System and method for modeling consortium data

• US 8,050,959 B1
• Filed: 10/09/2007
• Issued: 11/01/2011
• Est. Priority Date: 10/09/2007
• Status: Active Grant

• Current Assignee: SAS Institute Incorporated
• Original Assignee: SAS Institute Incorporated
• Inventors: Jackson, Laura Elizabeth, Erdman, Donald James, Rioux, Jacques
• Primary Examiner(s): Jasmin; Lynda
• Assistant Examiner(s): SANTIAGO, LUIS F
• Application Number:
  US11/869,388
• Time in Patent Office: 1,484 Days
• Field of Search: 707/111
• US Class Current: 705/7.28
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities

Abstract

A method is provided for analyzing operational risk associated with one or more organizations, comprising receiving operational loss data from a plurality of organizations at a third-party risk management entity that is a separate entity from the plurality of organizations. The operational loss data includes confidential information regarding one or more of the plurality of organizations. The data received from the plurality of organizations, including the confidential information, is pooled. The pooled data is used to generate an operational risk model for one of the plurality of organizations, and this operational risk model is transmitted to the organization. A system for modeling operational risk for a plurality of organizations is provided, comprising a first data store configured to collect data regarding operational losses from the plurality of organizations, whose data includes confidential information regarding one or more of the organizations. The system includes software instructions configured to pool the operational loss data collected from the plurality of organizations and software instructions configured to generate operational risk models for the organizations using the pooled data, wherein the confidential information is not removed from the pooled data. The system also includes a second data store configured to store the generated models.

Claims

1. A computer-implemented method for analyzing operational risk associated with one or more organizations, comprising:

receiving operational loss data from a plurality of organizations based on historical loss events, which includes confidential information regarding one or more of the plurality of organizations, wherein the operational loss data is received by a third-party risk management entity that is a separate entity from the plurality of organizations;

pooling the data received from the plurality of organizations, including the confidential information;

generating one or more operational risk models for one of the plurality of organizations using the pooled data, wherein the confidential information is not removed from the pooled data, wherein the one or more operational risk models includes an effect model that is specific to the one of the plurality of organizations, the effect model including at least one of a scale effect to a distribution shape that is common to the plurality of organizations and a frequency effect that scales a common mean of the plurality of organizations; and

transmitting the one or more operational risk models to the one organization;

wherein the steps of the method are performed by one or more processors;

wherein the scale effect is a model that includes the following parameters;

2. The method of claim 1, wherein a combined operational risk model is generated, the combined operational risk model comprising:

common model elements that are common to all of the organizations whose operational loss data was used to create the model; and

organizational model elements that are specific to each of the organizations whose operational loss data was used to create the model;

wherein the organizational model elements corresponding to an organization and the common model elements are transmitted to the organization.

3. The method of claim 1, wherein the generated operational risk model transmitted to the one organization does not contain information that could be used to ascertain the confidential information of another organization in the plurality of organizations.

4. The method of claim 1, wherein operational risk models are generated for more than one of the plurality of organizations.

5. The method of claim 1, wherein a modified data set is created from the pooled data by removing the confidential information.

6. The method of claim 5, wherein the modified data set is transmitted to the one organization along with the one or more generated models.

7. The method of claim 1, wherein each generated model includes a constant to represent the effect on the model of the operational loss data for each organization of the plurality of organizations whose data was included in the pooled data.

8. The method of claim 1, wherein information about how the models were constructed is transmitted to the one organization along with the one or more generated models.

9. The method of claim 1, wherein information regarding the state of the organization'"'"'s operations at the time of an operational loss is received along with the operational loss data.

10. The method of claim 9, wherein the information regarding the state of the organization'"'"'s operations at the time of an operational loss is used to generate operational risk models for the plurality of organizations.

11. The method of claim 1, wherein operational risk models are generated for a plurality of groups that represent business lines of the organization.

12. The method of claim 1, wherein operational risk models are generated for a plurality of categories of operational risk.

13. The method of claim 1, wherein the organizations are for-profit business entities.

14. The method of claim 13, wherein the business entities are financial institutions.

15. A method for making a risk management decision for an organization using a data model generated by a risk management entity that is a separate entity from the organization, comprising:

collecting operational loss data for the organization based on historical loss events, which includes confidential information regarding the organization;

transmitting the collected operational loss data to the independent risk management entity; and

receiving from the independent risk management entity a data model generated based in whole or in part on the operational loss data for the organization as well as operational loss data, including confidential information, for one or more other organizations;

wherein the confidential information regarding the organization and the one or more other organizations is not removed prior to generating the data model, wherein the data model includes an effect model that is specific to the organization, the effect model including at least one of a scale effect to a distribution shape that is common to both the organization and the one or more other organizations and a frequency effect that is scales a common mean of the organization and the one or more other organizations;

wherein the steps of the method are performed by one or more processors;

wherein the scale effect is a model that includes the following parameters;

16. The method of claim 15, wherein the data model received from the independent entity is incorporated into the existing operational risk modeling process of the organization.

17. A system for modeling operational risk for a plurality of organizations, said system comprising:

a first data store configured to collect data regarding operational losses from the plurality of organizations based on historical loss events, which includes confidential information regarding one or more of the organizations;

software instructions configured to pool the operational loss data collected from the plurality of organizations;

software instructions configured to generate operational risk models for the organizations using the pooled data, wherein the confidential information is not removed from the pooled data, wherein the operational risk models include an effect model that is specific to one of the plurality of organizations, the effect model including at least one of a scale effect to a distribution shape that is common to the plurality of organizations and a frequency effect that scales a common mean of the plurality of organizations;

a second data store configured to store the generated models;

wherein the scale effect is a model that includes the following parameters;

18. The system of claim 17, wherein the first and second data stores are included in the same data storage medium.

19. The system of claim 17, including software instructions configured to transmit the generated models to the organizations.

20. A system for communicating with a risk management entity that is a separate entity from a plurality of organizations includes a system for modeling operational risk that is configured to collect and pool operational loss data for the plurality of organizations, including confidential information regarding one or more of the organizations, and generate operational risk models using the pooled data, said system comprising:

a first data store configured to collect operational loss data for an organization based on historical loss events, which includes confidential information regarding the organization;

software instructions configured to transmit the collected operational loss data to the independent risk management entity; and

a second data store configured to receive operational risk models from the risk management entity, wherein the operational risk models were generated based in whole or in part on the operational loss data for the organization as well as operational loss data, including confidential information, for one or more other organizations, wherein the confidential information regarding the organization and the one or more other organizations is not removed prior to generating the operational risk models, wherein the operational risk models include an effect model that is specific to the organization, the effect model including at least one of a scale effect to a distribution shape that is common to both the organization and the one or more other organizations and a frequency effect that scales a common mean of the organization and the one or more other organizations;

wherein the scale effect is a model that includes the following parameters;

21. The system of claim 20, wherein the first and second data stores are included in the same data storage medium.