There is growing recognition among financial institutions, financial regulators and policy makers of the importance of addressing nature-related risks and opportunities. Evaluating and assessing nature-related risks for financial institutions is challenging due to the large volume of heterogeneous data available on nature and the complexity of investment value chains and the various components' relationship to nature. The dual problem of scaling data analytics and analysing complex systems can be addressed using Artificial Intelligence (AI). We address issues such as plugging existing data gaps with discovered data, data estimation under uncertainty, time series analysis and (near) real-time updates. This report presents potential AI solutions for models of two distinct use cases, the Brazil Beef Supply Use Case and the Water Utility Use Case. Our two use cases cover a broad perspective within sustainable finance. The Brazilian cattle farming use case is an example of greening finance - integrating nature-related considerations into mainstream financial decision-making to transition investments away from sectors with poor historical track records and unsustainable operations. The deployment of nature-based solutions in the UK water utility use case is an example of financing green - driving investment to nature-positive outcomes. The two use cases also cover different sectors, geographies, financial assets and AI modelling techniques, providing an overview on how AI could be applied to different challenges relating to nature's integration into finance. This report is primarily aimed at financial institutions but is also of interest to ESG data providers, TNFD, systems modellers, and, of course, AI practitioners.

翻译：金融机构、金融监管机构及政策制定者日益认识到应对自然相关风险与机遇的重要性。由于自然领域存在大量异构数据、投资价值链的复杂性以及各组成部分与自然之间的关联关系，金融机构评估自然相关风险面临巨大挑战。人工智能可解决扩展数据分析与复杂系统分析的双重问题。我们探讨了通过发现数据填补现有数据缺口、不确定性下的数据估计、时间序列分析及（近）实时更新等议题。本报告针对"巴西牛肉供应链用例"与"水务公用事业用例"两大不同场景提出了潜在的人工智能解决方案。这两个案例涵盖了可持续金融领域的广泛视角：巴西肉牛养殖案例体现了"绿化金融"——将自然考量融入主流金融决策，引导投资从历史记录欠佳、不可持续的行业转移；英国水务公用事业案例中部署基于自然的解决方案则体现了"融资绿化"——推动投资向自然正向成果倾斜。两个案例还覆盖了不同行业、地理区域、金融资产及人工智能建模技术，全面展示了人工智能如何应用于推动自然与金融融合过程中面临的各类挑战。本报告主要面向金融机构，同时对ESG数据提供商、自然相关财务信息披露工作组、系统建模者及人工智能从业者也具有重要参考价值。