Transition
Risk
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 below list of projects are funded in the first phase of the competition under the Transition Risk Theme.
SME Green Credit Score
Financial institutions experience significant challenges in assessing environmental sustainability and its impact on the credit quality of small and medium-sized enterprises (SMEs), despite SMEs’ material contribution to UK business emissions.
Our project aims to address these challenges and gaps in the market through the development of an innovative ‘Green Credit Score’ technology, which will enable financial institutions and public authorities to assess climate and environmental risks for SMEs.
This will facilitate more sustainable lending and significantly improve sustainability metrics for SMEs whilst building a virtuous circle of carbon footprint measurement and risk-based funding, thus helping to meet net zero targets.
Real Estate Portfolio Carbon Risk Score (CaRiS)
CaRiS is a methodology and proof-of-concept tool to enable financial services organisations to better understand embodied and operational carbon associated with residential assets, enabling effective risk management and better decision making in managing portfolios in future.
The project team is working with stakeholders to clarify the specification for a tool, and to develop and test an early prototype drawing upon existing datasets, standards and decarbonisation pathways.
Emissions Tracking for Pension Portfolio Managers
GHGSat is developing a new emissions monitoring tool and data analytics solution that will support institutional investors from pension funds with an independent third-party assessment of Scope 1 and 2 emissions for key parts of their assets.
The solution being developed in this project is set apart from similar products because it will integrate the direct methane emissions measurements GHGSat satellites already in orbit. The satellite constellation is the only one of its kind in orbit today.
An Innovative Knowledge Graph approach to extract high volumes of climate and environmental structured and unstructured data
Auquan has developed an information capture algorithm that uses NLP and an auto-assembling knowledge-graph technology tailored for financial services. It extracts information from unstructured and structured data.
The NLP suite has so far been trained to extract financial entities, locations and relationships from text, which get assembled into an interconnected knowledge graph, so users can easily visualise an entire value chain (subsidiaries, suppliers, clients, operational locations, owned assets) of a company.
Scope 3 emissions check model for real-time consumer loan decision process (S3-ECheMo)
Modirect Limited
S3-ECheMo is an innovative approach to scoring the environmental friendliness of consumer loan requests (based on the intended activities) and integrating the obtained information with credit risk assessments in pricing interest rates on loans.
The project seeks to profile consumer loans with respect to the potential scope 3 emissions and transition risks. S3-ECheMo would also provide an intuitive dashboard for supporting emissions trading (costs/rebate) decision-making.
A geospatial asset management model for physical and transition risk assessments and capital reallocation (GeoAM2)
GeoAM2 is a disruptive approach to asset management that seeks to achieve three things:
(1) aggregate assets owned by asset management firms into a database with extensive unique nameplate data;
(2) geolocate and tag these assets to determine countries or regions of existence; and (
3) evolve immediate and predictive asset risk assessment scores using integrated AI and ML algorithms.
GeoAM2 has in place the sub-components of investments held by asset/wealth management firms and in real-time and provides two risk scores (immediate and predicted) to managers highlighting and predicting how such risks will change based on projected government policies.
