Auditor Judgements after Withdrawal of the Materiality Accounting Standard in Australia

David, Raul; Abeysekera, Indra

doi:10.3390/jrfm14060268

Cited by 7 publications

(7 citation statements)

References 43 publications

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“…In particular, the study results by Sharma et al (2016) found that fraud detection from unstructured data is a way to reduce fraud to a certain level. Furthermore, David and Abeysekera (2021) and Yang et al (2018) found that the greater the number and variety of unstructured data types, the more the audit risk and audit costs would be. Thus, we consider that unstructured data types cause higher audit risks and costs than structured data types.…”

Section: Big Data Analytics and Auditor Judgmentmentioning

confidence: 99%

“…The use of data analytics can assist auditors in reducing cognitive errors caused by the large and varied number of data (Ahmad, 2019). Previous studies examined the effect of data analytics on auditor judgment and found that data analytics can improve auditor judgment (Brown-Liburd et al , 2015; Kend and Nguyen, 2020; David and Abeysekera, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Big data analytics and auditor judgment: an experimental study

Sihombing

Narsa

Harymawan

2023

ARJ

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Purpose Auditors’ skills and knowledge of data analytics and big data can influence their judgment at the audit planning stage. At this stage, the auditor will determine the level of audit risk and estimate how long the audit will take. This study aims to test whether big data and data analytics affect auditors’ judgment by adopting the cognitive fit theory. Design/methodology/approach This was an experimental study involving 109 accounting students as participants. The 2 × 2 factorial design between subjects in a laboratory setting was applied to test the hypothesis. Findings First, this study supports the proposed hypothesis that participants who are provided with visual analytics information will rate audit risk lower than text analytics. Second, participants who receive information on unstructured data types will assess audit risk (audit hours) higher (longer) than those receiving structured data types. In addition, those who receive information from visual analytics results have a higher level of reliance than those receiving text analytics. Practical implications This research has implications for external and internal auditors to improve their skills and knowledge of data analytics and big data to make better judgments, especially when the auditor is planning the audit. Originality/value Previous studies have examined the effect of data analytics (predictive vs anomaly) and big data (financial vs non-financial) on auditor judgment, whereas this study examined data analytics (visual vs text analytics) and big data (structured and unstructured), which were not tested in previous studies.

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Section: Big Data Analytics and Auditor Judgmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Big data analytics and auditor judgment: an experimental study

Sihombing

Narsa

Harymawan

2023

ARJ

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“…First, firms should avoid reporting cluttered information by only reporting information that matters, which is of significance. Materiality is a construct arising from three interactions -firm, auditor and ethics (David and Abeysekera, 2011). This paper provides a revised version of the materiality description in the SDG Compass (2015, p. 27) as "issues that reflect firm's significant outcomes and impacts on UN SDGs that substantively influence the assessments and decisions of stakeholders".…”

Section: Section 3 Of the Corporate Report: Sustainability Reportingmentioning

confidence: 99%

“…The reduction in water and air pollution is attributed to more significant benefits than costs incurred, whereas firms have not decreased greenhouse gas emissions because costs were more than benefits accrued to them (Shapiro, 2022). Chouinard et al (2011) point out that absorbing otherwise externalised costs into the cost of production makes firms less competitive. These trends point out that the financial implications to firms in adopting sustainability practices are core to their decision-making.…”

Section: Introductionmentioning

confidence: 99%

A framework for sustainability reporting

Abeysekera

2022

SAMPJ

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Purpose A sustainability reporting framework must demonstrate that resources are fairly bought and used to support diverse life on earth within habitable ranges. The purpose of this paper is to propose a principle-based sustainability reporting framework that measures, audits and reports based on sustainability outcomes and impacts as part of the corporate reporting framework. Design/methodology/approach This paper draws on the United Nations Sustainable Development Goals (UN SDGs) and targets for preparing a reporting framework. It uses Gaia Theory and the Theory of Distributive Justice constructs that align with sustainable development principles to delineate a reporting approach. Findings Frameworks that promote sustainability reporting have increasingly embraced UN SDGs but overly focus on performance promoting inter-firm comparisons. This framework introduces principle-based sustainability reporting where firms demonstrate their chosen contribution to sustainable development using 17 UN SDGs as goal posts. Research limitations/implications This conceptual paper presents theoretical constructs that future research can empirically validate to enhance sustainability reporting. Practical implications This principle-based sustainability reporting framework is implementable for corporate reporting, where sustainability reporting integrates with the financial and economic intellectual capital reporting frameworks. Social implications This framework highlights the importance of acquiring and using resources to distribute justice and fairness. It is a joint project between firms and stakeholders. Originality/value This framework promotes integrated thinking for firms to engage in principle-based sustainability reporting and provides a roadmap for sustainability reporting using the SDG Compass logic model.

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“…al., 2019;Acito et. al., 2019;David and Abeysekera, 2021;Altiero et. al., 2021), therefore the professional audit literature could be used as a primary source of information for identifying qualitative characteristics.…”

Section: Primary Qualitative Characteristics Among Infi Nite Number O...mentioning

confidence: 99%

Application of Qualitative Characteristics to Evaluate Misstatements in Financial Statements: Evidence from Factual Audit Data

Masiulevičius

Lakis

2022

ECO

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The auditor should use qualitative characteristics, which describe the essence of misstatement, while assessing identified misstatements. Final decision depends on the professional judgment made by the auditor, however, auditors may make erroneous decisions or be biased. Previous theoretical research highlighted problems with the application of qualitative characteristics. However, factual audit data is confidential and usually not available for researchers to examine, therefore previous research mostly relied on surveys or experiments and there is little evidence on how auditors behave during real audits (rather than simulations). One audit company agreed to provide us with factual data for this research. The aim of the research is to examine the application of primary qualitative characteristics based on factual audit data. During the research, the audits performed in one Lithuanian audit company for the financial years 2019–2020 were examined as well as summarized official (publicly available) data about audit companies in Lithuania and audits performed by them for 2018–2020 financial years were examined. Firstly, most important primary qualitative characteristics, as well as secondary commonly used characteristics, were singled out. Our further investigation, based on received 2019–2020 factual audit data revealed that some auditors still do not apply primary qualitative characteristics in all cases. Even though we investigated one company and we cannot directly extrapolate results for the whole audit market, but our results are in line with the official and publicly available information about audit companies in Lithuania. Thus, we conclude that our results partly reflect truthful view of factual behavior of audit companies in Lithuania. These results also confirm theoretical research that qualitative characteristics are not sufficiently appreciated.

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Auditor Judgements after Withdrawal of the Materiality Accounting Standard in Australia

Cited by 7 publications

References 43 publications

Big data analytics and auditor judgment: an experimental study

Big data analytics and auditor judgment: an experimental study

A framework for sustainability reporting

Application of Qualitative Characteristics to Evaluate Misstatements in Financial Statements: Evidence from Factual Audit Data

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