<![CDATA[Purpose: This study explores risk measurement and management advancements to inform strategic financing decisions. It highlights the importance of innovative methodologies in enhancing organizational resilience and optimizing resource allocation amidst evolving financial landscapes. Research Design and Methodology: The research employs a robust and comprehensive quantitative descriptive approach, incorporating a systematic literature review and thematic coding techniques to analyze existing scholarly works. This methodology ensures a thorough and reliable examination of prevalent risk factors, existing models' efficacy, and technological solutions' integration in risk management. The findings are therefore grounded in a solid foundation of academic research and analysis. Findings and Discussion: The findings reveal that advanced quantitative models have significantly improved financial risk assessment accuracy, such as Value at Risk (VaR) and Conditional Value at Risk (CVaR). Behavioral finance insights emphasize the impact of cognitive biases on risk perception and decision-making. Technological innovations like artificial intelligence (AI) and blockchain have revolutionized risk management practices by offering real-time data analysis and enhanced transparency. Integrating environmental, social, and governance (ESG) factors into risk frameworks is crucial for aligning organizational strategies with sustainability imperatives. Implications: The research underscores the practical implications for organizations, highlighting the need to adopt a multi-dimensional approach to risk management. This approach combines quantitative models, behavioral insights, and advanced analytics, enabling better anticipation and mitigation of risks. This strategy empowers organizations to make informed strategic financing decisions by fostering organizational resilience and sustainable growth. Future research should focus on longitudinal studies, interdisciplinary collaboration, and the impact of emerging technologies and ESG factors on risk management practices.]]>
