Granted Patent B2

US 9,613,331 · App. 14/060,242 · Granted Apr 4, 2017

Abstract

Claims (44)

1. A method for outputting a rating based upon an estimate of an environmental factor of an entity when data relating to the environmental factor for the entity is incomplete, the method being implemented in a machine having a processor and a memory, the method comprising:

receiving at the machine data relating to an industry, sector, or sub-sector to which the entity belongs;

determining by the processor one or more circumstances in which environmental factor data concerning the entity is at least one of missing and incomplete;

based on the determining, applying the data to a plurality of estimation modules to obtain the estimate of the environmental factor of the entity in the absence of the missing or incomplete data, wherein each estimation module of the plurality of estimation modules encodes a respective heuristic model algorithm;

computing, by each estimation module of the plurality of estimation modules, using the respective heuristic model algorithm, a different component of the estimate of the environmental factor of the entity;

applying by the processor the estimate as a factor in a formula to generate the rating for the entity; and

outputting the rating from the machine.

2. A method as in claim 1 , further comprising making the estimate available to a user through a user interface.

3. A method as in claim 2 , wherein the making step is selectively enabled based upon operation of a data-fault module executing in the machine, the data-fault module being operative to configure the processor to enable the making step if the entity is determined to have missing or incomplete data concerning the environmental factor.

4. A method as in claim 1 , further comprising a threshold step of determining, via a data-fault module executing in the machine, whether the entity has missing or incomplete data concerning the environmental factor, and performing the remaining steps if the entity is determined to have missing or incomplete data concerning the environmental factor.

5. A method as in claim 1 , wherein the step of computing, by each estimation module of the plurality of estimation modules, the different component of the estimate of the environmental factor of the entity is performed in parallel.

6. A method as in claim 1 , further comprising combining the results of the plurality of estimation modules.

7. A method as in claim 6 , wherein the combining the results of the plurality of estimation modules includes computing a simple average that is provided as the environmental factor in the form of a single value.

8. A method as in claim 1 , wherein the respective heuristic model algorithms have a hierarchical accuracy order, and wherein the computing, by each estimation module of the plurality of estimation modules, of the different component of the estimate is performed in accordance with the hierarchical accuracy order.

9. A method as in claim 1 , including the additional steps of:

computing an error associated with each respective heuristic model algorithm by applying each respective heuristic model algorithm to at least one additional entity having a known value concerning the environmental factor; and

calculating a difference between the estimate for the additional entity concerning the environmental factor and the known value.

10. A method as in claim 9 , including the additional step of correcting for any calculated difference concerning the additional entity so as to account for such error in the estimate for the entity.

11. A method as in claim 1 , including the additional steps of:

providing a user interface to the machine; and

permitting users, through the user-interface, to customize at least one of the respective heuristic model algorithms.

12. A method as in claim 1 , wherein the entity is selected from the group consisting essentially of a company, a corporation, a limited liability company, a limited liability corporation, a partnership, a limited liability partnership, a self-regulated organization, and a joint venture.

13. A method for outputting an estimate of an environmental factor of an entity when data relating to the environmental factor for the entity is incomplete, the method being implemented in a machine having a processor and a memory, the method comprising:

receiving at the machine data relating to an industry, sector, or sub-sector to which the entity belongs;

determining by the processor one or more circumstances in which environmental factor data concerning the entity is at least one of missing and incomplete;

based on the determining, applying the data to a plurality of estimation modules, wherein each estimation module of the plurality of estimation modules encodes a respective heuristic model algorithm;

computing, by each estimation module of the plurality of estimation modules, using the respective heuristic model algorithm, a different component of the estimate of the environmental factor of the entity;

estimating by the processor the environmental factor of the entity based on the different components computed by the plurality of estimation modules; and

outputting the estimate from the machine.

14. A method as in claim 13 , further comprising making the estimate available to a user through a user interface.

15. A method as in claim 14 , wherein the making step is selectively enabled based upon operation of a data-fault module executing in the machine, the data-fault module being operative to configure the processor to enable the making step if the entity is determined to have missing or incomplete data concerning the environmental factor.

16. A method as in claim 13 , further comprising a threshold step of determining, via a data-fault module executing in the machine, whether the entity has missing or incomplete data concerning the environmental factor, and performing the remaining steps if the entity is determined to have missing or incomplete data concerning the environmental factor.

17. A method as in claim 13 , wherein the step of computing, by each estimation module of the plurality of estimation modules, the different component of the estimate of the environmental factor of the entity is performed in parallel.

18. A method as in claim 13 , wherein the estimating the environmental factor data includes combining the results of the plurality of estimation modules.

19. A method as in claim 18 , wherein the combining the results of the plurality of estimation modules includes computing a simple average that is provided as the environmental factor in the form of a single value.

20. A method as in claim 13 , wherein the respective heuristic model algorithms have a hierarchical accuracy order, and wherein the computing, by each estimation module of the plurality of estimation modules, the different component of the estimate is performed in accordance with the hierarchical accuracy order.

21. A method as in claim 13 , including the additional steps of:

computing an error associated with each respective heuristic model algorithm by applying each respective heuristic model algorithm to at least one additional entity having a known value concerning the environmental factor; and

calculating a difference between the estimate for the additional entity concerning the environmental factor and the known value.

22. A method as in claim 21 , including the additional step of correcting for any calculated difference concerning the additional entity so as to account for such error in the estimate for the entity.

23. A method as in claim 13 , including the additional steps of:

providing a user interface to the machine; and

permitting users, through the user-interface, to customize at least one of the respective heuristic model algorithms.

24. A method as in claim 13 , wherein the entity is selected from the group consisting essentially of a company, a corporation, a limited liability company, a limited liability corporation, a partnership, a limited liability partnership, a self-regulated organization, and a joint venture.

Assignments (9)