{"title":"对社会负责的(再)保险承保实践:随时可用的“大数据”对优化巨灾风险管理的贡献","authors":"Ivelin M. Zvezdov, S. Rath","doi":"10.2139/ssrn.2737508","DOIUrl":null,"url":null,"abstract":"Today's advances in big data technologies readily allow for storing large inter-dependent data sets of historical and modeled natural hazard and financial data and unifying their granularity and accuracy with common geo-spatial and risk-type record identifiers. This is a significant component at both single insurance account, and even more so at the larger multi-policy portfolio scale for enabling optimal and socially responsible insurance underwriting practices. This supports insurance risk transfers by creating more accurate and all-uncertainty encompassing pricing techniques, and exposes these techniques and methodologies to all market players, including insurance policy holders via transparent statistical and actuarial principles.","PeriodicalId":210981,"journal":{"name":"Corporate Governance: Social Responsibility & Social Impact eJournal","volume":"588 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Towards Socially Responsible (Re)Insurance Underwriting Practices: Readily Available ‘Big Data’ Contributions to Optimize Catastrophe Risk Management\",\"authors\":\"Ivelin M. Zvezdov, S. Rath\",\"doi\":\"10.2139/ssrn.2737508\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today's advances in big data technologies readily allow for storing large inter-dependent data sets of historical and modeled natural hazard and financial data and unifying their granularity and accuracy with common geo-spatial and risk-type record identifiers. This is a significant component at both single insurance account, and even more so at the larger multi-policy portfolio scale for enabling optimal and socially responsible insurance underwriting practices. This supports insurance risk transfers by creating more accurate and all-uncertainty encompassing pricing techniques, and exposes these techniques and methodologies to all market players, including insurance policy holders via transparent statistical and actuarial principles.\",\"PeriodicalId\":210981,\"journal\":{\"name\":\"Corporate Governance: Social Responsibility & Social Impact eJournal\",\"volume\":\"588 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Corporate Governance: Social Responsibility & Social Impact eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2737508\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Corporate Governance: Social Responsibility & Social Impact eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2737508","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards Socially Responsible (Re)Insurance Underwriting Practices: Readily Available ‘Big Data’ Contributions to Optimize Catastrophe Risk Management
Today's advances in big data technologies readily allow for storing large inter-dependent data sets of historical and modeled natural hazard and financial data and unifying their granularity and accuracy with common geo-spatial and risk-type record identifiers. This is a significant component at both single insurance account, and even more so at the larger multi-policy portfolio scale for enabling optimal and socially responsible insurance underwriting practices. This supports insurance risk transfers by creating more accurate and all-uncertainty encompassing pricing techniques, and exposes these techniques and methodologies to all market players, including insurance policy holders via transparent statistical and actuarial principles.