Innovate UK, the UK’s national innovation agency, is funding innovative solutions that integrate climate and environmental factors into financial services through its SBRI – Climate and Environmental Risk Analytics for Resilient Finance competition. CGFI is supporting Innovate UK and successful applicants to deliver the next generation of green finance analytics through expert advice and connecting applicants with potential users to shape the development of these innovative solutions early on.
The projects below are funded in the first phase of the competition under the Impact Disclosure theme.
Nature Based Solutions Analytics Platform
Alo Mundus’s platform provides investors and organisations with the tools they need to navigate the increasing variety of forestry projects that are cropping up worldwide.
It identifies opportunities, analyses them, and ranks them based on their potential to provide value to investors and ensure that corporations meet their social responsibility goals. I
t allows active management of portfolio risk and portfolio rebalancing decisions by identifying best bets among forestry investments through our monitoring systems.
When combined with our marketplace, customers can invest in projects that align with organisational values, from achieving NetZero to creating scalable and evidence-based social and biodiversity impacts.
A Novel AI-based Platform for Transparent Double materiality impact disclosure in the finance Industry.
Asset managers in sustainability responsible investing must gather climate and environmental data to understand companies’ climate-related risks and generate informed investment decisions.
Assessing companies’ climate-related risks, however, is challenging because ESG reports do not provide credible and transparent data sources, up to date data sources and metrics, transparent methodology, and consistent methodology focused on double materiality.
We propose a novel AI-based platform for enhanced environmental impact disclosure. Our solution combines seamlessly: transparent and unbiased data, focus on “double materiality”, and transparent metrics methodology using the SASB materiality map and the sustainability reporting standards roadmap from the EFRAG.
Machine learning powered tooling for analysing climate alignment in the financial industry
CAR is building an application to seamlessly integrate climate and environmental factors into financial decision making.
We do this using state of the art language models from machine learning and modern data pipelines to summarise relevant information for the asset manager.
Our application is 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 these factors to be considered in regular decision-making processes
Telespazio UK proposes to develop a satellite based AI Spatio- temporal tool called FinEO that ingests satellite imagery, datasets associated to specific industry activities and environmental conservation.
The tool will measure changes in the land and water that can be associated to industry activities addressing natural capital deterioration and/or restoration for environmental risk assessment.
FinEO addresses Impact Disclosure as the solution aims to work on disclosing environmental impacts across industry activities and/or validation of declared disclosures.
FinEO also addresses litigation risks around climate related claims as it could play a role in being a tool of transparency and disclosure validation.