Financial risk mitigation optimization systems and methods

• US 20070050282A1
• Filed: 08/25/2005
• Published: 03/01/2007
• Est. Priority Date: 08/25/2005
• Status: Active Grant

• Current Assignee: SAS Institute Incorporated
• Original Assignee: SAS Institute Incorporated
• Inventors: Chen, Wei, Hu, Ping, Erdman, Donald
• Granted Patent: US 7,624,054 B2
• Time in Patent Office: Days
• US Class Current: 705/38
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

Systems and methods for optimizing financial risk mitigations. A system and method can be provided for the generation of a financial risk mitigation optimization model. The model can be used in determining an allocation of financial risk mitigations with respect to exposures.

Claims

1. A computer-implemented method for mitigating financial risk, comprising:

receiving data indicative of exposures;

receiving data indicative of financial risk mitigations;

receiving data indicative of relationships between financial risk mitigation and exposure;

wherein the received relationship data indicates that there is at least a one-to-many relationship between a financial risk mitigation and an exposure;

generating a financial risk mitigation optimization model based upon the received exposure data, the received financial risk mitigation data, and the received relationship data;

wherein the financial risk mitigation optimization model is for use in determining an allocation of the financial risk mitigations with respect to the exposures.

2. The method of claim 1, wherein the financial risk mitigation optimization model maximizes the use of financial risk mitigations such that risk mitigated to a minimal level;

wherein the financial risk mitigation optimization model is solved as a generalized network problem based upon the exposure, mitigation and relationship data.

3. The method of claim 2, wherein the financial risk mitigation optimization model includes a linear programming algorithm for use in determining the allocation of the financial risk mitigations with respect to the exposures.

4. The method of claim 3, wherein the linear programming algorithm is at least one of an interior point algorithm, or a simplex algorithm, including any combinations thereof and any extensions for network optimization.

5. The method of claim 1, wherein financial risk mitigation is credit risk mitigation.

6. The method of claim 1, further comprising

calculating an exposure value associated with an exposure and a mitigation value associated with a financial risk mitigation, wherein the exposure and mitigation are related;

and

calculating an exposure riskiness measure that is associated with an exposure and a mitigation riskiness measure that is associated with a financial risk mitigation;

wherein the mitigation value is compared to the exposure value to determine what portion of the exposure can be offset by the financial risk mitigation.

7. The method of claim 6, wherein the mitigation and exposure riskiness measures of the financial risk mitigations and exposures, respectively, are determined based upon probability of default and loss given default associated with the financial risk mitigations and exposures.

8. The method of claim 6, wherein the data indicative of the relationships between financial risk mitigations and exposures is generated based upon agreements which specify how financial risk mitigations are associated with exposures.

9. The method of claim 8, wherein the relationships between the exposures and financial risk mitigations are established by at least one of a collateral agreement, an insurance agreement, a credit derivative, a guarantee, or a netting agreement.

10. The method of claim 8, further comprising calculating a discount factor between related exposures and financial risk mitigations;

wherein the discount factor is calculated based upon maturity mismatches between the exposures and financial risk mitigations, currency mismatches between the exposures and financial risk mitigations, or an over-collateralization requirement, and combinations thereof.

11. The method of claim 10, further comprising calculating a cost of using a financial risk mitigation to cover an exposure based upon the mitigation and exposure riskiness measures of the financial risk mitigation and the exposure, respectively.

12. The method of claim 1, further comprising the step of constructing a generalized network linking the data indicative of exposures to the data indicative of financial risk mitigations;

associating a cost and a discount factor with the linkings of the generalized network.

13. The method of claim 1, wherein the financial risk optimization model is configured to notify a user of a minimum asset value level adequate to cover risk-weighted financial risk mitigations and any risk-weighted unsecured exposures.

14. The method of claim 13, further comprising performing an analysis of risk weighted assets for the exposures,

wherein performing the analysis of risk weighted assets comprises:

adjusting the financial risk mitigations by multiplying them by associated financial risk mitigation discounts based upon the relationships between financial risk mitigations and exposures, and multiplying them by associated financial risk mitigation riskiness measures;

adjusting any uncovered portions of the exposures by multiplying the uncovered exposures by associated exposure riskiness measures;

adding the adjusted financial risk mitigations associated with an exposure to the adjusted uncovered portions of the exposures.

15. The method of claim 14, wherein the analysis of risk weighted assets for the exposures alerts a user to a level of regulatory capital projected to cover risk weighted exposures and mitigations.

16. The method of claim 15, wherein the risk weighted assets analysis of the financial risk mitigation optimization model is created based upon financial regulations.

17. The method of claim 1, wherein the allocation of the financial risk mitigations to the exposures determines to what extent a financial risk mitigation is to cover an exposure with which the financial risk mitigation is associated.

18. The method of claim 1, wherein the one-to-many relationship comprises at least one of:

a relationship between an exposure and a plurality of financial risk mitigations, a relationship between a financial risk mitigation and a plurality of exposures, and a relationship between a plurality of financial risk mitigations and a plurality of exposures.

19. Computer software stored on one or more computer readable media, the computer software comprising program code for carrying out a method according to claim 1.

20. A system configured to generate a financial risk mitigation optimization model including an allocation of financial risk mitigations to exposures, comprising:

software instructions configured to retrieve exposure data, financial risk mitigation data and relationship data

wherein the relationship data describes the relationship between the exposure data and the financial risk mitigation data;

wherein the relationship data indicates that there is at least a one-to-many relationship between a financial risk mitigation and an exposure;

software instructions configured to generate a financial risk mitigation optimization model based upon the exposure data, the financial risk mitigation data, and the relationship data.

21. The system of claim 20, further comprising software instructions configured to apply the financial risk mitigation optimization model to the financial risk mitigations and exposures, and produce a regulatory capital level based upon financial risk mitigations, unsecured exposures, and associated riskiness measures.