Portfolio management system with gradient display features

• US 20070203759A1
• Filed: 02/26/2007
• Published: 08/30/2007
• Est. Priority Date: 02/27/2006
• Status: Abandoned Application

• Current Assignee: Guy Carpenter & Company LLC (Marsh & McLennan Cos., Inc.)
• Original Assignee: Guy Carpenter & Company LLC (Marsh & McLennan Cos., Inc.)
• Inventors: Soh, Elizabeth, Mathai, Shajy, Belubekian, Maya E.
• Application Number:
  US11/710,874
• Publication Number:
  US 20070203759A1
• Time in Patent Office: Days
• US Class Current: 705/4
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

The present invention provides a tool to depict the relative impact to the losses of a insurer'"'"'s portfolio from catastrophic events, such as a hurricanes or earthquakes, at a specific risk level by geographic area using a grid level database and a spatial database to generate maps. The maps developed using this tool help visualize the potentially dangerous areas for writing new business and/or identify preferential places for growth. The tool also creates a list of zip codes with incremental losses at a particular risk level representing the relative attractiveness of writing new policies (or eliminating existing policies) in one zip code versus another. The spatial database provides rich spatial geometry features in the form of raster images available in the spatial database and the invention provides the corresponding spatial algebra to create relativity maps with gradient features and zip code loss information.

Claims

1. A data analysis system comprising:

a grid level exposure database for storing exposure data including a uniform grid of equal exposures;

a grid level loss database for storing pre-modeled insurance portfolio loss data for the uniform grid of equal exposures to catastrophic events; and

a geo-spatial database for receiving the loss data in raster format and user input in order to generate maps that include gradient features depicting contribution to loss in a risk managed layer (RML).

2. The system of claim 1 wherein the geo-spatial database includes catastrophic loss data that contribute to tail loss with respect to the insurance portfolio data and the maps being generated to provide gradient features that reflect the catastrophic loss data with respect to insured property values.

3. The system of claim 1 wherein the loss data in raster format is spatial data and raster algebra is performed on the spatial data to calculate contribution to loss in the RML.

4. The system of claim 1 wherein the geo-spatial database provides the uniform grids by plotting pixilated points correlated to the insurance portfolio data and providing equal exposures by adding the cost of a wood frame building in each grid point from the grid level exposure database.

5. The system of claim 1 further comprising a geo-spatial application for scripting the insurance portfolio data and generating maps from raster data.

6. The system of claim 1 wherein the gradient features comprise various graphical indicia depicted on a map and each indicia representative of different data points.

7. A data analysis system comprising:

a processor that calculates spatial data pertaining to events that contribute to tail loss with respect to the insurance portfolio data and the spatial data in raster format where raster algebra is performed on the spatial data to calculate contribution to loss in a risk managed layer (RML); and

an end user device to display maps that include gradient features identifying the contribution to loss in RML.

8. The system of claim 7 wherein the insurance portfolio includes catastrophic loss data and the maps being generated provide gradient features that reflect the catastrophic loss data.

9. The system of claim 7 wherein the processor includes a spatial database having a geo-spatial software in order to plot pixilated points correlated to the insurance portfolio data.

10. The system of claim 7 wherein the processor includes a geo-spatial application for scripting the insurance portfolio data.

11. The system of claim 7 wherein the gradient features comprise various graphical indicia depicted on a map and each indicia representative of different data points.

12. A method of conducting data analysis comprising the steps of:

modeling incremental tail loss at pixilated points; and

developing a grid of the pixilated points representative of specific events across a wide geographic area correlated to a risk managed layer (RML).

13. The method of claim 12 further comprising the step of:

selecting events in the RML from an exceedance probability curve modeled from insurance portfolio data.

14. The method of claim 12 further comprising the step of:

developing a map to identify preferential places for insurance growth or loss prevention.

15. The method of claim 12 further comprising the step of:

developing a map including a zip code index that compares the attractiveness of writing business in one zip code versus another zip code.

16. The method of claim 12 wherein the RML includes the same-value and same-construction exposures located in the nodes or pixilated points of an equally-spaced grid.

17. The method of claim 12 further comprising the step of modeling grid level tail losses for an existing insurance portfolio in order to evaluate the sensitivity of each geographic area to the increase in losses in the RML.

18. The method of claim 12 further comprising the step of calculating the tail loss for each location in the grid.

19. The method of claim 18 further comprising the step of determining tail loss contribution in order to provide a spatial pattern that will be unique to each particular insurer based on the individual insurer'"'"'s portfolio, which drives the losses in the RML.

20. The method of claim 19 further comprising the step of approximating the changes to losses in RML that occur by addition of incremental exposure to the losses of the incremental portfolio.

21. The method of claim 19 further comprising the step of modeling incremental exposure by uniformly distributing pixilated points geographically, so that all areas of interest are accessed in terms of their relative impact on the losses to the RML.

22. The method of claim 19 further comprising the step of obtaining results for the grid losses at each location level and using the RML events for each insurer'"'"'s analysis to calculate a contribution to the insurer'"'"'s RML losses.

23. The method of claim 19 further comprising the step of overlaying maps having expected loss and concentration of policy data and generating an overall map depicting gradient features that are representative of catastrophe losses by using different graphical indicia.

24. The method of claim 19 wherein the tail loss is equal to the RML.

25. The method of claim 12 further comprising the step of selecting events from an exceedance probability curve where the RML is unbounded with respect to the return period.

26. The method of claim 12 further comprising the step of selecting events from an exceedance probability curve where each loss on the EP curve is paired with a simulation event.

27. A system for displaying geographic and insurance portfolio data comprising:

an end user device, including a computer readable signal-bearing medium, such medium having a circuit for receiving insurance portfolio data and data parameters input by a user of the end user device and the data parameters for calculating a spatial distribution of events that contribute to tail loss with respect to the insurance portfolio data; and

map data received by the end user device, the map data depicting the spatial distribution using gradient features.

28. The system of claim 27 wherein the end user device is a computer connected to a network and transmitting and receiving insurance portfolio data via the internet and displaying the map data, including pixilated points representative of specific events for a RML to provide an estimate of incremental tail loss for each pixilated point.

29. The system of claim 27 wherein the end user device is connected to the internet and is capable of receiving email and the email including data representative of events for a RML for providing an estimate of incremental tail loss with respect to particular geographic region.