Technical Pricing API

Estimate Premium is a service that returns AAL (average annual loss) and marginal metrics. The service is provided through modules, each representative of a geography and peril such as hurricane, storm surge, earthquake, severe convective storm, or wildfire (for example).

Each module is provided with certain terms and restrictions that, in some cases may include extended contractual obligations, audit of usage, and in some cases fees.

Estimate Premium is most reliable when the client provides pre-validated latitude and longitude for a location. If you’re unable to provide latitude/longitude values, please reference our Geocoding service section.

AVAILABLE RESPONSE METRICS

• Gross AAL = Net Pre Cat AAL. The current release of AAL does not contemplate Per Risk or inuring structures as they would within the catastrophe model.

• Standard Deviation Gross AAL = Standard Deviation Net Pre Cat AAL. The current release of Standard Deviation AAL does not contemplate Per Risk or inuring structures as they would within the catastrophe model.

• PML = RML. RML is the Risk Managed Layer and is defined as the "conditional expected loss giving an event has loss within a layer." Note that the loss has to be bigger than the lower bound, AND smaller than the upper bound. Typically a layer is defined by the lower and upper return periods based on an EP curve. For example, RML 90-110, RML 225-275, etc. The main purpose of using RML in portfolio management is a way to manage PML around a stable set of equally sized events in the PML calculation. Since the calculation of PML is nonlinear, it is difficult to directly manage it, for example in portfolio optimization. RML, as defined above, can be easily decomposed (also called co-measure) across the portfolio. If we choose a layer close to the PML point we are interested – for example the “layer” defined by the 90 to 110 loss for 100 year return period, the RML effectively becomes a stable approximate of the PML 100. Again, for example if we managed to reduce the RML we can effectively reduce the PML. In other words, RML contains the important event set that contribute around PML value. The RML concept is explored and explained in depth by John Major in the paper “Gradients of Risk Measures: Theory and Application to Catastrophe Risk Management and Reinsurance Pricing, 2004”

• Excess AAL – It is similar to RML in that RML is conditioned from XSAAL by the probability of a loss within the layer.

• Ceded AAL = Layer Recovery. The AAL due an excess layer. To allocate the reinsurance premium back to any segment of an insurance portfolio, we separate the ceded loss and the reinsurance margin such that reinsurance margin = deposit premium – layer recovery. Ceded loss is typically allocated pro-rata to the gross mean loss.

• Reinsurance Margin = Deposit Premium – Layer Recovery. The standard base for allocation of Deposit Premium (and therefore Reinsurance Margin) is pro rata to the variance of the layer ceded loss. The layer ceded variance is decomposed as the sum of covariance of layer ceded loss with segment ceded loss – hence the “covariance” or marginal segment contribution to ceded layer variance.

• Reinsurance Premium = Deposit Premium. The Deposit Premium is allocated in line with the Reinsurance Margin and the equivalent of Layer Recovery (as Ceded AAL) + Reinsurance Margin.

• Cost of Catastrophe Capital = Capital Cost – The “cost” assigned to some portion or the entire retained loss net post cat. It is allocated by CoTVaR of net post cat losses. CoTVaR can be represented as RML with the upper layer bound as unlimited. In an "aggregatebased" case the CoTVaR is calculated based on the annual loss. An aggregate based calculation can only be accomplished when a MetaRisk timeline or AIR year loss table is used as the baseline.

• Net AAL = Net Post Cat AAL. This is the company retained loss or simply net loss. It is allocated pro rata to gross mean loss. This is similar to the layer ceded loss allocation.

• FHCF Premium – Florida Hurricane Cat Fund Premium and is calculated based on the territory, coverage, deductible, class of business and the rates from Paragon and outlined in a separate FHCF Premium Estimate document including assumptions based on catastrophe model inputs.

• Expense Ratio – Client provided factors

• LAE – Client provided factors

The Baseline in the response gives the reference portfolio value(s) and Marginal gives the prospective location level value(s.)

Baseline = In Force Portfolio.

Marginal = Prospective Account.

Generalized Module Request Parameters

List of generalized input parameters and module specific codes for primary and secondary risk characteristics, including ranges of values are provided on the Lookup Values tab.

API REFERENCE - DETAILED

The GC Carpenter API includes an API Explorer, a tool that helps you explore and debug GC Carpenter API endpoints. More detailed information on an endpoint is displayed in the API Explorer.

EstimatePremium

Detailed information on Base URL, Action, Headers, and Body Parameters is displayed in the API Explorer.

BaseURL: [Base URL provided by GC]

Action: POST

Headers:

• Content-Type: application/json

• Authorization: Bearer [access_token]

Body Parameters:

• Detailed information on Body Parameters is displayed in the API Explorer.

The above resources should return one of the following HTTP response codes:

Responses:

ERROR SUMMARY

The service returns a Fault Exception object for all errors. The Fault Exception object has a Fault Code, Description and a Fault Type that indicates if the fault was generated due to client (or sender) entry or a server (or receiver) fault.

The error codes mentioned below are some of the codes that can be used by the client applications to take appropriate actions