The Role of Big Data in Audit: Implications for Improving Audit Quality and Fraud Detection Effectiveness for External Auditors

Abstract

The digital transformation in auditing drives the utilization of big data as a novel approach to enhance the efficiency and effectiveness of the audit process. Big data enables auditors to process large volumes of information in real-time and analyze complex transaction patterns, which potentially improves audit quality and fraud detection capabilities. This study aims to evaluate the impact of big data on audit quality and the effectiveness of fraud detection by external auditors in Indonesia. Using a quantitative approach, data were collected through structured questionnaires distributed to 50 external auditors with a minimum of three years of experience, employing purposive sampling technique. Data were analyzed using multiple linear regression. The findings indicate that the implementation of big data significantly contributes to the improvement of audit quality and efficiency in identifying fraud. Auditors leveraging big data can detect anomalies more accurately and rapidly. The study recommends strengthening information technology competencies among auditors and developing audit systems based on data analytics. Future research should explore moderating variables such as industry complexity.