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Aggregating global insurance risk in real-time using Elasticsearch and H3

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Aggregating global insurance risk in real-time using Elasticsearch and H3
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237
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CC Attribution 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Insurance companies can underwrite millions of locations and having too much risk in one place can mean the difference between profit and loss. In this session we will explore the business challenge and understand how a geospatial platform based on Elasticsearch and the Uber H3 spatial index can help insurers make better decisions. Insurance companies can underwrite millions of locations through complex distribution networks of brokers and direct channels and having too much risk in one place can mean the difference between profit and loss, In extreme cases a catastrophic event such as 9/11 could bring down the company completely. In this session we will explore the business challenge and understand how a geospatial platform based on Elasticsearch and the Uber H3 spatial index can help insurers make better decisions and avoid accumulation issues. The techniques that we will demonstrate are applicable to many real-world problems where we have large amounts of data that need to be visualised and analysed in real-time. Authors and Affiliations – Mark Varley, Addresscloud, United Kingdom Track – Use cases & applications Topic – Business powered by FOSS4G Level – 1 - Principiants. No required specific knowledge is needed. Language of the Presentation – English