catastrophe modeling in insurance and reinsurance

Insurance & Reinsurance

Bring limitless scale to your insurance analytics. Cloud-native spatial analysis for catastrophe modeling, fraud detection, and portfolio risk analysis.

axa insurance customer bluecross blueshield insurance customermapfre insurance customerswiss re insurance customerbnp insurance customer

Functional risk solutions to better assess exposure and model catastrophes. 
Access powerful spatial insights and climate related data streams to effectively manage your insured assets, assess disaster impacts  and control policy selection before the risk is in your portfolio.

Video opener

Identifying patterns in risk exposure becomes far more efficient with fast and intuitive analysis and visualization of location data.
Empower your insurance analytics with risk intelligence that boosts both your resiliency and portfolio understanding - whether it is commercial, home, health, or any other type of insurance.

17%
more staff using geo-insights
Video opener

An increasing number of Insurance firms are now moving towards Spatial Risk Management - using scalable cloud native software to show the spatial distribution of risks. 
Combine low-code analytical tools, with thousands of geospatial datasets to take insurance risk modeling to the next level. Model and predict risks, detect anomalies, and subsequently plan, underwrite, and react more rapidly to potential risks or opportunities within your insurance portfolios.

3x
more geospatial data used in underwriting
Video opener

Geospatial data & analytics can be integrated into predictive models to surface potential fraud indicators based on geographic patterns, helping insurers proactively investigate suspicious claims.
Use spatial data and analytics to analyze unusual patterns and trends in policy claims data based on geographic locations that may indicate potential fraudulent activity.

6
hours less spent on data cleaning per week
Video opener

Use spatial data and analysis to assess risk exposure for insured assets and drive more effective pricing strategies. 
Take into consideration key risk factors such as flood, fire or storm events, burglary and vehicle crime incidents to determine optimal home and vehicle premium pricing. Now you can easily bring a broad range of risk-related spatial datasets together in powerful predictive spatial models.

Video opener

WHAT OUR CLIENTS SAY

TALK TO US

Request a Demo

Schedule a 20 minute meeting with our experts to understand how you can use spatial analysis in your organization.