Artificial Intelligence in Information Technology-Driven Audit and Effect on Audit Quality in Some Selected Commercial Banks in Lagos State, Nigeria

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Authors: Uchendu Joy Felix & Omorogbe Comfort E.

Abstract

Contemporary research has shown that some commercial banks struggle with inadequate technological expertise among internal auditors resulting in weak internal controls.  This study, therefore, examined artificial intelligence in information technology-driven audit and its effect on audit quality. Artificial intelligence was in the aspect of automated risk assessment (ARA), continuous monitoring and real-time data analytics (CMR). A survey research design was adopted for this study, using a multistage sampling technique in selecting Fifty (50) bank branches across the identified strata. Precisely, primary data from sixty-eight (68) IT Accounting Auditors in commercial banks in Lagos State, Nigeria, as respondents were analysed. The data were analysed using both descriptive and inferential statistics. Pearson Product-Moment Correlation (PPMC, Simple and Multiple Regression and analysis of variance were employed to test the hypotheses (p≤ 0.05). The research revealed a strong positive linear association and significance between variables studied. The extent to which the joint impact of artificial intelligence in automated risk assessment and continuous monitoring on audit quality during IT-driven audits was significant (Adj. R2 = 0.644). This indicates that Artificial Intelligence in ARA and CRM jointly explained approximately 64% of the total Variation in IT-audit quality. The study concluded that the adoption of Artificial Intelligence in IT-driven audit has become a transformative force in enhancing audit practices within commercial banks in Lagos State, Nigeria. It was recommended, among others, that commercial banks institutionalise the adoption of Artificial Intelligence tools in their audit processes by creating dedicated AI-audit integration frameworks. For instance, the management of each bank can develop internal AI-powered platforms that automatically flag unusual transactions in real time for auditors to review. Also, the management should invest in upgrading digital infrastructure, such as cloud-based systems, to ensure smooth AI operations, through the adoption of fraud detection software.

Keywords: Artificial Intelligence, IT-Driven Audit, Audit Quality, Automated Risk, Assessment, Continuous Monitoring