Machine learning & data science
Overview
Enabling technologies, such as distributed ledgers and smart contracts, can enable financial transactions and behaviours that support the transition to sustainability. Data science and AI can help the financial system secure much more accurate, consistent, and timely data to inform decision-making, risk pricing, and capital allocation.
Our work
This research cluster seeks to deploy data science and AI to support the theory and practice of sustainable finance.
Research topics include:
- Deploy data science techniques to new and existing datasets, including alternative data, to support financial institutions and financial regulators in the transition to global environmental sustainability
- Harness new technologies, including distributed ledgers and smart contracts, to enable the efficient deployment of capital into sustainable investments across different asset classes, sectors, and geographies
- Ensure greater data quality, consistency, and comparability, including through better data assurance and new data standards
Projects, programmes, and special initiatives
- GeoAsset
- Sustainable Finance Theme at The Alan Turing Institute
- Leverhulme Centre for Nature Recovery (LCNR)
- UK Centre for Greening Finance & Investment (CGFI)
Research associate
- Dr Alok Singh | Research Associate, Machine Learning and Data Science