GRA · Reinsurance and Catastrophe

Spatial financeWhere capital meets hazard, exposure and transition

Actuarial mathematics for reinsurance and catastrophe

Actuarial mathematics turns exposure, loss experience and assumptions into reinsurance prices, reserves and capital. In catastrophe reinsurance it combines model output with experience, applies contract terms and allocates capital across layers.

01تۆمارکردن

Actuarial mathematics for reinsurance and catastrophe on the record.

Method recordSTEM method
  1. ڕێگاActuarial mathematics
  2. Applied inبیمەی ئەتکایی و کارەسات
  3. داتا3 inputs
  4. Canonical pageSTEM Commons
02بەکارهێنان

What actuarial mathematics does here.

Actuarial mathematics applies probability, statistics and financial theory to measure and price contingent risks, particularly in insurance and pensions. It determines reserves and premiums for uncertain future obligations. In insurance and catastrophe, climate and hazards and disaster and crisis, actuarial methods determine whether risks can be insured and at what cost. They help assess accumulation of correlated losses across portfolios and regions. The canonical description is on the STEM Commons.

Layer pricing from model output

Event loss tables are passed through layer terms, including reinstatements, to estimate expected loss and volatility per layer.

Blending experience and exposure rating

Historical losses and modelled losses are blended in proportion to the credibility of the experience for each layer.

Capital allocation

Capital is allocated to treaties by their contribution to tail risk, informing the cost of capital loading.

03Spatial finance

Exposure, hazard and the exceedance curve.

Which places drive loss in a severe year, and how far it reaches into reinsurance. Illustrative design values.

Coastal exposure under cyclone and earthquake zones, beside the loss curve it produces.Illustrative design values, not a model output or a price.
04داتا

What the method consumes.

Datasets and records used by actuarial mathematics on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.

داتاڕۆڵناونیشان
Event loss tablesLayer lossesمۆدێلکراو
Ceded loss historyExperience ratingREPORTED
Contract termsFinancial structureDECLARED
05چاودێری

Tail fit.

The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.

Tail fit

Reinsurance and catastrophe · Actuarial mathematics · Run R-2774

Shape parameter uncertainGRA · Reinsurance and Catastrophe

Return level curve

Method card

ڕێگا
Actuarial mathematics
ڕێباز
peaks over threshold
Threshold
94th percentile
ناونیشان
مۆدێلکراو

Parameters

generalised Pareto fit

Shape ξ0.19−0.010.59heavy tail if above zero
Scale σ1.60.85.2units of the variable
Exceedances49declustered
Tail fit: the screen’s structure, terms and states for Reinsurance and catastrophe.ناو و بەهای نموونەیی؛ دیزاینێکە، نەک تۆمار یان سیستەمی ڕاستەوخۆ.
06پشتڕاستکردنەوە

How results are checked.

Assumptions are tested through experience studies and actual-versus-expected analysis. Independent actuarial review checks methods and results.

بپشکنەHow it is done
Actual versus expectedLayer losses are compared with expectations over time
Sensitivity to model choicePrices are recomputed under alternative models
پێداچوونەوەی سەربەخۆPricing is reviewed against actuarial standards

Historical experience may not reflect emerging or correlated risks. Long-tail liabilities are sensitive to assumptions about future trends.

07Loss model

Loss exceedance, average annual loss and probable maximum loss.

The loss a portfolio in the footprint can expect per year and at the 1 in 100 and 1 in 250 levels that insurers and lenders price, from the same three blocks every catastrophe model 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.

کۆنترۆڵەکان

Typical annual hazard intensity (location)
1.00 intensity index
بڵاوبوونەوەی لێکەوتە توندەکان (پێوەر)
0.80 intensity index
توندییەک کە تێیدا نیوەی بەها لەدەست دەچێت
4.00 intensity index
بڵاوبوونەوەی لاوازی
0.55
بەشی بەها لە شوێنپێی مەترسیدەردا
40%
ستانداردی پاراستن (ماوەی گەڕانەوە)
50 ساڵ

خوێندنەوەکان

تێکڕای زیانی ساڵانە
0.51% of value
زیان لە 1 لە 100 ساڵدا
24.5% of value
زیان لە 1 لە 250 ساڵدا
28.4% of value
توندی لە 1 لە 100 ساڵدا
4.68 intensity index
ژمارە، ڕێگا و سەرچاوەکان
ماوەی گەڕانەوە (ساڵ)Intensity (intensity index)زیان (% ی بەها)
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

ڕێگاکان

  1. مەترسیدەری بەهای زۆرداری Gumbel Gumbel (1958)، Statistics of Extremes، Columbia University Press
  2. ناسکیی لۆگنۆرماڵ (لاوازی) FEMA (2003)، HAZUS-MH Technical Manual
  3. چەمکی ئەگەری تێپەڕبوون و تێکڕای زیانی ساڵانە Grossi و Kunreuther (2005)، Catastrophe Modeling، Springer
  4. کاریگەری بەربەست Di Baldassarre و ئەوانی دیکە (2013)، Socio-hydrology، HESS 17
  5. پەنجەی نادڵنیایی (مۆنتی کارلۆی پارامیتەر) Spiegelhalter, Pearson و Short (2011)، Visualising uncertainty about the future، Science 333
  6. هەستیاریی یەک-یەک (تۆرناد) Saltelli و ئەوانی دیکە (2008)، Global Sensitivity Analysis: The Primer، Wiley

داتا

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:

  • ڕووبارەکان Natural Earth
  • بەرینی شارەکان Natural Earth
  • شارەکان Natural Earth
  • بوومەلەرزەکانی M4.5+، هەفتەی ڕابردوو (USGS) U.S. Geological Survey · register usgs.earthquake.summary-feeds
  • ڕێژەی باران، نیو کاتژمێری ڕابردوو (IMERG) NASA GPM IMERG Early · register nasa.gibs.context-live-layers
  • پێشبینی ڕۆیشتنی ڕووبار، 30 ڕۆژ لەگەڵ مەودا (GloFAS لە ڕێگەی Open-Meteo) Open-Meteo.com (CC BY 4.0), Copernicus GloFAS · register open-meteo.public-pages
  • بەرینی دروستکراو و نیشتەجێبوون، 2010 (HBASE، Landsat) CIESIN/Columbia, NASA SEDAC HBASE · register sedac.context-urban-layers
Loss exceedance, average annual loss and probable maximum loss. Illustrative teaching model: it runs on the values set by the controls, not on measured data. Methods: Gumbel extreme-value hazard (Gumbel (1958), Statistics of Extremes, Columbia University Press); Lognormal fragility (vulnerability) (FEMA (2003), HAZUS-MH Technical Manual); Exceedance-probability curve and average annual loss (Grossi and Kunreuther (2005), Catastrophe Modeling, Springer).

لە ناو شەش کۆڵەکەکەدا، بە سەرپەرشتیی Nexus Consortium

09شبیهسازی دووانە و زنجیرەیی

Trace a shock to the balance sheet.

Assembled from the Nexus Standards area profile بیمە و دووبارەبیمە: the shocks it names, the سیستەمەکان 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.

مەترسیدەرەکان

  • Tropical cyclone
  • بوومەلەرزە
  • Ice-jam flood
  • ئاگری دارستان
  • Storm surge (set off downstream)
  • Intense rainfall (set off downstream)
  • River flood (set off downstream)
  • Flash flood (set off downstream)
  • Dangerous surf (set off downstream)
  • پچڕانی کارەبای فراوان (لە خوارەوە دەستپێدەکات)
  • ئاوارەبوونی بەکۆمەڵ (لە خوارەوە دەستپێدەکات)
  • Coastal flood (set off downstream)
  • 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)

کۆنترۆڵەکان

  • NS-0 دەستوور و بنەماکان
  • NS-3 UNIەکانی تۆماری مەترسی (ڕێزمان، خشتەی گواستنەوەی کۆن، دەسەڵاتی تەرخانکردن)
  • NS-9 UNIی ناوەڕۆکی (دامەزراندنەکان، نموونەکان، نموونەکانی پڕۆگرام)
  • NS-10 Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)
  • NS-11 سەلماندن و چاودێری (بەڵگە، گواهییەکان، چاودێریی گونجان لەگەڵ zero-trust)
  • NS-14 پابەندبوون و هاوتاکردن لەگەڵ ستانداردی دەرەکی
  • NRS-F3 بیمە، مەترسیی کارەسات و کەلێنەکانی پاراستن
  • NRS-H113 خێزانی مەترسیدەر: ناسکیی سیستەمی دارایی (NHS-1 soc.financial-system)
  • NRS-U17 Universe platform profile: Insurance Nexus
  • NRS-H71 خێزانی مەترسیدەر: کارەساتە کەونی و کاتی قووڵەکان (NHS-1 planet.deep-time)
  • NRS-H65 خێزانی مەترسیدەر: پێشێلکردنی سنوورەکانی گۆی زەوی (NHS-1 planet.boundary)
  • NRS-F8 گواستنەوەی مەترسیی پارامێتری و لەسەر بنەمای نیشاندەر

چاودێری

  • 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

جوگرافیای نموونە

  • Western Europe: 152 hexagonal cells
  • ڕێژەی بارین، نیو کاتژمێری ڕابردوو (IMERG)، NASA GIBS
  • ڕووناکییەکانی شەو ئەمشەو، پچڕانی کارەبا (VIIRS Day/Night Band)، NASA GIBS
  • ئاوی ڕووی زەوی لە ڕێگەی هەورەوە، 30 م (ڕادارەی OPERA DSWx-S1)، NASA GIBS
  • Carbon monoxide, smoke transport (AIRS), NASA GIBS
10Stewardship

Who maintains the method.

مەترسی ئەکچوەری و بڕی stewards actuarial mathematics for the Consortium and reviews how it is applied across platforms.

11Exposure, loss and capital

What it means for exposure, loss and capital.

The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.

Exposure and loss at return periods

How losses from actuarial mathematics for reinsurance and catastrophe grow with severity, gross and net of reinsurance, against capital.

1 in 101 in 501 in 1001 in 250grossnet of reinsurance800
Return periodAnnual probabilityGross lossNet lossNet, capital = 100
1 in 100.10141010
1 in 500.02332121
1 in 1000.01462727
1 in 2500.004683939
تێکڕای زیانی ساڵانە3.12.22.2
Illustrative loss index for a example portfolio (capital = 100): the exceedance-probability form insurers and supervisors read. Not data on any institution, not a price or a rating.
NGFS climate scenarios · Network for Greening the Financial SystemIFRS S2 Climate-related Disclosures · ISSBTCFD recommendations · Financial Stability Board TCFDPrinciples for the effective management of climate-related financial risks · Basel Committee on Banking Supervision
12پەیوەست

ئەو شوێنانەی ئەم لاپەڕەیە لە ناو کۆنسۆرتیۆم بۆیان دەبات.

13پرسیارەکان

پرسیار و وەڵام.

What are the limits of actuarial mathematics in this field?
Historical experience may not reflect emerging or correlated risks. Long-tail liabilities are sensitive to assumptions about future trends.
How are results checked?
Assumptions are tested through experience studies and actual-versus-expected analysis. Independent actuarial review checks methods and results.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
ئەو canonical method page lists every platform that applies it.
Reportsبەشداربە

لەم لاپەڕەیەوە بەڵگە پێشکەش بکە.

Reports 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.

Global Risks Allianceبیمەی ئەتکایی و کارەساتئامادەیی دارایی و بیمەڕێگا و تەکنیکی
بیمەی ئەتکایی و کارەسات

Bring an exposure or capital question to the Alliance.

زانیاری و پرسیار ئەمڕۆ کراوەن. پرسیارێک ژمارەی ئاماژەی پێدەدرێت و هەنگاوی دواتر دیاری دەکات؛ داواکاری، پارەدان، تەرخانکردنی کۆمپیوتەر و تۆمارکردن تەنیا کاتێک دەکرێنەوە کە تیم، مەرج و توانای پێداچوونەوەیان هەبێت.

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