Aon plc, a leading global professional services firm, today announced the firm’s multi-year collaboration with Asia Pacific climate data and analytics provider AbsoluteClimo, helping to advance climate modelling and inform better decisions as organizations navigate emerging volatility from climate-based perils.
The collaboration, which aims to analyse the effects of climate change and variability on climate-based peril activity, adds to Aon’s growing suite of analytical and academic initiatives to bring the latest climate science to our arsenal, helping to evolve our risk understanding and drive exposure mitigation to inform better decisions.
Data provided by AbsoluteClimo’s proprietary global climate physics and catastrophe machine learning models, GoTCHA and ClimoCats, helps to inform the view of Aon’s catastrophe modelling teams, allowing climate change considerations to be incorporated into modelled results for clients.
Peter Cheesman, head of APAC Analytics for Aon’s Reinsurance Solutions, said: “Our proof of concept collaboration with AbsoluteClimo is enabling us to test how climate risk is evaluated. We are working on modelling enhancements for our clients and anticipate this collaboration will continue to provide comprehensive analyses and forecasts of significant and costly perils in the Asia Pacific region.”
AbsoluteClimo’s models can provide climate forecasts months and years into the future, which Aon can draw upon when necessary to assist re/insurer clients to develop forward-thinking underwriting and pricing strategies.
AbsoluteClimo CEO and Climatologist Brendan Lane Larson added: “By working with Aon, we are excited to be able to bring our cutting-edge technology to the benefit of the insurance industry. Through this collaboration, we anticipate further innovation in our capabilities as we help each other progress our own understanding of risk through advanced data and analytics.”
For more information about Aon’s Reinsurance Solutions, please visit: https://www.aon.com/home/solutions/reinsurance.html.