灾难模型:在偿付能力评估和管理下得出南非保险公司资本要求的200年1次死亡率冲击

IF 0.1 Q4 BUSINESS, FINANCE South African Actuarial Journal Pub Date : 2015-01-01 DOI:10.4314/SAAJ.V15I1.3
Adam Plantinga, D. Corubolo, R. Clover
{"title":"灾难模型:在偿付能力评估和管理下得出南非保险公司资本要求的200年1次死亡率冲击","authors":"Adam Plantinga, D. Corubolo, R. Clover","doi":"10.4314/SAAJ.V15I1.3","DOIUrl":null,"url":null,"abstract":"This paper investigates catastrophe risk for South African life insurers by considering the additional deaths that could arise from a 1-in-200 year mortality shock. Existing South African academic research on catastrophic risk has mostly focused on property losses and the resulting impact on property insurance companies. Life catastrophe risks have not been extensively modelled in a South African context. Local research would be beneficial in terms of quantifying these catastrophic risks for South African life insurers, and would assist firms when assessing their own catastrophe mortality solvency requirements under the new Solvency Assessment and Management (SAM) regime by providing a summary of data relating to various past catastrophes. In this paper we model a wide range of catastrophes to assess such mortality risk faced by life insurance companies in South Africa. An extensive exercise was undertaken to obtain data for a wide range of catastrophes and these data were used to derive severity and frequency distributions for each type of catastrophe. Data relating to global events were used to supplement South African data where local data were sparse. Data sources included official government statistics, industry reports and historical news reports. Since, by nature, catastrophic events are rare, little data are available for certain types of catastrophe. This means there is a large degree of uncertainty underlying some of the estimates. Simulation techniques were used to derive estimated distributions for the potential number of deaths for particular catastrophic events. The calculated overall shock for the national population was 2.6 deaths per thousand, which was lower than the SAM Pillar 1 shock of 3.2 deaths per thousand for the same population. It has been found that a worldwide pandemic is by far the main risk in terms of number of deaths in a catastrophe and, given that this is the most significant component of catastrophe risk, prior research on this risk in an South African context is summarised and revisited.","PeriodicalId":40732,"journal":{"name":"South African Actuarial Journal","volume":null,"pages":null},"PeriodicalIF":0.1000,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Catastrophe modelling: deriving the 1-in-200 year mortality shock for a South African insurer’s capital requirements under Solvency Assessment and Management\",\"authors\":\"Adam Plantinga, D. Corubolo, R. Clover\",\"doi\":\"10.4314/SAAJ.V15I1.3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates catastrophe risk for South African life insurers by considering the additional deaths that could arise from a 1-in-200 year mortality shock. Existing South African academic research on catastrophic risk has mostly focused on property losses and the resulting impact on property insurance companies. Life catastrophe risks have not been extensively modelled in a South African context. Local research would be beneficial in terms of quantifying these catastrophic risks for South African life insurers, and would assist firms when assessing their own catastrophe mortality solvency requirements under the new Solvency Assessment and Management (SAM) regime by providing a summary of data relating to various past catastrophes. In this paper we model a wide range of catastrophes to assess such mortality risk faced by life insurance companies in South Africa. An extensive exercise was undertaken to obtain data for a wide range of catastrophes and these data were used to derive severity and frequency distributions for each type of catastrophe. Data relating to global events were used to supplement South African data where local data were sparse. Data sources included official government statistics, industry reports and historical news reports. Since, by nature, catastrophic events are rare, little data are available for certain types of catastrophe. This means there is a large degree of uncertainty underlying some of the estimates. Simulation techniques were used to derive estimated distributions for the potential number of deaths for particular catastrophic events. The calculated overall shock for the national population was 2.6 deaths per thousand, which was lower than the SAM Pillar 1 shock of 3.2 deaths per thousand for the same population. It has been found that a worldwide pandemic is by far the main risk in terms of number of deaths in a catastrophe and, given that this is the most significant component of catastrophe risk, prior research on this risk in an South African context is summarised and revisited.\",\"PeriodicalId\":40732,\"journal\":{\"name\":\"South African Actuarial Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.1000,\"publicationDate\":\"2015-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"South African Actuarial Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4314/SAAJ.V15I1.3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Actuarial Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/SAAJ.V15I1.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 3

摘要

本文调查灾难风险的南非人寿保险公司通过考虑额外的死亡,可能从1-在200年的死亡率冲击。南非现有的关于灾难性风险的学术研究主要集中在财产损失及其对财产保险公司的影响上。生命灾难风险还没有在南非的背景下进行广泛的建模。当地的研究将有利于南非人寿保险公司量化这些灾难性风险,并将通过提供与过去各种灾难有关的数据摘要,帮助公司在新的偿付能力评估和管理(SAM)制度下评估自己的灾难死亡率偿付能力要求。在本文中,我们建立了一个大范围的灾难模型,以评估南非人寿保险公司面临的这种死亡风险。进行了广泛的工作,以获得各种灾难的数据,并利用这些数据得出每种灾难的严重程度和频率分布。与全球事件有关的数据被用来补充当地数据稀少的南非数据。数据来源包括政府官方统计数据、行业报告和历史新闻报道。由于从本质上讲,灾难性事件是罕见的,因此对于某些类型的灾难几乎没有可用的数据。这意味着在一些估计的基础上存在很大程度的不确定性。利用模拟技术推导出特定灾难性事件的潜在死亡人数的估计分布。计算出的全国人口总体冲击为每千人2.6人死亡,低于相同人口的第一支柱冲击3.2人死亡。研究发现,就灾难造成的死亡人数而言,世界范围的大流行病是迄今为止的主要风险,鉴于这是灾难风险的最重要组成部分,本文总结并重新审视了之前在南非背景下对这一风险的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Catastrophe modelling: deriving the 1-in-200 year mortality shock for a South African insurer’s capital requirements under Solvency Assessment and Management
This paper investigates catastrophe risk for South African life insurers by considering the additional deaths that could arise from a 1-in-200 year mortality shock. Existing South African academic research on catastrophic risk has mostly focused on property losses and the resulting impact on property insurance companies. Life catastrophe risks have not been extensively modelled in a South African context. Local research would be beneficial in terms of quantifying these catastrophic risks for South African life insurers, and would assist firms when assessing their own catastrophe mortality solvency requirements under the new Solvency Assessment and Management (SAM) regime by providing a summary of data relating to various past catastrophes. In this paper we model a wide range of catastrophes to assess such mortality risk faced by life insurance companies in South Africa. An extensive exercise was undertaken to obtain data for a wide range of catastrophes and these data were used to derive severity and frequency distributions for each type of catastrophe. Data relating to global events were used to supplement South African data where local data were sparse. Data sources included official government statistics, industry reports and historical news reports. Since, by nature, catastrophic events are rare, little data are available for certain types of catastrophe. This means there is a large degree of uncertainty underlying some of the estimates. Simulation techniques were used to derive estimated distributions for the potential number of deaths for particular catastrophic events. The calculated overall shock for the national population was 2.6 deaths per thousand, which was lower than the SAM Pillar 1 shock of 3.2 deaths per thousand for the same population. It has been found that a worldwide pandemic is by far the main risk in terms of number of deaths in a catastrophe and, given that this is the most significant component of catastrophe risk, prior research on this risk in an South African context is summarised and revisited.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
South African Actuarial Journal
South African Actuarial Journal BUSINESS, FINANCE-
自引率
0.00%
发文量
0
期刊最新文献
Anti-selection in voluntary health insurance markets: A focus on medical schemes in South Africa Quantitative guidelines for retiring (more safely) in South Africa Suitability of the 2.5% net discount rate for quantum of damage calculations in South Africa An economic scenario generator for embedded derivatives in South Africa The impact of giving and receiving remittances on life insurance purchases
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1