Nature-related keyword frequency distribution in China’s sustainable finance FIGURE 11 Pure ESG-themed funds China policy10% 20% 30% 40% 50% 60% 70% 80% 90% 100%Invasive alien species introduction/removal Resource use/replenishment Land/freshwater/ocean use change Pollution/pollution removal Climate change7% 8% 5% 11% 5% 8% 12% 16% 63% 63% 0% Emerging technologies, such as satellite remote sensing, AI, internet of things (IoT)-based data collection systems and blockchain, are poised to play a transformative role in addressing data-related bottlenecks in nature finance. These technologies provide accurate, real-time and scalable data, enhancing the quality and credibility of information used for risk assessment. AI, in particular, significantly reduces the cost of data collection and processing, making high-quality biodiversity data more affordable. By enriching available data and ensuring transparency, these technologies help to provide nature-related qualitative reference, paving the way for more informed and effective investment decisions.Leveraging emerging technologies to overcome data limitations 2 The Institute of Public and Environmental Affairs (IPE) in China has been working to integrate fragmented environmental data – such as on ecological protection zones, biodiversity reserves, water and soil conditions, pollutant emissions, land use and related regulations – into a unified platform.36 Using spatial data integration technologies and AI, IPE presents a visualized dataset that enables financial institutions to understand the natural environment around a project. This empowers them to assess both physical and transition risks associated with nature. IPE’s ecosystem data and risk models are now integrated with financial institutions such as the Postal Savings Bank of China37 and WeBank.38Data integration and technological innovation: Filling data gaps and breaking down data silosSource: IIGF analysis. 18

Nature Related Sustainable Finance in China 2025