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Data Selection

Please select your preferred settings

You may either select preloaded archetype data which contains some example risk data or choose to import your own data. Note: All preloaded archetype data is in USD. Any user data should be converted to USD before uploading into the Tool.


Strategy Design


Recap of risk data


Instrument details


Economic Assumptions

The Manual Override assumptions let you set the economic assumptions used for the main analysis. The alternative Sensitivity Assumptions can be used if you want additional outputs showing the impact of alternative assumptions. The indicative assumptions are taken from the World Bank framework paper. The user will obtain results more specific to their circumstances if the assumptions are manually overridden with relevant economic assumptions. To enter assumptions please highlight and then type to replace with the desired input. Deleting assumptions will return the input to default indicative assumption.

Sensitivity calculations will be calculated automatically if any of the sensitivity assumptions differ from the equivalent initial assumption or manual override entered.

Please refer to the user guide for details of each assumption.

* Economic assumptions labelled with an asterisk feed into the output of Exhibit 1s (on the Output section) in the case that the sensitivity assumption differs from the initial assumption.


General Assumptions

Indicative Assumption

Manual Override

Sensitivity Assumption

Marginal interest rate on sovereign debt (%) *

Discount rate (%) *

Reserve Fund Assumptions

Investment return on unspent reserves (%) *

Line of Contingent Credit Assumptions

Interest rate on contingent credit (%) *

Arrangement fee for contingent credit (%)

Treatment of outstanding concessionary loans (0 or 1 only)

Repayment term of contingent credit (years)

Emergency Ex-Post Budget Reallocation Assumptions

Social rate of return on projects not funded due to reallocation of budgets (%) *

Ex-post Sovereign Borrowing Assumptions

Marginal interest rate on ex-post borrowing (%) *

Repayment term of ex-post borrowing (years)

Annual effective increase in cost financing through ex-post borrowing

Delay period in financing through ex-post borrowing (months)

Insurance Assumptions

Insurance pricing multiple

Subsidised Insurance Assumptions

Insurance pricing multiple


Outputs


These outputs focus on comparing the funding gap under different strategies. These identify when the chosen financing instruments will be exhausted and hence it is assumed that ex-post sovereign borrowing has to be relied upon.


The level of funding available for each of the chosen DRF strategies

This graph shows the defined layer strategy for the selected strategies. The strategies correspond to those selected on the 'Strategy Design' section.

The chances of each instrument being fully drawn over the next year

This graph demonstrates the probability that the full amount available from each funding instrument is exhausted within a given year. For example if reserve fund has a corresponding percentage of 30% then the entire reserve fund is expected to be fully used in 30% of scenarios. For each strategy, it shows the instruments in the order they are selected, so funding instruments used earlier will exhaust sooner, with a greater probability. The probability of insurance being exhausted is directly linked to the maximum loss covered by the insurance.

Ex-post sovereign borrowing is never exhausted due to the simplifying assumption that it is unlimited. A more realistic assumption for the limit on ex-post sovereign borrowing could be derived from detailed discussions with a particular government.

The funding available from limited risk retention instruments for each DRF strategy based on different magnitudes of loss

This graph shows the respective available funding within limited* risk retention instruments for the chosen strategies as the size of loss increases. The point at which the funding value crosses the x axis corresponds to the total level of funding available for the selected strategy. A negative funding value indicates the funding available is not sufficient to meet the cost of the disaster. It is assumed the modelled country will need to utilise ex-post sovereign borrowing to fill this gap in funding. If the funding value does not cross the x axis then the risk retention instruments are always sufficient to meet the size of the loss shown.

If you have two strategies which overlap only a single line will be shown. Strategies can be hidden by clicking on them in the legend.

*Excludes Ex-post sovereign borrowing

These outputs focus on illustrating the likelihood of different losses and how the losses under different scenarios will be funded.


The expected magnitude of loss at different return periods over the next year

This graph shows the expected magnitude of loss at different return periods. For example a 1 in 10 loss is the size of loss which is expected once in every 10 years. Consequently, a 1 in 5 year loss will have a smaller loss than a 1 in 10 year loss. The average shown in this exhibit is the long term average.

The breakdown of instrument use to fund a user selected loss (return period) over the next year under each DRF strategy

This graph shows a breakdown by instrument type of the magnitude of loss for a given return period based on the user's entered DRF strategies. Please note this graph shows the size of loss covered by each instrument but not necessarily in the order they will be used. Exhibit 2c, on the next tab, shows the same information as displayed in this exhibit but defines the size of loss in terms of the probability of the loss occurring, rather than in terms of return periods. This is designed to help the user to understand how return periods and loss probabilities relate to one another. For example a loss which has a 20% probability of occurring is equivalent to a loss with 1 in 5 year return period. Note: Average scenario approximated by closest simulation event.

The breakdown of instrument use to fund a user selected loss (probability) over the next year under each DRF strategy

This graph shows a breakdown by instrument type of the magnitude of loss for a given probability based on the user's entered DRF strategies. Please note this graph shows the size of loss covered by each instrument but not necessarily in the order they will be used. Exhibit 2b, in the previous tab, shows the same information as displayed in this exhibit but defines the size of loss in terms of the return period in which the corresponding loss size would be expected to occur. This is designed to help the user to understand how return periods and loss probabilities relate to one another. For example a loss which has a 20% probability of occurring is equivalent to a loss with 1 in 5 year return period.

How layers of DRF instruments could fund the range of potential losses over the next year



These outputs focus on the opportunity costs associated with funding losses with different strategies. They can therefore be used to compare the economic efficiency of different strategies (given a set of assumptions).


The potential opportunity cost of funding losses for different magnitudes of loss over the next year under each DRF strategy

This graph shows the expected cost of funding losses for different magnitudes associated with each of the defined layer strategies. The different magnitudes of loss are represented as return periods. For example a 1 in 10 loss is the size of loss which is expected once in every 10 years. Consequently, a 1 in 5 year loss will have a smaller cost than a 1 in 10 year loss. The average shown in this exhibit is the long term average.

Percentage opportunity cost saving for different magnitudes of loss over the next year of DRF Strategies B and C relative to the Base Strategy



The above exhibit shows the percentage savings of Strategies B and/or C relative to the Base Strategy. For example an indicator showing a 5% saving for a 1 in 5 year event means that strategy is 5% cheaper than the Base Strategy at funding the equivalent likelihood of loss. The overall likelihood that Strategies B/C are cheaper than the Base Strategy are shown beneath the graph. Where the cost of the Base Strategy is 0, a comparison is not useful and therefore not shown. The average shown in this exhibit is the long term average. The user is able to use Exhibit 3d for information about events at other return periods / probabilities.

The potential opportunity cost of funding user selected losses (probabilities) over the next year under each DRF strategy

This graph allows a user to classify 'Severe' and 'Extreme' aggregate losses by their probability of occurrence. It then shows the expected cost within each strategy. The user can enter their chosen probabilities to define each annual aggregate loss. For example, one possible combination would be to define a severe loss as 20% (equivalent to a 1 in 5 year return period) and an extreme loss as 10% (equivalent to a 1 in 10 year return period). The probabilities selected should be specific to the user's own requirements. The average shown in this exhibit is the long term average.

Percentage opportunity cost saving for different user selected losses (probabilities) over the next year of DRF Strategies B and C relative to the Base Strategy



The above exhibit shows the percentage savings of Strategies B and/or C relative to the Base Strategy for different severities of annual aggregate losses. The user can enter their chosen probabilities to define each aggregate loss. For example, one possible combination would be to define a severe loss as 20% (equivalent to a 1 in 5 year return period) and an extreme loss as 10% (equivalent to a 1 in 10 year return period). The probabilities selected should be specific to the user's own requirements. An indicator showing a 5% saving for a severe loss means that strategy is 5% cheaper than the Base Strategy at funding the equivalent likelihood of loss. The overall likelihood that Strategies B/C are cheaper than the Base Strategy are shown beneath the graph. Where the cost of the Base Strategy is 0, a comparison is not useful and therefore not shown.

The potential opportunity cost of funding a user selected loss (return period) over the next year under each DRF strategy split by instrument type

This graph shows a breakdown of costs incurred by instrument type for a given return period based on the user's entered DRF strategies. Please note this graph shows the amount of cost of each instrument but not necessarily the order they will be used in. The user can choose which return period to display the costs of. For example a loss which has a 20% probability of occurring is equivalent to a loss with 1 in 5 year return period. This exhibit uses the simulated long term average for the average return period. This may differ slightly to the average value shown in Exhibit 2a, however any difference is expected to be negligible.


These outputs focus on illustrating the impact of risk transfer and how the pay-outs of insurance will depend on whether the losses experienced are large or small.


The net profit and cost from insurance

The above graph shows net profit and cost for insurance (combined insurance and subsidised insurance) for each strategy - i.e. the total claim pay-outs (if any) minus the premium payments. It is intended to illustrate that insurance is a net cost for highly frequent annual aggregate losses, but becomes valuable for lower frequent sized annual aggregate losses. It also illustrates that for some strategies insurance might be a greater cost at high probabilities, but then typically becomes 'profitable' more 'quickly'.

The breakdown of insurance pay-outs for user selected losses (probabilities) over the next year under each DRF strategy

Associated probability of annual aggregate loss


This graph allows a user to classify 'Severe' and 'Extreme' magnitudes of loss by their probability of occurrence. The user can enter their chosen probabilities to define each magnitude. For example, one possible combination would be to define a severe magnitude as 20% (equivalent to a 1 in 5 year return period) and an extreme magnitude as 10% (equivalent to a 1 in 10 year return period). The probabilities selected should be specific to the user's own requirements. If the user selects a probability with an associated loss less than the attachment point no pay-out will be shown. If the user selects a probability with an associated loss greater than the exhaustion point the maximum pay-out will be shown. The graph shows the premium for the selected insurance layer entered by the user on the 'Strategy Design' section and the associated pay-outs that would occur if the defined severity of losses happened. For example the average pay-out shows the average annual pay-out an insurer would expect to make, not the pay-out an insurer would make based on the average annual loss. The premium minus the average pay-out is the effective cost of purchasing the insurance. Insurance is cost effective to the user at the probability of loss sizes where the pay-out is greater than the premium. The table directly above this text shows the probabilities associated with the attachment and exhaustion points for each strategy.


These outputs illustrate how the impact of alternative assumptions may impact on what is seen as the best strategy.


The effect of a change in the initial assumptions on the expected cost of funding losses under the Base Strategy

This graph shows the impact on the expected cost of funding losses under the Base Strategy due to a change to the initial assumptions outlined in the Sensitivity Analysis control panel. The change is the difference in the opportunity costs under the two sets of assumptions. Each bar represents the absolute and percentage change due to the change in the corresponding economic assumption only, with all other economic assumptions being kept at their value in the initial assumptions. The difference in the assumption entered by the user is shown on the respective bar. Economic assumptions which have no impact on any funding instruments will have zero impact on the cost of funding losses under the Base Strategy. It is important to note that the combined impact of 2 or more assumptions may not be equal to the sum of the individual changes due to the changes offsetting or concentrating a change in the expected cost. The average shown in this exhibit is the long term average.

The expected cost of funding losses for different magnitude of loss under each DRF strategy

This graph shows the expected cost of funding losses for different magnitudes associated with each of the defined layer strategies, under both the initial assumptions and sensitivity assumptions. The average shown in this exhibit is the long term average.

Percentage opportunity cost saving for different sensitivity assumptions relative to initial assumptions under each DRF strategy


The above exhibit shows the percentage savings for the chosen strategy using the sensitivity assumptions rather than the initial assumptions. For example an indicator showing a 2% saving for a 1 in 5 year event means that using the sensitivity assumptions for the same strategy is 2% cheaper than using the initial assumptions at funding the equivalent likelihood of loss. This exhibit uses the long term average. Where the cost of the Base Strategy is 0, a comparison is not useful and therefore not shown.


All values are in million USD

Base Main

Strat B Main

Strat C Main

Base Sensitivity

Strat B Sensitivity

Strat C Sensitivity

Alt i Sensitivity

Alt d Sensitivity

Alt r Sensitivity

Alt c Sensitivity

Alt h Sensitivity

Alt e Sensitivity


About

Overview


This Tool has been developed to support World Bank client countries better understand the benefits of ex-ante disaster risk financing instruments. It is an educational tool which aims to increase the user's understanding of different financial instruments that are available to them when managing the risk associated with disasters.

This Tool can be used with either one of the six preloaded data archetypes or manually inputted data which may be imported loss scenarios from the Financial Risk Assessment Tool. This Tool depends on a number of assumptions of the costs of different financial instruments, both explicit (which can be altered by the user) and implicit. It also depends on the quality of the data which is input. Therefore, the output from this Tool remains only an indication of the costs associated with a disaster risk finance strategy, and the total fiscal cost may differ significantly from the Tool's output.

The Tool is designed to work on a laptop or desktop PC with the web browser maximised, you may not be able to use the Tool on smaller screens. Please read the user guides before use.

Authorship


This Tool was developed by the Disaster Risk Financing and Insurance Program (DRFIP) which is housed in the Finance, Competitiveness and Innovation Global Practice of the World Bank Group. It has been developed with financial support from the European Union.

Disclaimer


This Tool has been developed to support World Bank client countries better understand the benefits of ex-ante disaster risk financing instruments. Information in the Tool is provided for educational purposes only and does not constitute legal or scientific advice or service. The World Bank makes no warranties or representations, express or implied as to the accuracy or reliability of the Tool or the data contained therein. Users of the Tool should seek qualified expert advice for specific diagnostic and analysis of a particular project. Any use thereof or reliance thereon is at the sole and independent discretion and responsibility of the user. No conclusions or inferences drawn from the Tool should be attributed to the World Bank, its Board of Executive Directors, its management, or any of its member countries. This Tool does not imply any judgement or endorsement on the part of the World Bank. In no event will the World Bank be liable for any form of damage arising from the application or misapplication of the tool, or any other associated materials.

User guide links

Please find links to the model documentation:


Link to user guide

This comprises a quick start guide as well as a more detailed reference guide explaining the functionality of the model.