Detecting and Predicting International Financial Relations

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AI technology has proven to be an effective and efficient tool to monitor international financial relations for countries, organizations, and individuals alike. In this project, we plan to build a real-time data collection capability for data on international financial events as well as issues from news media, world organization sources, and various financial social media and user-generated content platforms. We will then use computational social science methods (combining social science theory of international financial relations and machine learning/knowledge graph algorithms) to mine the data and derive predictive models of international events/issues. This will enable us to build a knowledge graph of world financial events and provide a baseline infrastructure for international financial relations monitoring. We will then produce and commercialize an international financial relations monitoring system based on the predictive models, coupled with a constantly updated international financial relations data.

This AI-enabled and knowledge-graph supported monitoring system of international financial relations will potentially serve a variety of institutional clients, including, investment firms, consulting firms, think tanks, academic research units, financial media, NGOs, etc. The system will be commercialized in two formats: syndicated products such as daily or weekly trends reports on a subscription-fee basis, and customized services such as live-monitoring visualizers tailored made for specific clients. We will launch the products and services first in Hong Kong and gradually expand to other parts of the world.

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