فهرست نشریات علمی دسترسی آزاد ایران

This study rigorously examines the influence of artificial intelligence (AI) algorithms on the detection and prevention of financial fraud, with a particular emphasis on the moderating role of internal control systems. Utilizing a quantitative, applied research design with a descriptive-survey approach, data were collected from 150 professionals across the domains of finance, auditing, information technology, and risk management through validated questionnaires administered via both online and offline channels.The research evaluates the efficacy of advanced AI techniques—including machine learning models, natural language processing (NLP), graph-based analytics, and real-time detection systems—in identifying intricate, non-obvious, and evolving fraudulent financial behaviors. The findings reveal that the integration of AI technologies significantly enhances fraud detection accuracy and responsiveness. Crucially, this positive impact is markedly amplified in organizational environments characterized by robust, well-structured internal control mechanisms.The results underscore the synergistic interplay between technological innovation and governance infrastructure, indicating that effective internal controls serve as a critical enabler in maximizing the potential of AI for financial fraud risk mitigation. This study contributes a novel empirical and conceptual framework that informs both academic inquiry and managerial practice, offering strategic insights for organizations aiming to enhance the resilience and intelligence of their financial oversight systems.