Machine learning powered tooling for analysing climate alignment in the financial industry

越来越多的人预计，资产所有者和管理者将把很大一部分资本配置到与气候相关的工具上。然而，与传统金融工具不同，传统金融工具的指标(如利率、存续期、股息收益率)是一)容易衡量的，以及二)容易理解的，气候融资指标具有更大的挑战性，原因如下(概述如下)。这意味着资产管理公司很难做出对气候结果进行优化的决策，而且在一切照常的基础上，是否可以i)增加对此类投资的摩擦，以及ii)在限制范围内，助长气候融资领域的资本错配。在这个项目中，CAR与气候债券倡议(CBI)合作，提议建立一个应用程序，将气候和环境因素无缝地整合到金融决策中，彻底改变资产所有者和经理与相关数据的交互方式。我们将构建一个能够从披露文档中提取和汇总复杂气候和环境数据的应用程序。并对照评估气候变化指标的优先国家和国际协调框架(例如欧盟分类)分析产出。该应用程序将使金融市场参与者可以搜索和使用这些数据，从而使他们分析相关信息的能力发生阶段性变化，并在常规决策过程中考虑这些因素。

Asset owners and managers are increasingly expected to allocate large proportions of capital towards climate-related instruments. However, unlike traditional financial instruments, which have metrics (e.g. interest rate, duration, dividend yield) that are i) easily measured, and ii) easily understood, climate finance metrics are significantly more challenging for several reasons (outlined below). This means asset managers find it difficult to make decisions which optimise for climate outcomes, and on a business-as-usual basis, can i) increase frictions towards such investments, and ii) at the limit, contribute to the misallocation of capital within the climate finance space.In this project, CAR, in partnership with the Climate Bonds Initiative (CBI), proposes to build an application to seamlessly integrate climate and environmental factors into financial decision making, overhauling how asset owners and managers interface with relevant data.We will build an application capable of extracting and summarising complex climate and environmental data from disclosure documentation, and analysing the output against prioritised national and international alignment frameworks for assessing climate change metrics (e.g. the EU Taxonomy). The application will make this data searchable and consumable by financial market participants, enabling a step change in their capacity to analyse relevant information and for these factors to be taken into account in regular decision making processes.