Predictive Intelligence: The Impact of Risk Modeling on Organizational Resilience
Prakash Somasundaram1, K Aishwarya Pillai2
1Prakash Somasundaram, Department of Computer Science, Northeastern University, San Francisco, California, United States of America (USA).
2K Aishwarya Pillai, Department of Computer Science, Northeastern University, San Francisco, California, United States of America (USA).
Manuscript received on 12 January 2024 | Revised Manuscript received on 16 January 2024 | Manuscript Accepted on 15 February 2024 | Manuscript published on 28 February 2024 | PP: 1-3 | Volume-13 Issue-3, February 2024 | Retrieval Number: 100.1/ijitee.C980213030224 | DOI: 10.35940/ijitee.C9802.13030224
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The importance of risk modelling in strategic planning and decision-making cannot be emphasized enough in an age where uncertainty is constant. This paper examines the crucial role of risk modelling as a vital resource for individuals and organisations seeking to understand and mitigate potential risks. The emergence of big data and technology has enabled the creation of complex risk models that provide more insights into potential hazards and enhance the effectiveness of risk management decisions. To properly measure and manage risks, this article highlights the value of risk models across various industries. Risk models are crucial for regulatory compliance, especially in sectors such as healthcare, where adherence to laws like GDPR and HIPAA is mandatory. These models provide a consistent method for evaluating risk, ensuring compliance and preventing costly fines. Additionally, the article covers how risk models enhance decision-making by reducing uncertainty and promoting transparency, which in turn fosters stakeholder trust. The paper’s main body describes a thorough approach to risk modelling, which begins with identifying potential risks and progresses to risk assessment through the use of methods like fault tree analysis (FTA) and event tree analysis (ETA). It then explains how to quantify risks using both quantitative and qualitative approaches, and concludes by summing up every potential threat to provide an overall risk profile for the company. This paper concludes by highlighting the need for risk modelling in the intricate corporate world. It offers a thorough process for creating risk models, aligning them with organisational goals, and utilising them as a preventive measure for enhancing resilience and long-term performance.
Keywords: Organizational Risk Management, Risk Modeling, Regulatory Compliance, Risk Assessment Techniques.
Scope of the Article: Simulation Optimization and Risk Management