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Abstract

Purpose: This study explores adaptive financial risk management strategies within the context of global economic uncertainty and market volatility. It focuses on how companies can enhance financial resilience by integrating technology and adopting flexible approaches to manage traditional and emerging risks.


Research Method: The study employs a systematic literature review (SLR) methodology, examining recent studies and foundational theories. This approach allows for the identification of effective adaptive strategies and the role of advanced technologies, including AI, big data analytics, and blockchain, in strengthening financial risk management.


Results and Discussion: The findings reveal that adaptive, technology-driven strategies significantly improve companies' responsiveness to market shifts and volatility. Tailored risk management approaches—specific to sectors and regions—are most effective in addressing conventional and emerging risks. Additionally, the study underscores the importance of a skilled workforce in operating modern risk management tools and highlights the value of flexible, data-driven frameworks.


Implications: The study suggests that companies integrate technology into risk management practices, invest in workforce training, and develop strategies tailored to their industry and geographic context. These insights provide practical guidance for companies seeking to enhance financial stability and resilience. Future research should expand on these findings by exploring adaptive practices across diverse sectors and regions to offer further insights.

Keywords

financial risk management adaptive strategies economic uncertainty technology integration corporate resilience

Article Details

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How to Cite
Randy, M. F., Sari M, F. I., Fadil, A. ., Wahab, W. A., & Herianto R, ⁠A H. (2026). Financial Risk Management Analysis in the Face of Market Uncertainty and Global Economic Instability. Advances in Management & Financial Reporting, 4(2), 320–335. https://doi.org/10.60079/amfr.v4i2.757
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