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GRA · Insurance Nexus

空间金融资本与危害、风险暴露和转型的交汇之处

健康险与人寿险

Health and life insurance carry the risks of illness, disability, death and living longer than savings last. They sit beside social insurance and public health 系统, and the boundary between private and public cover differs in every country. This page sets out how mortality, morbidity, longevity and pandemic risk develop, how they are measured, and which institutions decide what is covered, reserved and protected.

01登记

Health and life insurance on the record.

02问题

Health and life insurance: how the risk develops.

Social, health and longevity risk. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

机制

Longevity trend risk

Improvements in mortality accumulate over decades. A small misjudgement of the trend compounds across annuity and pension liabilities, and the error is recognised only slowly as experience emerges.

机制

Morbidity and medical cost

Claims for illness and disability depend on incidence, recovery, treatment practice and the price of care. New therapies, ageing and changing diagnosis shift costs faster than tariffs and reserves adjust.

机制

Pandemic shock

A pandemic raises mortality and morbidity at once, disrupts care, and hits asset values and operations at the same time, so life, health, business interruption and investment risks become correlated.

机制

Selection and the public boundary

Voluntary cover attracts those who expect to claim; underwriting, waiting periods and pooling rules respond. Where public schemes withdraw or exclude, private cover meets demand it was not priced for.

03地理

Environmental exposure in the Gulf of Mexico coast.

Population density, daytime surface heat and haze over the Gulf of Mexico coast, from NASA GIBS. Each layer carries its own date.

交互式地图需要JavaScript;图层列表和来源见下文。

图层 3

本页的环境暴露

关于此图层
证据
估计值
来源
世界网格化人口 v4.11(NASA SEDAC(哥伦比亚大学 CIESIN))
提供方
NASA SEDAC(CIESIN,哥伦比亚大学)
许可协议
CC BY 4.0
年份版本
null;基于人口普查的估算,静态(2020)
分辨率
约 1 公里网格
不确定性
基于普查的 2020 年每平方公里人口估算,作为风险暴露背景展示;不是受任何危害影响的人口数。
可通过以下方式到达
gibs.earthdata.nasa.gov,仅在您允许加载实时地图后访问
关于此图层
证据
观测(持续云层仍会造成缺口)
来源
VIIRS NOAA-20 3 级产品,8 日(NASA LANCE)
提供方
NASA LANCE
许可协议
NASA 开放数据
年份版本
8 日;卫星 8 日合成;持续云层仍会造成缺口
构建时的最新内容
2026-09-14
分辨率
约 1 公里网格
不确定性
截至所示日期的 8 天内地表的卫星表面温度,是一项热风险暴露指标;不是气温、热指数或高温预警。
可通过以下方式到达
gibs.earthdata.nasa.gov,仅在您允许加载实时地图后访问
关于此图层
证据
观测(云层造成缺口)
来源
VIIRS NOAA-20 Deep Blue AOD(NASA LANCE)
提供方
NASA LANCE
许可协议
NASA 开放数据
年份版本
每日;卫星反演;云层造成缺口
构建时的最新内容
2026-10-14
分辨率
约 2 公里网格
不确定性
对所示日期整个气柱中霾、烟和沙尘的卫星测量;是风险暴露指标,不是地面 PM2.5、空气质量指数,也不是健康预警。
可通过以下方式到达
gibs.earthdata.nasa.gov,仅在您允许加载实时地图后访问
关于此图层
证据
观测
来源
VIIRS 黑色大理石(VNP46A2)(NASA LAADS DAAC)
提供方
NASA LAADS DAAC
许可协议
NASA 开放数据
年份版本
每日;卫星辐亮度,已校正月光和大气影响
构建时的最新内容
2026-10-12
分辨率
约 500 米网格
不确定性
所示日期的卫星夜间辐亮度;灯光是用电和停电情况的代理指标,不是对供应或可及性的测量。
可通过以下方式到达
gibs.earthdata.nasa.gov,仅在您允许加载实时地图后访问
关于此图层
证据
观测(云层造成缺口)
来源
VIIRS 全球洪水产品(NASA LANCE)
提供方
NASA LANCE
许可协议
NASA 开放数据
年份版本
每日;卫星探测;云层造成缺口
构建时的最新内容
2026-10-14
分辨率
约 250 米网格
不确定性
卫星探测;云层造成缺口。按提供方发布的原样提供的卫星或模型栅格数据。云层、扫描带缺口和反演误差会造成缺口和噪声;这些数值是指标,不是某一地点的测量值。
可通过以下方式到达
gibs.earthdata.nasa.gov,仅在您允许加载实时地图后访问
关于此图层
证据
观测(云层造成缺口)
来源
OMI Aura(NASA GES DISC)
提供方
NASA GES DISC
许可协议
NASA 开放数据
年份版本
每日;卫星反演;云层造成缺口
构建时的最新内容
2026-10-10
分辨率
约 2 公里网格
不确定性
所示日期低层大气二氧化氮的卫星柱含量,主要来自燃烧;不是地面浓度,也不是健康预警。
可通过以下方式到达
gibs.earthdata.nasa.gov,仅在您允许加载实时地图后访问

最新可用

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap贡献者 (ODbL) · Natural Earth

正在加载最新的NASA影像。

拖动以移动。按住 Ctrl 或 ⌘ 并滚动、双指缩放或使用按钮缩放;悬停可查看指针下的数值;重置可返回该区域。

Environmental exposure, framed on the Gulf of Mexico coast.NASA 发布的卫星和模型产品,各带自己的日期。它们是指标,而非对任何地点的评估。

数据:NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap 贡献者 · Natural Earth · NASA EONET · CIESIN/Columbia, NASA SEDAC HBASE来源与许可

  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA 开放数据
  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA 开放数据
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). 采用 CC BY 4.0 许可。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 doi:10.7927/H49C6VHW. CC BY 4.0
  • VIIRS 近实时产品(洪水、地表温度、积雪覆盖、校正反射率),NASA LANCE;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • MODIS 和 VIIRS 大气产品,NASA LANCE 和 LAADS DAAC;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • VIIRS Black Marble 夜间灯光,NASA 戈达德航天中心;由 NASA Level-1 与大气档案和分发系统(LAADS DAAC)分发;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • OMI 二氧化氮(Aura)和 OMPS 气溶胶指数(Suomi NPP),NASA;由 NASA GES DISC 分发;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • ASTER GDEM 是 METI 和 NASA 的产品(ASTER Global Digital Elevation Model V003,NASA LP DAAC);影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。引用格式:NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA 开放数据
  • 使用 Natural Earth 制作。免费矢量和栅格地图数据,见 naturalearthdata.com。 公有领域
  • © OpenStreetMap 贡献者(ODbL),经由 NASA GIBS(海岸线、边界、道路和地名)。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 ODbL
  • Blue Marble,NASA Earth Observatory;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • 地球仪和平面地图上的背景信息:海岸线、边界、道路和地名来自 NASA GIBS 参考图层(OpenStreetMap 数据,ODbL,© OpenStreetMap contributors);Blue Marble 影像可作为可选底图;3D 地形和高程读数来自 ASTER GDEM 高程色彩指数(5 m 至 200 m 分级,为便于辨识而作了夸张处理)。边界按已发布的样式绘制,不代表对任何领土的立场。
  • 实时事件:NASA Earth Observatory Natural Event Tracker(EONET);事件仅供参考,并保留其原始来源链接。
  • 实时:NASA EONET。事件仅供参考,不是主管机构的预警。
  • 背景:CIESIN/Columbia, NASA SEDAC HBASE。哥伦比亚大学国际地球科学信息网络中心(CIESIN)和 NASA 社会经济数据与应用中心(SEDAC):Global Human Built-up And Settlement Extent (HBASE) 2010;Seto, Guneralp and Hutyra 2012, Global Grid of Probabilities of Urban Expansion to 2030;Global Urban Heat Island (UHI) Data Set, 2013。
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • 空气质量预报,5 天,PM2.5(CAMS,经由 Open-Meteo):包含经修改的 Copernicus 大气监测服务 2026 年信息。
  • 过去一年的每日气温(ERA5,经由 Open-Meteo):包含经修改的 Copernicus 气候变化服务 2026 年信息。
  • 天气数据来自 Open-Meteo.com (https://open-meteo.com/), 依据 CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). 授权。
  • 可选图层(图层列表中有 14 个来源:实时、预报、观测和背景)在开启时会在地图上和此处显示其提供方署名;预报是模型输出,派生指数是估计值。

图层与日期

  • 人口密度,2020 年:人口:哥伦比亚大学 CIESIN,世界网格化人口 v4.11(2018),NASA SEDAC, CC BY 4.0 · 静态
  • 地表温度,日间,8 天合成:VIIRS NOAA-20 3 级产品,8 天,NASA LANCE · 2026年9月14日
  • 气溶胶光学厚度,每日:VIIRS NOAA-20 Deep Blue AOD,NASA LANCE · 2026年10月13日
  • 夜间灯光,每日:VIIRS Black Marble(VNP46A2),NASA LAADS DAAC · 2026年10月12日
  • 洪水水体,3 日合成:VIIRS 全球洪水产品,NASA LANCE · 2026年10月14日
  • 二氧化氮,低层大气柱:OMI Aura,NASA GES DISC · 2026年10月10日

04指标

衡量什么,以及衡量得如何。

每个指标都注明其单位、频率、背后的来源类型以及数值将附带的证据标签。此处不显示数值:数值由计划依据其自身权限提供。

指标单位节奏来源类型标签
Age-specific mortality ratedeaths per thousand lives exposed年度Civil registration and insured experience观测
Actual-to-expected mortality ratioratio年度Insurer experience studies估算
Period life expectancy at stated age年年度National life tables已发布统计
Excess mortalitydeaths above expected baseline, P-score in percentweekly to annualCivil registration against a baseline估算
Disability incidence and recovery ratesclaims per thousand lives per year年度Insurer experience studies估算
Out-of-pocket health expenditurepercent of current health expenditure年度National health accounts已发布统计
Medical cost trendannual change in claim cost per member, percent年度Health insurer claims data已报告
Policy lapse ratepercent of policies per year年度Insurer persistency studies已报告
05监测

承保与理赔控制台。

团队跟踪该主题时会使用的界面:其指标、状态与决策。名称为示例,数值仅作示意。

承保与理赔控制台

Health and life insurance · Insurer Alpha · Quarter 2

  • 综合成本率,占已赚净保费的 %
    1022关注
  • 偿付能力比率,占 SCR 的 %
    152正常
  • 费率充足性
    1.04指数关注
  • 30 天内理赔,%
    92正常
财产业务组合超出风险偏好GRA · Insurance Nexus

业务条线

财产险,商业20265▲ 3以上
财产险,家庭21866▲ 1范围之内
车险16162▲ 5范围之内
卫生5976▲ 7关注

损失率

Underwriting and claims console: the screen’s structure, terms and states for Health and life insurance.示例名称和示意数值;是设计方案,并非记录或实时系统。
06来源

证据来自何处。

具名公共数据集与机构记录,各自注明许可类别。依协议获得的来源仅按其条款使用,绝不再次发布。

来源它提供什么许可类别
Human Mortality DatabaseDetailed national mortality and population data for life tablesFree with registration, Creative Commons attribution
联合国《世界人口展望》Population estimates and projections, mortality and fertility by countryCreative Commons attribution, IGO
WHO Global Health Expenditure DatabaseHealth spending by source, including out-of-pocket and voluntary insuranceCreative Commons non-commercial, IGO
WHO Global Health ObservatoryMortality, morbidity and health system indicators by country免费,世卫组织条款
Society of Actuaries experience studies and mortality tablesInsured mortality, morbidity and lapse experience, and improvement scalesPublic reports, SOA terms
OECD Health StatisticsHealth status, care resources and financing across member countries免费,OECD 条款
National statistics officesDeath registrations, causes of death and national life tablesPublic, terms per office
07损失模型

损失超越、年均损失和可能最大损失。

处于覆盖范围内的投资组合每年预期损失,以及保险公司和贷款机构定价所依据的 1/100 和 1/250 水平下的预期损失,均来自每个 巨灾模型 uses. Teaching model with stated illustrative values, not a prediction. The map on this page shows The Gulf of Mexico coast; the model itself is not tied to a place.

控制措施

典型年度危害强度(所在地)
1.00 强度指数
极端值的扩散(尺度)
强度指数 0.80
损失一半价值时的强度
4.00 强度指数
脆弱性的离散程度
0.55
危害足迹中的价值占比
40%
防护标准(重现期)
50 年

读数

年均损失
占价值的 0.51%
百年一遇(1/100)的损失
占价值的 24.5%
250 年一遇(1/250)的损失
占价值的 28.4%
百年一遇(1/100)的强度
强度指数 4.68
数字、方法与来源
重现期(年)强度(强度指数)损失(占价值的 %)
10.090.00
21.270.00
41.910.00
72.470.00
133.000.00
243.510.00
444.020.00
824.5323.55
1545.0326.44
2875.5328.87
5366.0330.88
1,0006.5332.53

方法

  1. Gumbel 极值危害 Gumbel (1958), Statistics of Extremes, Columbia University Press
  2. 对数正态易损性(脆弱性) FEMA (2003), HAZUS-MH Technical Manual
  3. 超越概率曲线与年均损失 Grossi and Kunreuther (2005), Catastrophe Modeling, Springer
  4. 堤防效应 Di Baldassarre and others (2013), Socio-hydrology, HESS 17
  5. 不确定性扇形图(参数蒙特卡罗) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
  6. 单因素敏感性(龙卷风图) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley

数据

The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:

  • 河流 Natural Earth
  • 城市范围 Natural Earth
  • 城市 Natural Earth
  • 过去一周 M4.5+ 地震(USGS) 美国地质调查局 · 登记 usgs.earthquake.summary-feeds
  • 降雨率,最近半小时(IMERG) NASA GPM IMERG Early · 登记 nasa.gibs.context-live-layers
  • 河流流量预报,30 天及范围(GloFAS via Open-Meteo) Open-Meteo.com(CC BY 4.0)、Copernicus GloFAS · 登记 open-meteo.public-pages
  • 建成区与居民点范围,2010 年(HBASE,Landsat) CIESIN/Columbia、NASA SEDAC HBASE · 登记 sedac.context-urban-layers
损失超越概率、年均损失和可能最大损失。示意性教学模型:它依据控件设定的数值运行,而不是实测数据。方法:Gumbel 极值危害(Gumbel(1958),Statistics of Extremes,Columbia University Press);对数正态脆弱性曲线(FEMA(2003),HAZUS-MH Technical Manual);超越概率曲线与年均损失(Grossi 和 Kunreuther(2005),Catastrophe Modeling,Springer)。
08决定

由谁决定,以及证据服务于什么。

Insurance Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

谁来决定问题本页面服务的证据
Life insurers and pension fund trusteesWhat mortality improvement and longevity assumptions to adopt, and whether to transfer longevity riskExperience studies, national trends and the spread between improvement scales
Health ministries and social insurance agenciesWhat the public scheme covers and how private cover may complement itOut-of-pocket spending, coverage gaps and the distributional effect of each design
保险监管机构Whether biometric assumptions and pandemic scenarios are adequately reflected in reserves and capitalAssumption benchmarks, stress scenarios and experience against expectation
Health insurersHow to set tariffs and benefit design under medical cost trend and community rating rulesClaims cost trends and pooling rules, labelled by source

该主题产生的产出

  • Guide to mortality, morbidity and longevity risk and the boundary with social insurance
  • Brief on pandemic correlation across life, health and non-life lines
  • Method note on reading excess mortality and experience studies
  • Evidence-to-diligence checklist for mortality improvement assumptions
09孪生与级联模拟器

Trace a shock in health and life insurance to the balance sheet.

Assembled from the Nexus Standards area profile 保险与再保险: the shocks it names, the 系统 and sectors that carry the loss, the controls that dampen it and the data that observe it. Pick an initiating shock and step through the cascade to see which exposures it reaches and where losses could concentrate. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise, not a forecast, a valuation, a rating or investment advice. To model a place of your own choosing, open the full System Builder.

灾害

  • 热带气旋
  • 地震
  • 冰塞洪水
  • 野火
  • Storm surge (在下游引发)
  • Intense rainfall (在下游引发)
  • 河流洪水(在下游引发)
  • Flash flood (set off downstream)
  • 危险海浪(在下游引发)
  • 大范围停电(在下游引发)
  • 大规模流离失所(在下游引发)
  • 沿海洪水(在下游引发)
  • Aftershock sequence (set off downstream)
  • Fault surface rupture (set off downstream)
  • Soil liquefaction (set off downstream)
  • Slope slide (set off downstream)
  • Rockfall (set off downstream)
  • Tsunami (set off downstream)

控制措施

  • NS-0 章程与原则
  • NS-3 风险记录 UNI(语法、旧编码对照、分配机构)
  • NS-9 情境 UNI(部署、实例、计划实例)
  • NS-10 政策和条款(机器可读的义务:定义、约束、评估和执行)
  • NS-11 验证与监测(证据、证明、零信任符合性观测)
  • NS-14 符合性及与外部标准的对照
  • NRS-F3 保险、巨灾风险与保护缺口
  • NRS-H113 危害类别:金融体系脆弱性(NHS-1 soc.financial-system)
  • NRS-U17 宇宙 platform profile: Insurance Nexus
  • NRS-H71 危害类别:深时与宇宙灾难(NHS-1 planet.deep-time)
  • NRS-H65 危害类别:超越行星边界(NHS-1 planet.boundary)
  • NRS-F8 参数化与指数型风险转移

观测

  • OECD Data Explorer (incl. Creditor Reporting System, insurance and pension statistics) (listed for reference)
  • Insurance statistics (listed for reference)
  • USGS earthquake GeoJSON summary feeds (listed for reference)
  • Direct economic loss attributed to disasters in relation to global gross domestic product (GDP)
  • Direct economic loss attributed to disasters in relation to global gross domestic product
  • (a) Number of commercial bank branches per 100,000 adults and (b) number of automated teller machines (ATMs) per 100,000 adults

示例地理范围

  • 西欧:152 个六边形网格
  • 过去半小时降雨率(IMERG),NASA GIBS
  • 今夜夜间灯光与停电(VIIRS 昼夜波段),NASA GIBS
  • 穿透云层的地表水,30 m(OPERA DSWx-S1 雷达),NASA GIBS
  • Carbon monoxide, smoke transport (AIRS), NASA GIBS
10核心问题

What professionals ask.

  • How do changes in life expectancy affect life insurers and annuity providers?
  • How do pandemics affect mortality, morbidity and claims?
  • How do medical advances and rising health costs change health insurance?
  • How do private health and life cover interact with public 社会保护?
  • How should insurers use health data while protecting privacy and fairness?
11部门特征

Where exposure in health and life insurance travels.

The sectors that carry exposure in health and life insurance and how a loss in one passes to the others, across portfolios and public finances.

选择角点 · 悬停连线6 / 15 项关系

签名

卫生及其合作伙伴

卫生部门为基础设施提供运营人力(0.3),为粮食提供农业劳动力(0.3),为水提供公用事业人力(0.2)。

W · E · I · F · H · B

部门
4 共 6
关系
6 共 15
耦合
0.42 占总量份额

当前最强的关系

  • 水 → 粮食 · 灌溉0.8
  • 粮食 → 健康 · 营养0.7
  • 基础设施 → 水 · 管道、水坝和处理设施0.6
  • 水 → 健康 · 饮用水和卫生设施0.7
典型城市区域的教学数值,不是任何地点的测量值。耦合是所涉关系强度的总和,以全部十五种关系的占比表示。
12机制

驱动因素与动态。

Life insurers and pension providers face longevity risk: if people live longer than assumed, annuity payments last longer than priced. Mortality improvements over many decades have made this a central concern. Pandemics produce the opposite shock, raising mortality and morbidity sharply over short periods. Health insurers face rising costs from medical technology, chronic disease and ageing populations.

The boundary between private insurance and public provision varies widely between countries. Where public 系统 are strong, private cover supplements them; where they are weak, private cover may be the main protection for those who can afford it. Gaps in health and life cover leave households exposed to catastrophic expenses. Public health science is studied at Health Nexus at The Global Centre for Risk and Innovation (GCRI).

13风险暴露、损失与资本

What health and life insurance means for exposure, loss and capital.

风险官、监管者或财政部会要求的风险暴露、损失、情景和资本视图,以及它们据以报告的框架。结构遵循监管和精算实务。数值为说明性:绝非价格、评级或建议。

各重现期的风险暴露与损失

How losses from health and life insurance grow with severity, gross and net of reinsurance, against capital.

1/10(10 年一遇)1/50(50 年一遇)1/100(100 年一遇)1/250(250 年一遇)总额扣除再保险后的净额800
重现期年概率总损失净损失净额,资本 = 100
1/10(10 年一遇)0.10141010
1/50(50 年一遇)0.02332121
1/100(100 年一遇)0.01462727
1/250(250 年一遇)0.004683939
年均损失3.12.22.2
一个示例投资组合的示意性损失指数(资本 = 100):保险公司和监管机构所读的超越概率形式。并非任何机构的数据,也非价格或评级。
NGFS 气候情景 · 央行与监管机构绿色金融网络IFRS S2 气候相关披露 · ISSBTCFD 建议 · 金融稳定理事会 TCFD有效管理气候相关金融风险的原则 · 巴塞尔银行监管委员会
14方法与局限

How it is studied.

  1. 01

    Mortality and morbidity analysis

    Experience studies and projection models from 精算数学.

  2. 02

    Longevity modelling

    Stochastic models of mortality improvement, with uncertainty through probability and statistics.

  3. 03

    Pandemic scenarios

    Scenario analysis of mortality, morbidity and asset effects together.

  4. 04

    局限

    Future mortality trends are uncertain, pandemic effects vary by population, and health data raises privacy and fairness questions.

15方法

如何研究,以及方法无法说明的内容。

  1. 精算数学基于进展三角形的损失准备金评估 · 经验费率与可信度在此应用
  2. 概率与统计频率与严重程度建模 · 假设的贝叶斯更新在此应用
  3. 极值理论与尾部风险超额分层的大额损失定价 · 偿付能力资本的尾部度量在此应用
  4. 人工智能与机器学习基于影像的风险暴露数据丰富 · 欺诈与理赔分类 · 定价模型的公平性测试在此应用
16问题

问题与解答。

What is longevity risk?
The risk that people live longer than assumed, so annuity, pension and long-term care obligations cost more than reserved. It affects insurers, pension funds and public pension systems alike.
Why does insured mortality differ from population mortality?
Insured lives are selected by underwriting and tend to differ in income, health and occupation. Experience studies measure the difference rather than assuming it.
Is a pandemic insurable?
Parts are, such as individual life and health claims, but a severe pandemic correlates losses across lines and assets. Many proposals pair private cover with public backstops; designs and their limits differ.
How did recent pandemic experience affect insurers?
It raised mortality and health claims in some lines and disrupted operations, and it prompted wider use of pandemic scenarios.
Does GRA advise on health or life policies?
No. It provides sector-level research only.
Does GRA give advice on this topic?
No. GRA does not underwrite, sell, solicit, negotiate, place or broker insurance, and it does not rate, advise on or arrange transactions. Readiness work is not approval. Its analysis is shared, sector-level understanding.
报告贡献

从本页贡献证据。

报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

全球风险联盟(Global Risks Alliance)Insurance Nexus金融与保险准备度全球部门风险与韧性
Insurance Nexus

向联盟提出风险暴露或资本问题。

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