We would like to invite you to our fourth AI for Sustainable Finance Seminar. The series is an opportunity for researchers and practitioners working or interested in this emerging interdisciplinary field to come together and explore new methods, datasets, and research questions. It is also an opportunity to share updates with colleagues and network with your peers. The seminars are organised by The Alan Turing Institute Sustainable Finance Theme.
The fourth webinar will take place on the 28th October at 3pm UK time, it will be followed by wider network updates and discussion chaired by Dr Ben Caldecott.
The seminar will be given by Dr Daniel Moran, who is an environmental economist at NTNU in Norway and uses big data and data-driven analysis to shed light on the connections between natural systems, including the climate and the economy. Dr Moran is a co-creator Eora global supply chain model which tracks monetary and biophysical flows globally. Work on carbon and biodiversity footprints using Eora has been featured in top academic journals and featured in popular media such as National Geographic, the New York Times, and TIME magazine, and the model is in wide use in the private and government sector as well as by academic users at over 800 universities. Dr Moran holds a PhD from the School of Physics at the University of Sydney. Prior to joining academia, he worked for Nobel economist Paul Romer in Silicon Valley, and on Wall Street at MSCI’s ESG research unit.
About the event
One important challenge in conservation is that, in many hotspots, export industries drive overexploitation. Conservation measures must consider not just the point of impact, but also the consumer demand that ultimately drives resource use. The emerging field of spatial footprinting offers tools to identify implicated supply chains by coupling spatial, and when available, remote sensing, data to global supply chain databases which can trace implicated products through multiple trade and transformation steps to final consumers. Linking GIS to spatial data can help businesses and governments realize more sustainable supply chains.