Spatial Finance Initiative

Earth observation and remote sensing combined with machine learning has the potential to transform the availability of information in our financial system and change how risks, opportunities, and impacts are measured and managed by financial institutions. ‘Spatial finance’, where geospatial data is integrated into financial theory and practice, creates a significant opportunity for the financial services industry.

Finance applications enabled by geospatial data and analysis are extensive, but such approaches are particularly helpful for analysing risks and impacts related to climate change and the environment. For these reasons, we believe that geospatial analysis will become a core competency for financial analysis and this will have very significant implications for information markets, financial products, and risk management. This will help financial markets to measure and manage climate-related risks, as well as a vast range of other factors that affect risk and return in different asset classes.

Spatial Finance Initiative

The Spatial Finance Initiative has been established to bring together research capabilities in space, data science, and financial services to make them greater than the sum of their parts. The Initiative is designed to be a funnel, undertaking and coordinating world-leading academic research and channelling these into real-world finance-related applications. The research will be translated into practical and pre-operational products and services by working closely with the finance community and geospatial and financial services providers.

The Initiative has been established by the Alan Turing Institute, Green Finance Initiative, Satellite Applications Catapult, and the University of Oxford. It is a multi-disciplinary multi-stakeholder project focused on globally significant research and applications.

The Initiative will have a number of outputs over multiple years: research projects, (pre-) operational demonstrators, events, training and capacity building, and the incubation of applications.

Research Questions Include:

  • How can earth observation and machine learning secure geospatial data, particularly asset-level data, relevant to financial decision-making?
  • What does geospatial data mean for the future of financial analysis and what hypotheses can we test with such data?
  • How can spatial finance support the implementation of the Task Force on Climate-related Financial Disclosures (TCFD)?
  • What are the implications for the skills and resources available for financial analysts?
  • How could geospatial data and ‘spatial reporting’ complement and support traditional financial reporting, as well as integrated reporting?
  • What uses could geospatial data have for non-financial objectives and impact investing?
  • How can geospatial data support engagement with investee companies?
  • Does geospatial data and analysis have implications for traditional theories of finance and economic geography?


The Alan Turning Institute

The Alan Turing Institute, headquartered in the British Library, London, was created as the national institute for data science in 2015. In 2017, as a result of a government recommendation, we added artificial intelligence to their remit.

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City of London Green Finance Initiative

The City of London Corporation – the body responsible for running London’s Square Mile – regards green finance as prudent, profitable and one of the best tools available in the race to cut carbon.

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Oxford Sustainable Finance Programme

The Oxford Sustainable Finance Programme at the University of Oxford Smith School of Enterprise and the Environment is a multidisciplinary research centre working to be the world's best place for research and teaching on sustainable finance and investment.

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