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Illegal wildlife trade on a global scale poses a serious threat to ecosystems and the environment, as well as risk challenges in the areas of finance and insurance. This study proposes a data-driven project based on a comprehensive understanding of trends in illegal trade and effective measures to reduce its scale. Through in-depth analysis of historical data, implementation of a continuous monitoring and tracking system, and collection of relevant data for continuous assessment, we are able to more accurately identify illegal trade behavior. Using data analysis techniques, such as time series analysis and GIS analysis, we will create visualization reports to provide a scientific basis for relevant decision makers. This study also selected the most suitable partner to facilitate the successful implementation of the project through a tiered analysis process. Ultimately, we identified an authoritative, well-resourced target client with a deep interest in ecological conservation, providing a solution to the challenges of illegal trade in the financial and insurance sectors.
Hong et al. (Thu,) studied this question.