Exploring Data Analytics Adoption in Auditing: Opportunities and Challenges in Malaysia’s Big 4 Firms

Aug 29, 2026

Data analytics capabilities have expanded as auditing increasingly relies on locating, understanding, and validating organizational data to support accurate decisions and professional judgments. Evidence on the efficiency and acceptance of big data analytics in auditing remains limited, motivating this qualitative study of 13 semi-structured interviews with auditors in Malaysia’s Big 4 firms. Findings highlight implementation challenges such as skills and knowledge gaps, technological barriers, and organizational resistance, alongside opportunities including improved audit quality and efficiency, professional development, and strategic insights, informing practitioners and policymakers.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages8

Reading Time20 min

AccessFree to download

Introduction

Research aim and research question

Background and literature gap

Significance of the study

Exploring Data Analytics Adoption in Auditing: Opportunities and Challenges in Malaysia’s Big 4 Firms Siti Salimah Binti Jalal1,Dahlia Fernandez2, KhairulNajmuddin bin Abd Majid3 1Faculty of Accountancy, Universiti Teknologi MARA (UiTM) Cawangan Johor, Kampus Segamat, Johor, Malaysia; [salimahjalal@uitm.edu.my](salimahjalal@uitm.edu.my) 2,3Faculty of Economic and Management, Universiti Kebangsaan Malaysia, UKM Abstract The capabilities of data analytics have expanded considerably as the auditing profession emphasizes the necessity to find, understand and validate organization data to facilitate accurate choices and judgements. The efficiency and acceptance of big data analytics in auditing in need for further evidence, hence, this study aims to explore the challenges and opportunities of adoption data analytics in Malaysia’s Big 4 audit firms. Total of 13 semi-structured interviews has been conducted using qualitative analysis with the auditors from Malaysia’s Big 4 audit firms. The participants involve in audit operational for engagements that prioritize the planning, execution, reporting, and assessment of the audit engagements. Hence, thematic analysis framework was used. Nevertheless, this study provides evidence towards challenges in implementing data analyticsand the opportunities. Thus, the findings underscore critical themes related with challenges, including skills and knowledge gaps, technological barriers and organizational resistance. In addition, the findings emphasize significant themes related with opportunities, including enhanced audit quality and efficiency, professional development, strategic insights for firms. Thus, this study has contributed substantial implications for practitioners and the literature as it advances the knowledge of data analytics in diverse settings and offer insights to policymakers and organization, particularly in accounting and audit industry. Keywords: (Data Analytics; Audit; Big 4; Challenges; Opportunities) INTRODUCTION The enormous volumes of data that are generated daily from a variety of sources has become a forefront attention of a Big Data concept. The amount of Big Data is growing at rapid rate, it is resulting on both such as benefits and issues as well (Berisha et al.,2022). Along with Big Data, the business relies on data analytics for decision making (Kumar, 2015) . The use of data analytics has become increasingly widespread because of its ability to manage different kinds of data. To perform audit procedures such as matching purchase orders e.g. invoices and payments, analysis of revenue trends by product and identifying the combinations of users involved in processing transactions from metadata attached to transactions will be carried out with the assistance of data analytics (ACCA, 2020) . Data might be deemed “big” when the information system has reached its full capacity or unable to do the particular purpose (Vasarhelyi et al., 2015) . As a result, the accounting profession, particularly auditing, is not an exception regarding the implementation of data analytics and this is because audit firms are required to manage both financial and non-financial data pertaining to their clients. Indeed, oneof the primary characteristics of data analytics is the ability to handle both structured and non- structured data in sophisticated ways, which may then be handled by auditors in accordance with the reality of prescriptive analytics (Appelbaum et al., 2017) . The use of data analytics into audit processes has resulted in a transformation of the way audits are carried out, making them more effective as well as efficient in detecting risks (KPMG, 2014) . However, this transition is not without its challenges. Adapting traditional auditing methods to integrate new technologies comes with challenges like ensuring data security, managing system complexity and aligning data analytics tools with existing audit frameworks. Although previous studies have concentrat

FAQs

What is the purpose of the study on data analytics adoption in auditing?

To explore the challenges and opportunities encountered by auditors when adopting data analytics in Malaysia’s Big 4 audit firms, providing insights for both academic understanding and professional application.

How was the study conducted?

The study used 13 semi-structured interviews with auditors from Malaysia’s Big 4 firms and applied thematic analysis to interpret the qualitative data.

What challenges and opportunities did the findings emphasize?

Challenges include skills and knowledge gaps, technological barriers, and organizational resistance; opportunities include enhanced audit quality and efficiency, professional development, and strategic insights for firms.

Aug 29, 2026

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