АВТОМАТИЗОВАНІ СИСТЕМИ РИЗИК-МЕНЕДЖМЕНТУ В МІЖНАРОДНІЙ ЕКОНОМІЦІ ТА ГЛОБАЛЬНИХ ІНВЕСТИЦІЯХ

The article explores the growing significance of automated risk management systems (ARMS) in the context of the global investment ecosystem, especially amid rising financial volatility, geopolitical tensions, and the increasing complexity of capital flows. The relevance of this study is determined by the growing dependence of institutional investors and global financial markets on the speed, adaptability, and analytical precision of automated systems. The work identifies key structural elements of ARMS, including data aggregation, predictive analytics, decision-making algorithms, and real-time dashboards, which collectively allow for dynamic and informed risk mitigation in rapidly changing environments. Particular attention is paid to the integration of machine learning and artificial intelligence, which provide ARMS with self-learning capabilities and the ability to detect non-linear market patterns and black swan events. The study analyzes practical implementations in leading financial institutions, such as BlackRock’s Aladdin and JPMorgan’s AI models, showing how automation reshapes risk forecasting and capital allocation. It is emphasized that the transition from traditional models, such as Value at Risk and scenario analysis, to algorithmic frameworks not only increases operational efficiency but also introduces a new set of regulatory, ethical, and systemic challenges. These include algorithmic opacity, technological inequality between developed and emerging markets, and the need for international standards in data governance and model accountability.  Through the comparative analysis of traditional and automated models, the article highlights the advantages of ARMS in terms of speed, accuracy, and scalability, while also recognizing the importance of human oversight in ensuring responsible decision-making. It is concluded that the effective development and implementation of automated risk management strategies require a multidisciplinary approach, combining technological innovation with financial regulation, ethical guidelines, and cross-border cooperation. The findings support the notion that ARMS are not only tools of efficiency but essential components of financial sustainability and resilience in an increasingly algorithm-driven world.