(untitled) (International Journal of Financial, Administrative and Economic Sciences, 2026)
This study aimed to measure the impact of artificial intelligence techniques, with their four dimensions: Genetic Algorithms, Intelligent Agents, Artificial Neural Networks, and Machine Learning, on Audit Quality in combating Financial Fraud in Sudanese commercial banks operating in Khartoum State during 2023-2024.Adopting the descriptive analytical approach, primary data were collected via a questionnaire distributed to 142 internal auditors and risk managers from 15 commercial banks. Data were analyzed using SPSS 26 through descriptive statistics, Cronbach’s Alpha, Pearson correlation, and multiple/stepwise regression. Results revealed a statistically significant impact at α ≤ 0.05 of AI dimensions combined on combating financial fraud, with R = 0.771 and R² = 0.594, explaining 59.4% of variance. Machine Learning ranked first individually with 46.7% explanatory power. The study recommends investing in human capital, ensuring data quality, building tech partnerships, and establishing AI units in banks to enhance fraud detection.