Utilizing big data analytics in the selection and testing of journal entries and its impact on professional skepticism

Abstract This study investigates the influence of Big Data Analytics (BDA) on the journal entries (JEs) testing performed by auditors and its subsequent impact on their professional skepticism (PS). The study employed semi-structured interviews with 9 auditors at the manager level or above, working at Big 4 auditing firms. The thematic analysis was employed to examine the interview transcripts, Given the small and qualitative nature of the sample, the study offers in-depth, interpretive insights rather than generalized conclusions. The findings revealed that BDA assists auditors in effectively testing JEs by enhancing risk identification and maintaining an appropriate level of PS. In this study, several factors were identified that positively impact skepticism when using BDA in JEs testing, including proper training, teamwork and communication, regular meetings among audit teams, and executive involvement. But relying too much on BDA output can be risky; auditors should question results instead of blindly accepting them. The study also stresses the need for updated auditing standards to address using BDA in JEs testing and implication on PS. Regulatory bodies and internal reviewers are also important in maintaining high skepticism levels between auditors. This study contributes valuable empirical evidence to the existing literature on the impact of BDA in audit procedures, specifically in the selection and testing of JEs, and highlights the importance of utilizing advanced technique such as BDA in maintaining PS. JEL Classification: 1. M42 Auditing.