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

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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.