Advanced Applications of Predictive Analytics and Machine Learning in Enhancing IT Audit Accuracy and Anomaly Detection
Keywords:
Predictive analytics, machine learning, IT audit, anomaly detection, audit accuracy, predictive modelingAbstract
The integration of predictive analytics and machine learning (ML) in IT auditing has significantly advanced anomaly detection and decision-making accuracy. These technologies enable auditors to process large-scale data, identify subtle patterns, and predict risks proactively, resulting in enhanced audit effectiveness. This paper reviews current methodologies, tools, and applications in IT audits, emphasizing predictive models and anomaly detection mechanisms. A literature review identifies key findings from prior research, highlighting the potential for ML-driven systems to streamline IT audits and improve governance. We also present a case analysis illustrating the practical benefits of adopting these advanced technologies.
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