Next-generation analytics for climate finance

Josh Gilbert and Gopal Erinjippurath

Global climate models and risk analytics have been developed and refined over decades, but rapid changes in the climate have led to increasing frequency and severity of climate-related events, causing billions in economic damages. However, since the 2010s technological advances have led to improvements in our monitoring and assessment of these risks. Satellite data, cloud computing and machine-learning capabilities have provided high cadence, high-quality climate data.

This chapter highlights the significance of these improvements in climate risk analytics for extreme climate events and greenhouse gas (GHG) emissions monitoring. The new generation of climate risk analytics has also broadened the applications for this data, across regulation, operational risk, and the creation of new climate-aware financial instruments, products and services. In this chapter, we present two specific dimensions in which next-generation analytics using geospatial techniques can be useful for climate finance. One dimension explores the need for more functional climate models when assessing physical climate risk exposure, while the other explores the use of satellite-derived techniques to assess

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