Munich Re is now marketing new hurricane response tools designed to better help carriers assess widespread damage after a hurricane. Willis Towers Watson released an updated version of its Radar pricing software.
Munich Re has unveiled a new selection of hurricane response tools designed to help insurance companies assess widespread property damage after a hurricane and improve their customers’ claims experience.
The reinsurer’s Hurricane Response Suite was developed by Munich Re’s Remote Industries Team, along with its Innovation Lab, Remote Industries Team and the Geospatial Intelligence Center – an initiative of the National Insurance Crime Bureau. Remote Industries offers insurance companies the information they need to prioritize and steer claims adjuster resources, proactively reach out to affected policyholders and ultimately help mitigate losses. It uses high-resolution aerial imagery and machine learning to help insurance companies predict potential property claims four days prior to an expected hurricane.
The Hurricane Response Suite is designed to give insurance companies the fastest and most location-specific detection of property damage within days after a hurricane has occurred. Additional tools provide insurance companies with highly detailed predictions of damage days prior to the hurricane making landfall.
Willis Towers Watson released an updated version of its Radar pricing software, known as Radar 4.5.
The product is designed to deliver a range of metrics that provide companies with insights on pricing fairness to support the selection of rates that meet the business goals of insurers and needs of their customers, Willis Towers Watson said.
Radar 4.5 includes an evaluation library component to help insurers assess their pricing choices against several measures of fairness, such as fairness through unawareness, the quota system and conditional group parity — and determine whether or not their prices adhere to or violate any of those particular metrics within their portfolio.
Other updated features of Radar include further enhancements to the elastic net machine learning method.
Sources: Munich Re, Willis Towers Watson