Abstract
The article explores the transformative role of internal audit in anti-corruption efforts, emphasizing how technological advancements, particularly data analytics and IT tools, have redefined traditional practices. Advanced data analytics enables comprehensive transaction reviews, detecting anomalies and forecasting risks. Machine learning algorithms refine corruption detection by adapting to historical data, while network analysis tools uncover hidden connections within organizations. Practical applications such as real-time transaction monitoring, behavioral analytics, and integrated risk management have bolstered anti-corruption strategies. However, the successful implementation of these technologies requires robust data governance, skilled personnel, and ethical considerations regarding data privacy. The article underscores that technology enhances, rather than replaces, the critical role of human auditors in interpreting complex insights and making ethical decisions. Looking ahead, emerging technologies like blockchain and predictive modeling promise to further advance anti-corruption mechanisms, ensuring a proactive and effective internal audit approach.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call