Artificial Intelligence and Big Data Analytics in Financial and Administrative Auditing: Toward a Smart and Predictive Control System

The integration of Artificial Intelligence (AI) and Big Data Analytics into financial and administrative auditing is fundamentally transforming traditional control systems. This paper explores how these technologies enhance audit accuracy, efficiency, and transparency through the use of machine learning algorithms, anomaly detection, and predictive analytics. By enabling real-time identification of irregularities and improving risk assessment, AI reduces human error and strengthens decision-making processes. Meanwhile, Big Data allows auditors to process vast and unstructured datasets, providing more comprehensive insights into organizational performance and regulatory compliance. Based on international case studies, the study demonstrates that AI-driven auditing improves fraud detection and optimizes resource management, yet raises ethical and regulatory challenges concerning data protection and accountability. The findings emphasize that while AI and Big Data do not replace professional judgment, their integration represents a strategic evolution toward more resilient, transparent, and adaptive audit system.