Audit Opinion Accuracy of Listed Manufacturing Firms in Nigeria: A Voice Data Analytics Approach

Abstract

In response to concerns about existential threat of the auditing profession that followed the emergence of artificial intelligence (AI), the current study was undertaken to investigate the potential complementary role of technology in solidifying the profession through its deployment on voice data analytics. Against this backdrop, the study investigated the impact of voice data analytics on audit opinion accuracy of listed manufacturing firms in Nigeria. A mixed method design was implemented wherein primary data were sourced from the external auditors at firm level to measure voice data analytics, while secondary data were collected from the audited annual reports of the manufacturing firms. Following analyses, it was found that voice data analytics associated positively with improvement in audit opinion accuracy. Consequently, it was conclusive that voice data analytics has the potential to contribute to audit opinion accuracy. It was therefore recommended that manufacturing firms in Nigeria should leverage on the national Voice Data Retention Policy to achieve audit opinion accuracy by integrating their voice data generating platforms with internal audit systems. Also, the Financial Reporting Council of Nigeria, as regulator, should institutionalize voice data analytics in auditing practice in Nigeria.