Auditor judgment and decision-making in big data environment: a proposed research framework

Abstract

Purpose The role of big data and data analytics in the audit engagement process is evident. Notwithstanding, understanding how big data influences cognitive processes and, consequently, on the auditors’ judgment decision-making process is limited. The purpose of this paper is to present a conceptual framework on the cognitive process that may influence auditors’ judgment decision-making in the big data environment. The proposed framework predicts the relationships among data visualization integration, data processing modes, task complexity and auditors’ judgment decision-making. Design/methodology/approach The methodology to accomplish the conceptual framework is based on a thorough literature review that consists of theoretical discussions and comparative studies of other authors’ works and thinking. It also involves summarizing and interpreting previous contributions subjectively and narratively and extending the work in some fashion. Based on this approach, this paper formulates four propositions about data visualization integration, data processing modes, task complexity and auditors’ judgment decision-making. The proposed framework was built from cognitive theory addressing how auditors process data into useful information to make judgment decision-making. Findings The proposed framework expects that the cognitive process of data visualization integration and intuitive data processing mode will improve auditors’ judgment decision-making. This paper also contends that task complexity may influence the cognitive process of data visualization integration and processing modes because of the voluminous nature of data and the complexity of business processes. Hence, it is also expected that the relationships between data visualization integration and audit judgment decision-making and between processing mode and audit judgment decision-making will be moderated by task complexity. Research limitations/implications There is a dearth of studies examining how big data and big data analytics affect auditors’ cognitive processes in making decisions. This paper will help researchers and auditors understand the behavioral consequences of data visualization integration and data processing mode in making judgment decision-making, given a certain level of task complexity. Originality/value With the advent of big data and the evolution of innovative audit procedures, the constructed framework can be used as a theoretical foundation for future empirical studies concerning auditors’ judgment decision-making. It highlights the potential of big data to transform the nature and practice of accounting and auditing.

A Review of Big Data Research in Accounting

“…The literature discusses audit issues entailing audit procedures (Fay & Negangard, 2017; No et al, 2019), audit judgment (Brown‐Liburd et al, 2015; Hamdam et al, 2022; Rose et al, 2017), continuous auditing (Zhang et al, 2015), financial statement audit (Cao et al, 2015; Earley, 2015), forensic auditing (Rezaee & Wang, 2019), and internal auditing (Li et al, 2018; Rakipi et al, 2021; Tang et al, 2017). These procedures are discussed below.…”

“…Apart from audit procedures, other studies discuss the impact of big data on auditor judgment. Notably, Hamdam et al (2022) investigated the cognitive processes that may affect auditors’ judgment in a big data environment. The study’s finding was that data visualization and intuitive data processing have the greatest potential to improve auditor judgment.…”

“…The study’s finding was that data visualization and intuitive data processing have the greatest potential to improve auditor judgment. Hamdam et al (2022) proposed a framework to explain how cognitive data visualization and intuitive data processing can enhance the quality of auditor judgment. Accordingly, Brown‐Liburd et al (2015) examined big data’s behavioral implications on auditor judgment.…”

The effects of person‐specific, task, and environmental factors on digital transformation and innovation in auditing: A review of the literature

“…This study focuses on data visualization and population testing. Hamdam et al (2021) reviewed prior literature to develop a conceptual framework to model the cognitive process that could influence auditors' decisions in a big data environment. The framework considers the intersections of descriptive‐analytic tools like data visualization, data processing modes, the complexity of the underlying audit task and auditors' judgment and decision‐making.…”

“…As previously mentioned, practicing auditors also use population testing as a dual‐purpose test of not only what happened but also why. Hamdam et al (2021) developed a conceptual framework that suggests task complexity moderates the effectiveness of technology use in the audit. This relation is particularly germane to diagnostic analytics because testing the full population rather than a sample could increase the complexity of the diagnostic task when voluminous anomalies could be identified.…”