Environmental change related to human activities has become a major systemic risk that financial institutions must take into account. While climate-related regulations have emerged, and with them the need to estimate the effects of climate change and transition efforts on economies and financial stability, the more global issue of nature has remained an unsolved problem, with a lack of data and methodologies.
In this paper, we propose an end-to-end model that estimates changes in financial risk metrics (PD, LGD, EL, VaR) based on nature degradation simulated from socioeconomic and climate change scenarios.
We base our approach on standard economic and financial modeling used in systemic stress testing exercises, and complement it upstream with ad hoc transmission channels from natural capital asset maps to economic production losses, using input-output analysis to consider geosectoral risk diffusion.
Our model can be used to carry out nature stress testing and to compute nature value at risk for corporate portfolios.
