Big Data and Business Intelligence
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The study argues that organizations capable of embedding predictive analytics into strategic governance structures will achieve stronger resilience, improved decision quality, and more sustainable competitive positioning in increasingly uncertain markets.
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Risk management is undergoing a fundamental transformation as organizations confront increasingly complex, interconnected, and rapidly evolving business environments. Traditional risk governance approaches, which often rely on historical reporting and reactive decision-making, are becoming insufficient for addressing emerging uncertainties. Advances in predictive analytics, artificial intelligence, machine learning, and real-time data processing have created opportunities for organizations to move beyond retrospective risk assessment and adopt forward-looking governance models. This article explores strategic risk governance as a framework for integrating predictive analytics into executive decision-making processes. Particular attention is given to risk intelligence, predictive capability development, data-driven governance systems, executive decision architectures, organizational resilience, ethical considerations, and future risk management paradigms. The study argues that organizations capable of embedding predictive analytics into strategic governance structures will achieve stronger resilience, improved decision quality, and more sustainable competitive positioning in increasingly uncertain markets.
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@article{GNDZ2026Strategic,
title = {Strategic Risk Governance: Integrating Predictive Analytics into Executive Decision Frameworks},
author = {Neslihan GÜNDÜZ},
journal = {International Journal of Research Publications},
year = {2026},
doi = {10.47119/ijrp1001991620269490},
url = {https://doi.org/10.47119/ijrp1001991620269490}
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