramatically in this Big Data era, it can be difficult to clearly discriminate the data relevance level. Further research is needed to investigate whether and how auditors distinguish relevant data from irrelevant or weakly relevant data when selecting inputs to ADA. It is also recommended to explore potential interventions to mitigate the potential dilution and averaging effects on auditor judgment when using ADA.
In this section, I discuss how the anomalies identified by ADA may influence auditor skepticism. The topics discussed in the current section are the larger number of anomalies, false positives and false negatives.
As the size and complexity of datasets included in ADA testing increase, the number of anomalies identified is also likely to increase dramatically (e.g.,
Therefore, auditors will need to employ certain prioritization procedures where they exercise cognitive effort and skeptical judgment to determine which anomalies will be further investigated and the order in which they will be examined (e.g.,
False positives (i.e., type I errors) are those items or relationships identified as potential anomalies that, after further investigation, are determined to be reasonable and explained variations in the data (e.g.,
Since the presence of a larger number of false positives has become a concern in the application practice of ADA, it is critical to explore how to counter negative effects of false positives on the application of professional skepticism (e.g.,
Besides false positives, ADA may also produce false negatives (i.e., type II errors). False negatives refer to those red flags that ADA fail to identify (e.g.,
Since ADA enable the incorporation of larger and more diverse datasets, they are expected to reduce the risk of missing important information. However, the size of the datasets is not necessarily positively related to data completeness or quality, and therefore it is still possible that some relevant data fail to be included into ADA for audit testing. Hence, false negatives still emerge in ADA testing even though larger datasets have been incorporated.
Importantly, ADA’s capability of incorporating larger and more diverse datasets may create an illusion that the output is free of missed information. Psychological research indeed finds that the amount of information more saliently enhances decision makers’ confidence in their judgment than the accuracy of their judgment (
Further research on auditors’ response to false negatives of ADA could examine whether and how the incorporation of larger datasets into ADA changes auditors’ expectation on the false negative rates. It is important to learn more about auditors’ awareness of the false negative rates of ADA and to explore what potential interventions can be taken to maintain auditor skepticism, especially their sensitivity to new information when perceiving lower false negative rates of ADA testing.
A mindset refers to “a set of judgmental criteria and cognitive processes and procedures that produce a disposition or readiness to respond in a certain manner” (
Mindsets potentially influence auditors’ ADA adoption decisions.
In addition to ADA adoption decisions, future research could examine how mindsets influence auditors’ assessment and evaluation of contradictory evidence from ADA.
Future research could more examine whether the implications from prior literature can be generalized to ADA practice. Particularly, future research should explore whether there are certain types of mindsets specifically related to ADA so that auditors can employ to improve professional skepticism when using ADA.
In this section, I discuss how the contextual environment around auditors and their interactions with key stakeholders in the ADA journey potentially influence their judgment quality and motivation for skeptical behavior when using ADA. The potential factors discussed in the current section include tone at the top, the work of data specialists, the audit committee’s attitude, sophistication of the client’s information technology (IT) systems, and regulations.
Supervisors can play a significant role in auditors’ ADA journey (e.g.,
Future research could examine what is the appropriate leadership or tone at the top (e.g., transformational, transactional, delegative, participative, or authoritarian) to encourage auditor professional skepticism when using ADA. Research could also investigate whether and how the methods of expressing (e.g., explicitly vs. implicitly) the tone at the top would influence auditors’ skepticism in ADA practice.
Since auditors usually lack the expertise to fully interact with emerging technologies (e.g.,
Further research could provide empirical findings about auditors’ coordination and communication with data specialists in their ADA practice. Research could also examine how different forms of data specialists’ help (e.g., providing systematic training vs. helping on request, centralized vs. decentralized) influence the effectiveness of using ADA and professional skepticism.
An audit committee’s attitude can also influence auditors’ ADA practice (
Further research may examine what characteristics of the audit committee (e.g., expertise) would influence auditors’ ADA practice. Research could provide evidence on what support the audit committees could provide to auditors for applying ADA in their audit engagement. Research could further examine how auditors respond when management and the audit committee have contradictory attitudes and expectations on the ADA practice.
The sophistication of the client’s IT systems largely influences auditors’ ADA adoption decision and perhaps their judgment quality when using ADA. When the client has more sophisticated IT systems, auditors are more likely to use ADA in their audit testing (e.g.,
Further research could examine whether auditors exercise an inappropriate level of reliance on information provided by the client when there are more advanced IT systems in the client entity and, if so, what are the possible interventions to reduce this potential overreliance.
Regulators’ attitude toward ADA can be especially important to auditors (e.g.,
Future research could examine how the characteristics of standards could influence auditors’ adoption decisions and auditing practice when using ADA, and what are the potential unintended consequences of proposed ADA standards to auditors’ judgment and application of professional skepticism.
Many stakeholders believe that the time has come for auditors to embrace technology (e.g.,
Future research linking ADA and auditors’ application of professional skepticism from those five perspectives has been recommended in this paper. For example, further research could examine potential behavioral interventions to prime auditors’ appropriate reliance on ADA. Future research is also recommended to investigate the potential effects of data characteristics on auditors’ assessment of evidence obtained from ADA. Researchers could continue to explore measures to mitigate the potential negative influences of ADA (e.g., the large number of anomalies and false positives) on auditors’ application of professional skepticism. Future research aiming to investigate appropriate mindsets that auditors should adopt when using ADA is also encouraged. Finally, research can explore social, contextual and environmental factors that motivate auditors’ better ADA practice and application of professional skepticism.
Overall, this paper informs academia, the audit profession, standard-setters, and regulators about the potential challenges to the appropriate application of professional skepticism when using ADA so that stakeholders can be alert to and prepared for those potential issues. Concluding, multiple efforts are needed to solve those challenges in auditors’ ADA journey and motivate the appropriate application of professional skepticism.
Xiaoxing Li MSc is a PhD candidate at the Department of Accounting, School of Business and Economics, Vrije Universiteit Amsterdam. She is currently working on her PhD dissertation in the area of audit data analytics and professional skepticism.
The author thanks the Foundation for Auditing Research for providing financial support through their research grant 2021B01. The views expressed in this document are those of the author and not necessarily those of the FAR. The author also thanks the editor, Anna Gold, and two anonymous reviewers for their comments and feedback.