RISK PATTERN DETERMINATION AND ASSOCIATED RISK PATTERN ALERTS

• US 20110131131A1
• Filed: 10/29/2010
• Published: 06/02/2011
• Est. Priority Date: 12/01/2009
• Status: Abandoned Application

• Current Assignee: Bank of America Corp.
• Original Assignee: Bank of America Corp.
• Inventors: Shiflet, Robert George JR., Griffin, Maura Louise, Stigler, Teresa Hegdahl, Turner, David G., Turner, Donna Dee, Harman, Mary Palmer
• Application Number:
  US12/916,228
• Publication Number:
  US 20110131131A1
• Time in Patent Office: Days
• US Class Current: 705/38
• CPC Class Codes: G06Q 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

Embodiments of the present invention relate to systems, apparatus, methods and computer program products for integrated risk assessment and mitigation. More specifically, embodiments of the present invention provide for determining risk patterns and, in particular embodiments, emerging risk patterns associated with emerging risk, based on a combination of, or in some embodiments all, financial institution data from multiple financial institutions, data aggregator data, non-financial institution data, negative activity data and/or risk deviation data. As a result of the determination of risk patterns, risk pattern alerts may be communicated to designated recipients for the purpose of managing the risk. In additional embodiments, a health risk indicator is determined that indicates the current condition of risk for a customer, a company, an industry or industry segment.

Claims

1. A system for risk management, the system comprising:

a computing platform including at least one processor and a memory;

a centralized risk database stored in the memory and configured to receive financial institution data from a plurality of financial institutions;

a risk pattern analysis routine stored in the memory, executable by the processor and configured to analytically monitor the financial institution data to identify one or more risk patterns; and

a risk pattern alert routine stored in the memory, executable by the processor and configured to generate and initiate communication of a risk pattern alert based on identified risk patterns.

2. The system of claim 1, wherein the risk pattern analysis routine is further configured to identify one or more emerging risk patterns associated with an emerging risk.

3. The system of claim 1, wherein the centralized risk database is further configured to receive data aggregator data from one or more data aggregators and wherein the risk pattern analysis routine is further configured to analytically monitor the data aggregator data to identify one or more risk patterns.

4. The system of claim 1, wherein the centralized risk database is further configured to receive non-financial institution data from one or more non-financial institutions and wherein the risk pattern analysis routine is further configured to analytically monitor the non-financial institution data to identify one or more risk patterns.

5. The system of claim 1, wherein the centralized risk database is further configured to receive negative activity data from a plurality of financial institutions and wherein the risk pattern analysis routine is further configured to analytically monitor the negative activity data to identify one or more risk patterns.

6. The system of claim 1, wherein the centralized risk database is further configured to receive data aggregator data from one or more data aggregators, non-financial institution data from one or more non-financial institutions and negative activity data and wherein the risk pattern analysis routine is further configured to analytically monitor the data aggregator data, the non-financial institution data and the negative activity data to identify one or more risk patterns.

7. The system of claim 1, wherein the centralized risk database is further configured to receive at least one of financial institution claims data or non-financial institution claims data and wherein the risk pattern analysis routine is further configured to analytically monitor the claims data to identify one or more risk patterns.

8. The system of claim 1, wherein the centralized risk database is further configured to receive claims data from at least one of financial institutions or non-financial institutions, data aggregator data from one or more data aggregators, non-financial institution data from one or more non-financial institutions and negative activity data and wherein the risk pattern analysis routine is further configured to analytically monitor the claims data, the data aggregator data, the non-financial institution data and the negative activity data to identify one or more risk patterns.

9. The system of claim 1, further comprising:

a behavioral baseline routine stored in the memory, executable by the processor and configured to determine a customer behavioral baseline score based on data in the centralized risk database; and

a risk score routine stored in the memory, executable by the processor and configured to determine a risk score associated with a risk type and based on one or more of the risk patterns.

10. The system of claim 1, wherein the risk pattern alert routine is further configured to generate and initiate communication of a risk pattern alert based on identified risk patterns, wherein the alert is communicated to at least one of financial institutions, non-financial institutions, data aggregators, government agencies or affected customers.

11. The system of claim 1, wherein the risk pattern alert routine is further configured to initiate communication of a risk alert to predetermined entities, wherein the predetermined entities are based on the type of risk pattern.

12. The system of claim 1, further comprising a risk health indicator routine stored in the memory, executable by the processor and configured to monitor data in the centralized risk database to determine a risk health indicator, wherein the risk health indicator indicates a current risk state condition for a customer, a company, an industry or a segment of an industry.

13. The system of claim 12, wherein the risk health indicator is further configured to identify entities having a higher than normal rate of risk, wherein the rate of risk indicates an increased likelihood of loss.

14. A method for risk assessment and mitigation, the method comprising:

receiving, at a centralized risk database stored in computing device memory, financial institution data from a plurality of financial institutions;

monitoring, via a computing device processor, the financial institution data to identify one or more risk patterns; and

generating and initiating communication of, via a computing device processor, a risk pattern alert based on identified risk patterns.

15. The method of claim 14, wherein monitoring further comprises monitoring, via the computing device processor, the financial institution data to identify one or more emerging risk patterns associated with an emerging risk.

16. The method of claim 14, wherein receiving further comprises receiving, at the centralized risk database, data aggregator data from one or more data aggregators and wherein monitoring further comprises monitoring, via the computing device processor, the data aggregator data to identify one or more risk patterns.

17. The method of claim 14, wherein receiving further comprises receiving, at the centralized risk database, non-financial institution data from one or more non-financial institution entities and wherein monitoring further comprises monitoring, via the computing device processor, the non-financial institution data to identify one or more risk patterns.

18. The method of claim 14, wherein receiving further comprises receiving, at the centralized risk database, negative activity data and wherein monitoring further comprises monitoring, via the computing device processor, the negative activity data to identify one or more risk patterns.

19. The method of claim 14, wherein receiving further comprises receiving, at the centralized risk database, data aggregator data from one or more data aggregators, non-financial institution data from one or more non-financial institutions and negative activity data and wherein monitoring further comprises monitoring, via the computing device processor, the data aggregator data, the non-financial institution data and the negative activity data to identify one or more risk patterns.

20. The method of claim 14, wherein receiving further comprises receiving, at the centralized risk database, claims data from at least one financial institutions or non-financial institutions and wherein monitoring further comprises monitoring, via the computing device processor, the claims data to identify one or more risk patterns.

21. The method of claim 14, wherein receiving further comprises receiving, at the centralized risk database, claims data from at least one of financial institutions or non-financial institutions, data aggregator data from one or more data aggregators, non-financial institution data from one or more non-financial institutions and negative activity data and wherein monitoring further comprises monitoring, via the computing device processor, the claims data, the data aggregator data, the non-financial institution data and the negative activity data to identify one or more risk patterns.

22. The method of claim 14, further comprising determining a customer behavioral baseline score based on data in the centralized risk database and monitoring for deviations in the customer behavioral baseline score and wherein monitoring the financial institution data further comprises monitoring, via the computing device processor, the deviations to identify one or more risk patterns.

23. The method of claim 14, wherein generating and initiating communication further comprises generating and initiating communication of, via the computing device processor, a risk pattern alert based on identified risk patterns, wherein the alert is communicated to at least one of a financial institution, a non-financial institution entity, a data aggregator, a government agency or an affected customer.

24. The method of claim 14, wherein generating and initiating communication further comprises generating and initiating communication of, via the computing device processor, a risk alert to predetermined entities, wherein the predetermined entities are based on the type of risk pattern.

25. The method of claim 14, further comprising monitoring, via a computing device processor, data in the centralized risk database to determine a risk health indicator, wherein the risk health indicator indicates a current risk state condition for a customer, a company, an industry or a segment of an industry.

26. The method of claim 25, wherein monitoring the data further comprises identifying entities having a higher than normal rate of risk, wherein the rate of risk indicates an increased likelihood of loss.

27. A computer program product comprising:

a computer-readable medium comprising;

a first set of codes for causing a computer to receive financial institution data from a plurality of financial institutions;

a second set of codes for causing a computer to monitor the financial institution data to identify one or more risk patterns; and

a third set of codes for causing a computer to generate and initiate communication of a risk pattern alert based on identified risk patterns.

28. The computer program product of claim 27, wherein the second set of codes is further configured to cause the computer to monitor the financial institution data to identify one or more emerging risk patterns associated with an emerging risk.

29. The computer program product of claim 27, wherein the first set of codes is further configured to cause the computer to receive data aggregator data from one or more data aggregators and wherein the second set of codes is further configured to cause the computer to monitor the data aggregator data to identify one or more risk patterns.

30. The computer program product of claim 27, wherein the first set of codes is further configured to cause the computer to receive non-financial institution data from one or more non-financial institution entities, and wherein the second set of codes is further configured to cause the computer to monitor the non-financial institution data to identify one or more risk patterns.

31. The computer program product of claim 27, wherein the first set of codes is further configured to cause the computer to receive negative activity data and wherein the second set of codes is further configured to cause the computer to monitor the negative activity data to identify one or more risk patterns.

32. The computer program product of claim 27, wherein the first set of codes is further configured to cause the computer to receive data aggregator data from one or more data aggregators, non-financial institution data from one or more non-financial institutions and negative activity data, and wherein monitoring further comprises monitoring, via the computing device processor, the data aggregator data, the non-financial institution data and the negative activity data to identify one or more risk patterns.

33. The computer program product of claim 27, wherein the first set of codes is further configured to cause the computer to receive claims data from at least one of financial institutions or non-financial institutions and wherein the second set of codes is further configured to cause the computer to monitor the claims data to identify one or more risk patterns.

34. The computer program product of claim 27, wherein the first set of codes is further configured to cause the computer to receive claims data from at least one of a financial institution or a non-financial institution, data aggregator data from one or more data aggregators, non-financial institution data from one or more non-financial institutions and negative activity data, and wherein monitoring further comprises monitoring, via the computing device processor, the claims data, the data aggregator data, the non-financial institution data, and the negative activity data to identify one or more risk patterns.

35. The computer program product of claim 27, further comprising a fourth set of codes for causing a computer to determine a customer risk baseline score based on data in the centralized risk database, and a fifth set of codes for causing a computer to monitor for deviations in the customer risk baseline score and wherein the second set of codes is further configured to cause the computer to monitor the deviations to identify one or more risk patterns.

36. The computer program product of claim 27, wherein the third set of codes is further configured to cause the computer to generate and initiate communication of the risk pattern alert based on identified risk patterns, wherein the alert is communicated to at least one of a financial institution, a non-financial institution entity, a government agency or an affected customer.

37. The computer program product of claim 27, wherein the third set of codes is further configured to cause the computer to generate and initiate communication of the risk alert to predetermined entities, wherein the predetermined entities are based on the type of risk pattern.

38. The computer program product of claim 27, further comprising a fourth set of codes for causing a computer to monitor data in the centralized risk database to determine a risk health indicator, wherein the risk health indicator indicates a current risk health condition for a customer, a company, an industry or a segment of an industry.

39. The computer program product of claim 38, wherein the fourth set of codes is further configured to cause the computer to identify entities having a higher than normal rate of risk, wherein the rate of risk indicates an increased likelihood of loss.

40. A system for assessing and mitigating risk, the system comprising:

a computing platform including at least one processor and a memory;

a centralized risk database stored in the memory and configured to data from one or more of a plurality of financial institutions, one or more non-financial institution entities or one or more data aggregators; and

a risk health indicator routine stored in the memory, executable by the processor and configured to monitor data in the centralized risk database to determine a risk health indicator, wherein the risk health indicator indicates a current risk state condition for an entity.

41. The system of claim 40, wherein the risk health indicator routine is further configured to determine the risk health indicator, wherein the risk health indicator indicates a current risk state condition for one of a customer, a company, an industry or a segment of an industry.

42. The system of claim 40, wherein the risk health indicator is further configured to identify entities having a higher than normal rate of risk, wherein the rate of risk indicates an increased likelihood of loss.

43. A method for risk management, the method comprising:

receiving, in a centralized risk database stored in the memory, data from one or more of a plurality of financial institutions, non-financial institution entities or one or more data aggregators; and

monitoring, via a computing device processor, data in the centralized risk database to determine a risk health indicator, wherein the risk health indicator indicates a current risk state condition for an entity.

44. The method of claim 43, wherein the monitoring further comprises determining, via the computing device processor, the risk health indicator, wherein the risk health indicator indicates a current risk state condition for one of a customer, a company, an industry or a segment of an industry.

45. The method of claim 43, wherein monitoring further comprises monitoring, via the computing device processor, the data to identify entities having a higher than normal rate of risk, wherein the rate of risk indicates an increased likelihood of loss.