Spatial financeWhere capital meets hazard, exposure and transition
Structural and earthquake engineering for reinsurance and catastrophe
Structural engineering explains how buildings and infrastructure respond to wind,ground shaking, flood and fire. In catastrophe reinsurance it supplies the vulnerability functions that converthazard intensityinto damage and loss.
What structural and earthquake engineering does here.
Structural andearthquakeengineering designs buildings, bridges and other structures to carry loads safely, including those from earthquakes, wind and floods. It determines how much damage the built environment suffers when hazards occur. In insurance and catastrophe, climate and hazards and disaster and crisis, structural engineering supplies vulnerability functions for loss models and guides retrofit priorities. It linkshazard intensityto disruption of housing, services and supply chains. The canonical description is onthe STEM Commons.
Vulnerability by construction class
Damage functions are developed by construction type, height, age and code era from engineering analysis and claims.
Building code effectiveness
Loss differences between buildings of different code eras are studied to show how much stronger standards reduce damage.
Post-event damage surveys
Field surveys after events record damage patterns by building type, which are then used to recalibrate vulnerability functions.
03Spatial finance
Assets on the grid, and the portfolio they make.
Where a portfolio’s assets sit, and how much of its value is most exposed. Hypothetical assets, not an assessment.
Sixteen assets at real towns, and the share of portfolio value in the most exposed places.Hypothetical assets and design scores, not advice.
04Dane
What the method consumes.
Datasets and records used by structural andearthquakeengineering on this platform, with the role each plays and the label its values carry. Sources are listed inthe source register.
Dane
Rol
Nîşan
Claims by construction type
Calibration
REPORTED
Engineering test results
Component behaviour
ÇAVDÊRÎKIRÎ
Post-event surveys
Damage patterns
ÇAVDÊRÎKIRÎ
05Çavdêrî bike
Fragility analysis.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Fragility analysis
Reinsurance and catastrophe · Structural and earthquake · Run R-8382
Test campaignGRA · Reinsurance and Catastrophe
Damage states
Slight
0.18
0.6
Cosmetic
Navîn
0.32
0.7
Repairable
Extensive
0.63
0.7
Major
Temam
0.9
0.7
Replace
Method card
Rêbaz
Endezyariya avahî û erdhejê
Standard
lognormal fragility
Nirxandkar
serbixwe
Nîşan
MODELKIRÎ
Fragility curves
Fragility analysis: the screen’s structure, terms and states for Reinsurance and catastrophe.Nav û nirxên nimûneyî; sêwiran e, ne qeyd an pergaleke zindî ye.
06Erêkirin
How results are checked.
Designs are checked against codes, laboratory and shake-table tests, and observed performance after events. Peer review is used for unusual structures.
Kontrol bikin
How it is done
Claims back-testing
Functions reproduce observed damage ratios
Secondary modifiers
The effect of roof, opening and foundation features is documented
Regional applicability
Functions are checked for the building stock where applied
Existing building stock is often poorly documented. Interaction of multiple hazards and degradation over time is incompletely represented.
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 everycatastrophe modeluses. 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.
Qada îhtîmala derbasbûnê û windahiya salane ya navînî Grossi and Kunreuther (2005), Catastrophe Modeling, Springer
Bandora bendavê Di Baldassarre and others (2013), Socio-hydrology, HESS 17
Pankeya nediyarîyê (Monte Carlo ya parametreyan) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
Hesasiyeta yek-yek (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Dane
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:
Rêjeya baranê, nîv saeta dawîn (IMERG) NASA GPM IMERG Early · register nasa.gibs.context-live-layers
Pêşbînî: herikîna çemê, 30 roj bi navber (GloFAS bi riya Open-Meteo) Open-Meteo.com (CC BY 4.0), Copernicus GloFAS · register open-meteo.public-pages
Berfirehiya avakirî û niştecihbûnê, 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).
Li seranserê şeş stûnan, bi pêşengiya Nexus Consortium
Assembled from theNexus Standardsarea profileSîgorta û ji nû ve sîgorta: the shocks it names, thepergalanand 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 fullSystem Builder.
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 structural and earthquake engineering for reinsurance and catastrophe grow with severity, gross and net of reinsurance, against capital.
Return period
Annual probability
Gross loss
Net loss
Net, capital = 100
1 in 10
0.10
14
10
10
1 in 50
0.02
33
21
21
1 in 100
0.01
46
27
27
1 in 250
0.004
68
39
39
Windahiya salane ya navînî
3.1
2.2
2.2
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
12Girêdayî
Ev rûpel li ser Konsorsiyûmê te ber bi kû ve dibe.
What are the limits of structural and earthquake engineering in this field?
Existing building stock is often poorly documented. Interaction of multiple hazards and degradation over time is incompletely represented.
How are results checked?
Designs are checked against codes, laboratory and shake-table tests, and observed performance after events. Peer review is used for unusual structures.
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.
rêzeya Pergalên Stratejîkis 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.
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