InsuranceERM Annual Awards 2022 - Americas

Catastrophe risk modelling solution of the year: Aon, Impact Forecasting

Impact Forecasting's Automated Response Offering (AER) claims the catastrophe risk solution of the year award after expanding coverage of its service to over 100 clients in the last 12 months.

The AER service transforms forecast data from weather services into wind footprints modelled against client portfolios to produce loss reports, which are then rapidly emailed to clients.

During 2021, the tool provided automated loss projections for windstorms in Europe, a busy Atlantic hurricane season in the US, as well as including Japan typhoons for the first time.

In practice, the service identifies locations most likely to be affected by storms allowing clients and stakeholders, among others, to prioritise claims operations in the necessary areas. The resulting reports are regularly updated in accordance with evolving data and are based on "actual event forecast parameters, rather than existing stochastic events".

Will Skinner, managing director at Impact Forecasting, cites the provider's close working relationships with US insurers and Lloyd's syndicates as key to its success.

"Insurers appreciate our willingness to listen to their needs and to provide real improvements in return when possible," said Skinner.

"AER was initiated in this way. We were challenged to improve a client's event response process and we collaborated across teams to deliver that."
Skinner also claims recent Atlantic hurricane seasons have tested and vindicated the solution.

"AER provided insurers and reinsurers with early estimates of projected losses (even before the storms hit land) for all of them – this includes last year's hurricane Ida, an event expected to produce over $25 billion in wind-related losses alone," said Skinner

"The solution uses actual hurricane weather forecast data from a number of different forecasts, rather than pre-modelled event footprints, and worked well during these seasons, at times providing loss forecasts for multiple events simultaneously."