THE EFFECT OF ARTIFICIAL INTELLIGENCE ON THE AUDITING OF FINANCIAL STATEMENTS IN LISTED DEPOSIT MONEY BANKS IN NIGERIA.

This study investigates the effect of Artificial Intelligence (AI) application on the audit of financial statements of listed Deposit Money Banks (DMBs) in Nigeria. Rapid technological advancements and the rising complexity of banking operations have exposed limitations in traditional, sample-based auditing methods. Using a structured questionnaire survey administered across six purposively selected Nigerian banks (Access Bank, Zenith Bank, UBA, First Bank, GTBank, and Sterling Bank), primary data was collected from 134 audit and IT professionals. Hypotheses were tested using the Pearson Product-Moment Correlation Coefficient (PPMC). The findings revealed statistically significant, very strong positive relationships between AI application and all four performance dimensions: Audit Cycle Time ($r = 0.882$), Audit Accuracy ($r = 0.890$), Audit Quality ($r = 0.894$), and Audit Effectiveness ($r = 0.894$) (all $p < 0.001$). The study concludes that AI adoption radically minimizes human error, compresses turnaround times, and enhances fraud detection capabilities. It recommends continuous investment in AI-competent workforce development and the establishing of robust data privacy frameworks.