Insurance Analytics for Insurance & Reinsurance

Boost business-analytics collaboration

Analyzing massive data volumes slows down decision-making. Harness cloud-native technology to perform seamless in-depth analysis at scale.

Use real-time insights

Without access to real-time data, organizations struggle to adapt to changing conditions. Stay agile with dynamic dashboards and interactive maps with real-time visibility into your analytics.

Deliver data-driven predictions

Identifying and mitigating risks is impossible without accurate data. Build predictive models to anticipate market changes and adjust pricing strategies effectively.

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Get inspired by our customers

"Using CARTO has allowed us to analyze large amounts of spatial data for 5G deployment at scale and build a creative solution to a complex industry problem."

Kendra Lord

Director of Geospatial Engineering & Analytics, T-Mobile

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“By working with CARTO we’ve been able to build the world’s leading telco data monetization solution (Vodafone Analytics) for Tourism, Real Estate & Retail - turning mobile event data into highly valuable spatial insights in 5 countries.”

David Gonzalez

Chief Data Officer at Vodafone Group

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Migrating to CARTO’s cloud-native Location Intelligence platform was, without doubt, the right choice for us. The enhanced analytical capabilities of CARTO have opened up our business to new possibilities for more advanced spatial use cases. More than 700 active users of our tools can now work more efficiently to deliver faster and more accurate services themselves.

Jozef Sorocin

Special Projects at g-Xperts GmbH

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“CARTO has allowed us to geo-enable our data, multiplying our reach. This extra reach allows us to work on things that affect people very directly, which is an essential part of our mission at SwissRe.”

Georgios Technitis

Senior Data Scientist at SwissRe

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Portfolio Risk Analysis

Assessing risk at scale can be time-consuming and resource-intensive. Accelerate decision-making with low-code analytical tools which allow you to quickly understand risk concentration, model potential threats, and detect anomalies.

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How to Use Spatial Data to Create a Wildfire Risk Index

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Catastrophe Modeling

Precision is key when estimating the economic impact of disasters. Harness hyper-local space-time data to accurately predict the economic effects of extreme events, enabling informed decisions about insured assets and policy selection.

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Fraud Analytics

Fraud detection can be an overwhelming task due to the volume of data and the complexity of patterns involved. Use hyper-local predictive models to pinpoint suspicious trends in claims data, streamlining your fraud detection efforts.

Exposure Management

Traditional methods for assessing risk exposure can be slow and cumbersome. Gain critical insights through fast and intuitive analyses of large volumes of location data, ensuring a unified perspective on exposure risks across all portfolios.

Risk-based Pricing Model Development

Accurately assessing risk factors can be a complex and time-consuming process, leading to suboptimal pricing strategies. Streamline the evaluation of key risk factors, such as climate events and urban crime rates, using intuitive analytical tools that enhance your pricing accuracy and responsiveness.