Big Data Analytics and Auditing Effectiveness of Selected Audit Firms in Nigeria

Abstract

This study examined the effect of Big Data Analytics (BDA) on the audit effectiveness of selected audit firms in Nigeria between 2015 and 2024. Specifically, the study assessed the effects of Big Data Volume, Big Data Variety, Big Data Processing Speed, on the audit effectiveness of audit firms in Nigeria. The study adopted an ex-post facto research design, using secondary data obtained from eleven (11) audit firms that consistently audited companies listed on the Nigerian Exchange Group (NGX) within the study period. The data were analyzed using Panel Least Squares Regression (fixed and random effects), supported by descriptive statistics, correlation analysis and the Hausman specification test to select the appropriate model. The regression results revealed that Big Data Volume (β = 0.085, p = 0.000) had statistically significant positive effects on audit effectiveness. Big Data Variety (β = 0.100, p = 0.071) showed positive but statistically insignificant effects on audit effectiveness. Conversely, Big Data Processing Speed (β = –0.065, p = 0.006) had a statistically significant negative effect on audit effectiveness. The study concluded that Big Data Analytics significantly affects audit effectiveness among Nigerian audit firms, with data volume emerging as the strongest determinants of fraud detection and audit reliability. However, the benefits of BDA are moderated by data quality, auditor competence, and technological capacity. The study recommended that audit firms invest in scalable data infrastructure, diversify data sources, and strengthen accuracy controls while balancing analytical speed with validation. Professional bodies such as ICAN and ANAN should promote continuous auditor training in data analytics to improve audit quality. The study contributed to existing knowledge by empirically analyzing the three core dimensions of Big Data Analytics and their distinct effects on audit effectiveness which is an approach that extends prior literature on technology-driven auditing within the Nigerian context.