AI-Assisted Risk Management and Prediction
Published: 2025
Author(s) Name: Swapna Vanguru, G. Uday Kishore and V. Bhavani |
Author(s) Affiliation: Computer Science and Engg., Keshav Memorial Engineering College, OU, Hyderabad, Telangana, India.
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Abstract
Risk management is crucial for reducing uncertainty in organisational and economic operations, but conventional approaches that depend on past performance and human knowledge are frequently insufficient. Real-time analysis of big and complicated information is made possible by artificial intelligence (AI), which brings cutting-edge methods like machine learning and predictive analytics. These features enable AI systems to identify hidden trends, forecast possible hazards, and offer early warnings for operational, financial, and cyber threats. Scenario analysis is further improved by predictive models, which enable proactive and well-informed decision-making for organisations. This increases resistance to adversities like natural catastrophes and supply chain interruptions. Smarter risk mitigation tactics are supported by AI-assisted risk management, which increases efficiency, accuracy, and adaptability.
Keywords: Artificial intelligence, Anomaly detection, Machine learning, Predictive analytics, Risk management.
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