Systematically accounting and assessing disaster losses and impacts.

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Presentation transcript:

Systematically accounting and assessing disaster losses and impacts

Loss Accounting Risk Modelling Hazard 1 Hazard 2 Hazard 3 Hazard n Portfolio 1 Assets and people at risk Risk retentionRisk transferRisk reductionOthers… Monitoring and following-up Risk Management Strategy 1 Risk Management Strategy 2 Risk Management Strategy 3 Risk Management Strategy n Portfolio 1 Assets and people at risk Portfolio 1 Assets and people at risk Portfolio 1 Assets and people at risk Tool Kit-Policy options The overall process

National disaster loss databases: Deconstructing disasters EM-DAT: Global level of Observation, National level resolution Datacards Deaths Missing Houses destroyed Houses demaged Victims Affected Losses (runees) Edication center , , , ,902 12,294,923 7,832,749,237 3,703 Fatalities Affected Damage 9,845 12,628, billion US$ State of Orissa dataset

A detailed picture of historical disaster losses and impacts A rich set of indicators Coverage of small, medium and large scale disasters. Disaggregation of data to usable units (District / Block / Building) Collected and validated locally within the country/state

Disaster loss accounting, analysis and reporting

Geographic description and source Impacts (16 quantitatifs indicators and 12 qualitatifs) Possibility to add options or new indicators Typical contents of a DesInventar dataset

Informing risk governance and population

UNISDR support to countries building DLDB 85

European Community Standards

Historical Risk Profiles, Baselines and Monitoring Weather related disasters and CC Relation to probabilistic models Economic impact of past disasters Generation of Empirical Risk Measures Hybrid (Empirical + Analytical) Risk Models Validation and Calibration of models Usage of Disaster Loss Databases

Historical Risk Profiles, Baselines and Monitoring NEPAL: Historical Risk Profile elements

Mortality due to storm surges DRR and CCA: Storm surges in Peru (1970 – 2009) Temporal distribution of storm surge reports Mortality due to storm surges

Housing sector damage/destruction due to extreme precipitation events Mortality due to extreme precipitation events Frequency of extreme precipitation events Weather related disasters in S. America (1970 – 2009)

Historical data used to validate Risk/Hazard maps Comparison of Cyclone/wind reports, deaths, damages and Hazard Atlas - ORISSA Low Hight Number of Reports of Cyclone, Winds Houses Damaged or Destroyed due to Cyclone, Winds Direct Mortality due to Cyclone, Winds

Historical data used to validate Risk/Hazard maps Number of Flood Reports in Orissa Comparison of Flood reports, deaths, damages and Hazard Atlas - ORISSA Low Hight Direct Mortality due to Floods in Orissa Damaged and Destroyed houses due to Floods in Orissa

Probabilistic Risk Assessment Hazard Modeling T = 100 years T =500 years = 0.01 = = Hazard maps for several return periods Hazard Intensity exceedance curve for each computation site T = 1000 years

Loss Exceedance Curves

Risk Pure Premium - RPP Average Annual Loss - AAL Probable Maximum Loss - PML It represents, the annual average of future expected losses, including catastrophic risk (disasters that have not happened yet but may, and eventually will happen). It is computed as the AAL divided by the portfolio exposed elements. It represents, in relative terms, the amount to be paid annually in order to cover future expected losses. PML is the anticipated value of the biggest loss that could result from a disaster caused by a “maximum credible event” Adopting Insurance Industry terms

Extensive Risk Assessment: ‘Empirical ’ Loss Exceedance Curves Empirical loss exceedance curve and historic risk metrics for Colombia as generated by DesInventar

‘Empirical ’ Loss Exceedance Curve for Albania (losses estimated) Empirical loss exceedance curve and historic risk metrics for Albania modelled with DesInventar

Revealing risk: integrating analytical and historical views Frequency 10 times per year Frequency 1 time every 10 years Frequency 1 time every 10’000 years 1 million USD 1 billion USD Extensive Intensive High frequency Low severity Low frequency High severity

Extensive Intensive The risk we will have “to live with…” 4 Residual risk 4 High frequency Low severity Low frequency High severity 1 Risk reduction 1 Corrective: Building retrofitting, mitigation strategies. 2 Risk retention 2 Prospective: Financial reserves, public investment, laws and regulations. Compensatory: Insurance, contingency funds. 3 Risk transfer 3 Risk Strategies

Risk retention and transfer structure Reserve fund Contingent loan Insurance and reinsurance Long term actions (Cat bond, taxes, long term loans, etc) National government IDB / World Bank Unprotected RETENTION TRANSFER Lower limit Upper limit AAL PML Total exposed value Deductible

#gar15 Thank you