Artificial Intelligence and Big Data Analytics in Monitoring and Preventing Corruption in Government Systems

Abstract

Artificial Intelligence tools such as machine learning algorithms, predictive analytics, and natural language processing can identify irregular patterns in financial transactions, procurement processes, and policy implementation, thereby detecting potential fraudulent activities in real time. Similarly, Big Data enables governments to collect, analyze, and interpret massive datasets from various departments to uncover hidden trends, inconsistencies, and corruption risks. By automating data analysis and ensuring evidence-based decision-making, AI and Big Data promote integrity and reduce human bias in administrative processes. The research also examines challenges such as data privacy, ethical use of technology, and the need for skilled personnel to manage these systems. Overall, the study highlights that adopting AI-driven analytics in governance can significantly strengthen anti-corruption frameworks, enhance public trust, and contribute to the development of transparent and accountable institutions. Integration of Artificial Intelligence (AI) and Big Data Analytics has emerged as a transformative approach in enhancing transparency, accountability, and efficiency within government systems. This study explores how these advanced technologies can be effectively utilized to monitor and prevent corruption in public administration.