Combining physics-based models, probabilistic approaches and machine learning to create forward-looking climate risk models at various temporal scales.
Leveraging computer vision and deep learning to create a best-in-class, high-resolution, digital terrain model for flood analysis.
Representing the range of possible futures resulting from the interaction between human activity and climate change through our Multiple Futures Models.
Leveraging the combination of machine learning and HPC to generate better model inputs
Widening access to highly sophisticated modelling techniques traditionally used by insurers. Probabilistic physics-based models using stochastic catalogues can now be applied to use cases in finance and asset management.