Spatial finance
Overview
We are pioneers of 'spatial finance' and coined the term. Spatial finance is the integration of geospatial data and analysis into financial theory and practice.
Our work
More geospatial data is being collected than ever before. When combined with artificial intelligence to automatically scan and interpret this vast amount of visual data on the cloud, unprecedented capabilities are becoming available. These rapidly growing data mountains can then feed increasingly sophisticated predictive models to generate more and more insights and results.
This has the potential to transform the availability of information in our financial system. It will allow financial markets to better measure and manage environment-related risks, as well as a vast range of other factors that affect risk and return in different asset classes.
Understanding all the possible use cases is in its infancy. Geospatial data and analysis enabled by new technologies will also allow us to (re)examine a vast range of hypotheses, potentially with implications for financial theory as well as practice.
We founded and work through the Spatial Finance Initiative (SFI), which aims to mainstream geospatial capabilities enabled by space technology and data science into financial decision-making globally. SFI undertakes and coordinates research and channels it into real-world finance-related applications. SFI has been established by The Alan Turing Institute, Satellite Applications Catapult, and the University of Oxford.
Research topics include:
- Using geospatial data and analysis to better measure different environmental and social risks and impacts
- Making accurate, comparable, and comprehensive asset-level data tied to ownership publicly available across all major sectors and geographies
- Spatial reporting to complement traditional and integrated financial reporting
- Understanding and testing possible implications of spatial finance for financial theory
