This study investigated the impact of artificial intelligence (AI), external audit quality on
financial accountability of Deposit Money Banks (DMBs) in Lagos State, Nigeria. More
specifically, this study examined the elements of the level of AI, effectiveness of AI in fraud
detection, reliability and accuracy of the audit, as well as timeliness and efficiency of the
audit, and the impact of these elements on financial accountability. Guided by Agency
Theory, the study employed a survey research design. External auditors and audit specialists
working in the four largest international audit firms (PwC, KPMG, EY and Deloitte) in Lagos
were surveyed, and 912 usable responses were collected. Data were analyzed using
descriptive statistics, reliability analysis using Cronbach’s alpha, and simple and multiple
regression analyses. The outcomes of the study revealed that the four model’s independent
variables had a positive and significant influence on financial accountability with a
confidence level of 95%. The level of AI adoption (β = 0.591, R² = 0.541), effectiveness of AI
in fraud detection (β = 0.624, R² = 0.573), reliability and accuracy of the audit (β = 0.573,
R² = 0.502), and timeliness and efficiency of the audit (β = 0.558, R² = 0.487). The combined
model was significantly high (R² = 0.714, F = 558.46, p < 0.05) and accounted for 71.4% of
the variance in financial accountability in which the effectiveness of AI in fraud detection was
the strongest of the four variables. The study found that the use of AI in external auditing
strengthened financial accountability in Nigerian Deposit Money Banks (DMBs). It suggested
the banks should allocate more resources toward the development of AI-based fraud
detection systems and real-time auditing. It is recommended that the Central Bank of Nigeria
(CBN) establishes a policy framework that balances the need to enhance the accountability of
banks and the development of responsible AI in auditing.