{"title":"Increase data sharing or die? An initial view for natural catastrophe insurance","authors":"P. Timms, J. Hillier, Chris Holland","doi":"10.1080/00167487.2022.2019494","DOIUrl":null,"url":null,"abstract":"ABSTRACT This article is an illustration of geography in action, recounting an investigation into an industry’s views of data sharing. The insurance sector is fundamentally analytics driven and based on geospatial data. One option for more effective and efficient insurance for natural hazard risks (e.g. flooding, earthquake) is, in theory, to increase the sharing of data between the various (re)insurance organisations. However, it remains unclear as to what extent this is desirable or practical for commercially sensitive data. This work creates a conceptual model of data sharing in (re)insurance, focusing on loss (claims) data for natural hazards as an illustrative microcosm, including the barriers and solutions to sharing. In light of this, an initial view on the future shape of insurance data sharing is given, finishing with an opinion on whether or not new external disruptors (e.g. start-ups in InsureTech or tech giants such as Google, Amazon and Tencent) pose an existential threat to incumbent firms.","PeriodicalId":46568,"journal":{"name":"Geography","volume":"107 1","pages":"26 - 37"},"PeriodicalIF":1.4000,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geography","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/00167487.2022.2019494","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 3
Abstract
ABSTRACT This article is an illustration of geography in action, recounting an investigation into an industry’s views of data sharing. The insurance sector is fundamentally analytics driven and based on geospatial data. One option for more effective and efficient insurance for natural hazard risks (e.g. flooding, earthquake) is, in theory, to increase the sharing of data between the various (re)insurance organisations. However, it remains unclear as to what extent this is desirable or practical for commercially sensitive data. This work creates a conceptual model of data sharing in (re)insurance, focusing on loss (claims) data for natural hazards as an illustrative microcosm, including the barriers and solutions to sharing. In light of this, an initial view on the future shape of insurance data sharing is given, finishing with an opinion on whether or not new external disruptors (e.g. start-ups in InsureTech or tech giants such as Google, Amazon and Tencent) pose an existential threat to incumbent firms.