<![CDATA[Background. The digital age has introduced both unprecedented opportunities and risks in financial management, as technological advancements have reshaped the landscape of financial operations. With the rapid growth of digital transactions, cybersecurity threats, and volatile markets, managing financial risk has become more complex for organizations. Purpose. This study aims to explore innovative strategies for managing financial risk in the digital era, focusing on technology-driven solutions that enhance risk assessment, mitigation, and resilience. The research investigates how digital tools such as artificial intelligence, machine learning, and blockchain can be leveraged to predict, monitor, and minimize financial risks effectively. Method. A mixed-method approach was employed, combining quantitative analysis of financial risk data with qualitative insights from industry experts. Machine learning algorithms were applied to historical financial data to identify risk patterns, while interviews with financial managers provided insights into practical risk management challenges and solutions. Results. Results indicate that AI-based predictive analytics significantly improve risk detection accuracy by up to 85%, and blockchain technology enhances transaction transparency, reducing fraud risks. These findings suggest that integrating advanced digital tools can lead to a more resilient and proactive financial risk management framework. Conclusion. The study concludes that adopting technology-driven strategies is essential for effective financial risk management in the digital age. By implementing AI, machine learning, and blockchain, organizations can gain real-time insights and foster a proactive approach to risk. These strategies not only reduce exposure to potential threats but also enhance decision-making processes, contributing to long-term financial stability.]]>
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