In short

• Predictive modelling is evolving, along with advances in technology and computing power.
• Predicting climate-change risks is a major focus, and models such as the Coupled Model Intercomparison Project and the Risk Index for Climate Displacement are helping insurers and governments in their decision-making.
• Other predictive models have a broader risk focus, with one even identifying data gaps to address for more accurate results.

Insurers and governments have long excelled at gathering data. Combined with tech advances such as AI and a healthy dose of organisational and research collaboration, predictive modelling is becoming increasingly accurate.

Here are some of the models helping us make better plans and decisions.

Predicting the future of climate change

As climate change continues to reshape the insurance landscape, climate-risk models are vital resources for predicting future scenarios.

The Coupled Model Intercomparison Project (CMIP) is a global project of the World Climate Research Programme. It provides climate projections to understand past, present and future climate changes, and to compare and test current climate models.

More than 50 modelling centres around the world participated in its sixth phase, CMIP6, which drew on 190 different experiments to simulate 40,000 years of climate and weather activity, and produced approximately 40 petabytes of data.

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