Transitioning to a sustainable future with inclusive, green economies and resilient ecosystems requires huge investments. The rescue packages imposed by the COVID-19 crisis make the pursuit of global sustainability goals even more dependent on urgent investment decisions to be taken by the public and private sector. This article examines some of the basic conditions for scaling up sustainable finance, focussing in particular on decision-support tools (DSTs) that guide investment decisions, such as metrics, rankings, ratings and standards. It identifies key DST strengths and weaknesses via a literature review of 100 publications containing expert opinions of sustainable finance scientists and professionals. This is complemented by a comparative analysis of three DSTs that represent the state of the art in their respective typologies: RobecoSAM’s Country Sustainability Rankings, IFC Performance Standards, and ETH’s Impact ÆSSURANCE Sovereign Ratings. The analysis reveals that: (i) experts express a strong, persistent criticism of current sustainability assessment practice, (ii) three main weaknesses characterize most DSTs: credibility deficit, narrow focus, and time-horizon limitations, and (iii) by using an integrated impact assessment framework, superior forecasting capacity and distributed verification techniques assisted by artificial intelligence, the Impact ÆSSURANCE rating model is a promising solution to scale up sustainable finance.

向具有包容性、绿色经济和弹性生态系统的可持续未来过渡需要大量投资。COVID-19 危机实施的一揽子救助计划使得实现全球可持续发展目标更加依赖于公共和私营部门做出的紧急投资决定。本文探讨了扩大可持续金融的一些基本条件，特别关注指导投资决策的决策支持工具 (DST)，例如指标、排名、评级和标准。它通过对 100 份包含可持续金融科学家和专业人士的专家意见的出版物进行文献回顾，确定关键的 DST 优势和劣势。这是对三种 DST 的比较分析的补充，这三种 DST 代表了各自类型中的最新技术水平：RobecoSAM 的国家/地区可持续性排名、IFC 绩效标准和 ETH 的 Impact ÆSSURANCE 主权评级。分析表明：(i) 专家们对当前的可持续性评估实践表达了强烈、持续的批评，(ii) 大多数 DST 的三个主要弱点是：可信度不足、关注范围狭窄和时间范围限制，以及 (iii) 通过使用综合影响评估框架、卓越的预测能力和人工智能辅助的分布式验证技术，Impact ÆSSURANCE 评级模型是扩大可持续金融规模的有前途的解决方案。