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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.

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.

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.

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.

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.

This paper aims to recommend a framework that serves as a practical work tool for conducting risk-based Shari’ah audit (RBSA) in Islamic financial institutions (IFIs).

Qualitative research method was used through critical in-depth content analysis of documented literature to generate deep insights, further supported with a hypothetical illustrative case study application of the framework on an Islamic bank, aimed at bringing the framework to a practical, near real-life scenario.

A robust RBSA framework has been developed which focuses on Shari’ah non-compliance risks to systematically and practically arrive at a rated opinion on the level of an IFI’s adherence with Shari’ah rules and principles as recommended by the Accounting and Auditing Organization for Islamic Financial Institutions, aimed to safeguard the IFI and promote financial system stability at large.

Practical realities limited the study to the use of a hypothetical case study bank. Future researchers can apply the framework to a real case study of diverse IFIs for effective contextual recalibration in diverse jurisdictions.

This paper aids the development of both internal and external Shari’ah audit practice using the risk-based approach.

The RBSA framework contributes to promoting public trust and confidence in the Islamic finance industry.

This paper has proposed this RBSA framework as a practical work tool for Shari’ah auditors in their engagements and regulators in promoting sound governance and financial system stability. It provides foundation for future researchers in the field.