Snapshot approach for underwriting valuation of asset portfolios

• US 20040034586A1
• Filed: 08/14/2002
• Published: 02/19/2004
• Est. Priority Date: 08/14/2002
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: GE Corporate Financial Services, Inc. (General Electric Company)
• Inventors: Doganaksoy, Murat, Keyes, Tim Kerry
• Granted Patent: US 7,983,974 B2
• Time in Patent Office: Days
• US Class Current: 705/36
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A method for valuing portfolio assets using a snapshot approach system is provided. The method includes segmenting portfolio assets into a predetermined number of segments based on financial attributes of each asset, selecting a representative sample of assets from each segment, valuing each asset in the representative asset sample, and calculating a value of the portfolio assets for bidding purposes based on the value of each asset in the representative asset sample.

Claims

1. A method for valuing portfolio assets using a snapshot approach system, said method comprising:

segmenting portfolio assets into a predetermined number of segments based on financial attributes of each asset;

selecting a representative sample of assets from each segment;

valuing each asset in the representative asset sample; and

calculating a value of the portfolio assets for bidding purposes based on the value of each asset in the representative asset sample.

2. A method according to claim 1 wherein segmenting portfolio assets further comprises segmenting portfolio assets into a predetermined number of segments based on financial attributes of each asset wherein the financial attributes of each asset include at least one of an amount of unpaid principal balance (“

UPB”

), a collateral type, whether the loan is secured, whether the loan is unsecured, real estate security, non-real estate security, a litigation status, a borrower operational status, and payment behavior.

3. A method according to claim 1 wherein segmenting portfolio assets further comprises:

assigning financial attributes to each asset in the portfolio wherein the financial attributes include at least one of an amount of unpaid principal balance (“

UPB”

), a collateral type, whether the loan is secured, whether the loan is unsecured, real estate security, non-real estate security, a litigation status, a borrower operational status, and payment behavior; and

categorizing each asset in the portfolio based on the financial attributes assigned to each portfolio asset.

4. A method according to claim 1 wherein selecting a representative sample of assets from each segment further comprises selecting a predetermined percentage of unpaid principal balance (“

UPB”

) of the portfolio assets.

5. A method according to claim 1 wherein valuing each asset in the representative asset sample further comprises performing an iterative and adaptive valuation in which each asset in the representative asset sample is individually valued.

6. A method according to claim 5 wherein performing the iterative and adaptive valuation further comprises:

underwriting each asset in the representative asset sample to generate underwriting data;

valuing each asset in the representative asset sample based on underwriting data;

segmenting each asset in the representative asset sample based on asset characteristics such that each asset in the representative asset sample is categorized with assets included in the representative asset sample having similar asset characteristics;

applying a stopping criteria; and

valuing the portfolio assets for bidding purposes by comparing the asset characteristics of the assets in the representative asset sample to the portfolio assets and extrapolating the value of the portfolio assets from the value of each asset in the representative asset sample.

7. A method according to claim 6 further comprising storing the underwriting data in a centralized database.

8. A method according to claim 6 wherein underwriting each asset in the representative asset sample further comprises:

collecting financial and business information relating to each asset in the representative asset sample;

performing collateral valuations for at least one asset in the representative asset sample; and

utilizing credit bureau information for at least one asset in the representative asset sample.

9. A method according to claim 6 wherein applying a stopping criteria further comprises performing an R-Squared analysis.

10. A method according to claim 6 wherein applying a stopping criteria further comprises:

valuing the representative asset sample based on underwriting data;

generating a valuation model for valuing the portfolio assets for bidding purposes by extrapolating the value of the portfolio assets from the value of the representative asset sample;

utilizing the valuation model to re-value the representative asset sample; and

determining whether the value of the representative asset sample based on underwriting data and the value of the representative asset sample based on the valuation model are substantially equal.

11. A method according to claim 1 wherein calculating a value of the portfolio assets for bidding purposes further comprises:

segmenting each asset in the representative asset sample based on asset characteristics such that each asset in the representative asset sample is categorized with assets having similar asset characteristics;

comparing the asset characteristics of the assets in the representative asset sample to the portfolio assets;

extrapolating the value of the portfolio assets from the value of each asset in the representative asset sample; and

calculating a total value of the portfolio based on the extrapolation.

12. A method according to claim 1 wherein calculating a value of the asset portfolio for bidding purposes further comprises generating a valuation model for use in bidding on the asset portfolio.

13. A method for valuing portfolio assets using a snapshot approach system, said method comprising:

segmenting portfolio assets into a predetermined number of segments based on financial attributes of each asset;

selecting a representative sample of assets from each segment;

performing an iterative and adaptive valuation in which each asset in the representative asset sample is individually valued, the iterative and adaptive valuation includes underwriting each asset in the representative asset sample to generate underwriting data, valuing each asset in the representative asset sample based on underwriting data, segmenting each asset in the representative asset sample based on asset characteristics such that each asset in the representative asset sample is categorized with assets included in the representative asset sample having similar asset characteristics, and applying a stopping criteria; and

valuing the portfolio assets for bidding purposes when the stopping criteria is satisfied by comparing the asset characteristics of the assets in the representative asset sample to the portfolio assets and extrapolating the value of the portfolio assets from the value of each asset in the representative asset sample.

14. A method according to claim 13 further comprising:

increasing the size of the representative sample of assets when the stopping criteria is not satisfied;

performing an iterative and adaptive valuation in which each asset in the increased representative asset sample is individually valued, the iterative and adaptive valuation includes underwriting each asset in the increased representative asset sample to generate underwriting data, valuing each asset in the increased representative asset sample based on underwriting data, segmenting each asset in the increased representative asset sample based on asset characteristics such that each asset in the increased representative asset sample is categorized with assets included in the increased representative asset sample having similar asset characteristics, and applying a stopping criteria; and

valuing the portfolio assets for bidding purposes when the stopping criteria is satisfied by comparing the asset characteristics of the assets in the increased representative asset sample to the portfolio assets and extrapolating the value of the portfolio assets from the value of each asset in the increased representative asset sample.

15. A portfolio valuation system for snapshot valuation of portfolio assets, said system comprising:

a centralized database for storing information relating to portfolio assets;

a server system coupled to said database and configured to perform valuation process analytics; and

at least one client system connected to said server system through a network, said server further configured to;

segment portfolio assets into a predetermined number of segments based on financial attributes of each asset;

select a representative sample of assets from each segment;

value each asset in said representative asset sample; and

calculate a value of the portfolio assets for bidding purposes based on the value of each asset in said representative asset sample.

16. A system according to claim 15 wherein said server is further configured to segment portfolio assets into a predetermined number of segments based on financial attributes of each asset wherein said financial attributes of each asset include at least one of an amount of unpaid principal balance (“

UPB”

), a collateral type, whether the loan is secured, whether the loan is unsecured, real estate security, non-real estate security, a litigation status, a borrower operational status, and payment behavior.

17. A system according to claim 15 wherein said server is further configured to:

assign financial attributes to each asset in said portfolio wherein said financial attributes include at least one of an amount of unpaid principal balance (“

UPB”

), a collateral type, whether the loan is secured, whether the loan is unsecured, real estate security, non-real estate security, a litigation status, a borrower operational status, and payment behavior; and

categorize each asset in said portfolio based on said financial attributes assigned to each portfolio asset.

18. A system according to claim 15 wherein said server is further configured to select a representative sample of assets from each segment based on a predetermined percentage of unpaid principal balance (“

UPB”

) of said portfolio assets.

19. A system according to claim 15 wherein said server is further configured to perform an iterative and adaptive valuation in which each asset in said representative asset sample is individually valued.

20. A system according to claim 19 wherein said server is further configured to perform said iterative and adaptive valuation by:

underwriting each asset in said representative asset sample to generate underwriting data;

valuing each asset in said representative asset sample based on underwriting data;

segmenting each asset in said representative asset sample based on asset characteristics such that each asset in said representative asset sample is categorized with assets in said representative asset sample having similar asset characteristics;

applying a stopping criteria; and

valuing said portfolio assets for bidding purposes by comparing said asset characteristics of said assets in said representative asset sample to said portfolio assets and extrapolating the value of said portfolio assets from the value of each asset in said representative asset sample.

21. A system according to claim 20 wherein said server is further configured to store said underwriting data in said centralized database.

22. A system according to claim 20 wherein said server is further configured to underwrite each asset in said representative asset sample by:

collecting financial and business information relating to each asset in said representative asset sample;

performing collateral valuations for at least one asset in said representative asset sample; and

utilizing credit bureau information for at least one asset in said representative asset sample.

23. A system according to claim 20 wherein said server is further configured to apply a stopping criteria by performing an R-Squared analysis.

24. A system according to claim 20 wherein said server is further configured to apply a stopping criteria by:

valuing said representative asset sample based on said underwriting data;

generating a valuation model for valuing said portfolio assets for bidding purposes by extrapolating the value of said portfolio assets from the value of said representative asset sample;

utilizing said valuation model to re-value said representative asset sample; and

determining whether the value of said representative asset sample based on said underwriting data and the value of said representative asset sample based on said valuation model are substantially equal.

25. A system according to claim 15 wherein said server is further configured to calculate a value of said portfolio assets for bidding purposes by:

segmenting each asset in said representative asset sample based on asset characteristics such that each asset in said representative asset sample is categorized with assets having similar asset characteristics;

comparing the asset characteristics of the assets in said representative asset sample to said portfolio assets;

extrapolating the value of said portfolio assets from the value of each asset in said representative asset sample; and

calculating a total value of said portfolio based on said extrapolation.

26. A system according to claim 15 wherein said server is further configured to generate a valuation model for use in bidding on said asset portfolio.

27. A portfolio valuation system for snapshot valuation of portfolio assets, said system comprising:

a centralized database for storing information relating to portfolio assets;

a server system coupled to said database and configured to perform valuation process analytics; and

at least one client system connected to said server system through a network, said server further configured to;

segment portfolio assets into a predetermined number of segments based on financial attributes of each asset;

select a representative sample of assets from each segment;

perform an iterative and adaptive valuation in which each asset in said representative asset sample is individually valued, said iterative and adaptive valuation comprises underwriting each asset in said representative asset sample to generate underwriting data, valuing each asset in said representative asset sample based on underwriting data, segmenting each asset in said representative asset sample based on asset characteristics such that each asset in said representative asset sample is categorized with assets included in said representative asset sample having similar asset characteristics, and applying a stopping criteria; and

value said portfolio assets for bidding purposes when said stopping criteria is satisfied by comparing asset characteristics of the assets in said representative asset sample to said portfolio assets and extrapolating the value of said portfolio assets from the value of each asset in said representative asset sample.

28. A system according to claim 27 wherein said server is further configured:

increase the size of the representative sample of assets when said stopping criteria is not satisfied;

perform an iterative and adaptive valuation in which each asset in said increased representative asset sample is individually valued, said iterative and adaptive valuation includes underwriting each asset in said increased representative asset sample to generate underwriting data, valuing each asset in said increased representative asset sample based on underwriting data, segmenting each asset in said increased representative asset sample based on asset characteristics such that each asset in said increased representative asset sample is categorized with assets included in said increased representative asset sample having similar asset characteristics, and applying said stopping criteria; and

value said portfolio assets for bidding purposes when said stopping criteria is satisfied by comparing asset characteristics of the assets in said increased representative asset sample to said portfolio assets and extrapolating the value of said portfolio assets from the value of each asset in said increased representative asset sample.

29. A computer for snapshot valuation of portfolio assets, said computer including a database of portfolio assets and configured to enable valuation process analytics, said computer programmed to:

segment portfolio assets into a predetermined number of segments based on financial attributes of each asset;

select a representative sample of assets from each segment;

value each asset in said representative asset sample; and

calculate a value of the portfolio assets for bidding purposes based on the value of each asset in said representative asset sample.

30. A computer according to claim 29 programmed to segment portfolio assets into a predetermined number of segments based on financial attributes of each asset wherein said financial attributes of each asset include at least one of an amount of unpaid principal balance (“

UPB”

), a collateral type, whether the loan is secured, whether the loan is unsecured, real estate security, non-real estate security, a litigation status, a borrower operational status, and payment behavior.

31. A computer according to claim 29 programmed to segment portfolio assets by:

assigning financial attributes to each asset in said portfolio wherein said financial attributes include at least one of an amount of unpaid principal balance (“

UPB”

), a collateral type, whether the loan is secured, whether the loan is unsecured, real estate security, non-real estate security, a litigation status, a borrower operational status, and payment behavior; and

categorizing each asset in said portfolio based on said financial attributes assigned to each portfolio asset.

32. A computer according to claim 29 programmed to select a representative sample of assets from each segment based on a predetermined percentage of unpaid principal balance (“

UPB”

) of said portfolio assets.

33. A computer according to claim 29 programmed to perform an iterative and adaptive valuation in which each asset in said representative asset sample is individually valued.

34. A computer according to claim 33 programmed to perform said iterative and adaptive valuation by:

underwriting each asset in said representative asset sample to generate underwriting data;

valuing each asset in said representative asset sample based on underwriting data;

segmenting each asset in said representative asset sample based on asset characteristics such that each asset in said representative asset sample is categorized with assets having similar asset characteristics;

applying a stopping criteria; and

valuing said portfolio assets for bidding purposes by comparing said asset characteristics of said assets in said representative asset sample to said portfolio assets and extrapolating the value of said portfolio assets from the value of each asset in said representative asset sample.

35. A computer according to claim 34 programmed to store said underwriting data in a centralized database.

36. A computer according to claim 34 programmed to underwrite each asset in said representative asset sample by:

collecting financial and business information relating to each asset in said representative asset sample;

performing collateral valuations for at least one asset in said representative asset sample; and

utilizing credit bureau information for at least one asset in said representative asset sample.

37. A computer according to claim 34 programmed to apply a stopping criteria by performing an R-Squared analysis.

38. A computer according to claim 34 programmed to apply a stopping criteria by:

valuing said representative asset sample based on said underwriting data;

generating a valuation model for valuing said portfolio assets for bidding purposes by extrapolating the value of said portfolio assets from the value of said representative asset sample;

utilizing said valuation model to re-value said representative asset sample; and

determining whether the value of said representative asset sample based on said underwriting data and the value of said representative asset sample based on said valuation model are substantially equal.

39. A computer according to claim 29 programmed to calculate a value of said portfolio assets for bidding purposes by:

segmenting each asset in said representative asset sample based on asset characteristics such that each asset in said representative asset sample is categorized with assets having similar asset characteristics;

comparing the asset characteristics of the assets in said representative asset sample to said portfolio assets;

extrapolating the value of said portfolio assets from the value of each asset in said representative asset sample; and

calculating a total value of said portfolio based on said extrapolation.

40. A computer according to claim 29 programmed to generate a valuation model for use in bidding on said asset portfolio.

41. A computer for snapshot valuation of portfolio assets, said computer including a database of portfolio assets and configured to enable valuation process analytics, said computer programmed to:

segment portfolio assets into a predetermined number of segments based on financial attributes of each asset;

select a representative sample of assets from each segment;

perform an iterative and adaptive valuation in which each asset in said representative asset sample is individually valued, said iterative and adaptive valuation comprises underwriting each asset in said representative asset sample to generate underwriting data, valuing each asset in said representative asset sample based on underwriting data, segmenting each asset in said representative asset sample based on asset characteristics such that each asset in said representative asset sample is categorized with assets included in said representative asset sample having similar asset characteristics, and applying a stopping criteria; and

value said portfolio assets for bidding purposes when said stopping criteria is satisfied by comparing asset characteristics of the assets in said representative asset sample to said portfolio assets and extrapolating the value of said portfolio assets from the value of each asset in said representative asset sample.

42. A computer according to claim 41 programmed to:

increase the size of the representative sample of assets when said stopping criteria is not satisfied;

perform an iterative and adaptive valuation in which each asset in said increased representative asset sample is individually valued, said iterative and adaptive valuation includes underwriting each asset in said increased representative asset sample to generate underwriting data, valuing each asset in said increased representative asset sample based on underwriting data, segmenting each asset in said increased representative asset sample based on asset characteristics such that each asset in said increased representative asset sample is categorized with assets included in said increased representative asset sample having similar asset characteristics, and applying said stopping criteria; and

value said portfolio assets for bidding purposes when said stopping criteria is satisfied by comparing asset characteristics of the assets in said increased representative asset sample to said portfolio assets and extrapolating the value of said portfolio assets from the value of each asset in said increased representative asset sample.

43. A computer program embodied on a computer readable medium for performing snapshot valuation of portfolio assets, said computer program comprising computer code that:

segments portfolio assets into a predetermined number of segments based on financial attributes of each asset;

selects a representative sample of assets from each segment;

values each asset in said representative asset sample; and

calculates a value of the portfolio assets for bidding purposes based on the value of each asset in said representative asset sample.

44. A computer program according to claim 43 further comprising computer code that segments portfolio assets into a predetermined number of segments based on financial attributes of each asset wherein said financial attributes of each asset include at least one of an amount of unpaid principal balance (“

UPB”

), a collateral type, whether the loan is secured, whether the loan is unsecured, real estate security, non-real estate security, a litigation status, a borrower operational status, and payment behavior.

45. A computer program according to claim 43 further comprising computer code that segments portfolio assets by:

assigning financial attributes to each asset in said portfolio wherein said financial attributes include at least one of an amount of unpaid principal balance (“

UPB”

), a collateral type, whether the loan is secured, whether the loan is unsecured, real estate security, non-real estate security, a litigation status, a borrower operational status, and payment behavior; and

categorizing each asset in said portfolio based on said financial attributes assigned to each portfolio asset.

46. A computer program according to claim 43 further comprising computer code that selects a representative sample of assets from each segment based on a predetermined percentage of unpaid principal balance (“

UPB”

) of said portfolio assets.

47. A computer program according to claim 43 further comprising computer code that performs an iterative and adaptive valuation in which each asset in said representative asset sample is individually valued.

48. A computer program according to claim 47 further comprising computer code that performs an iterative and adaptive valuation by:

underwriting each asset in said representative asset sample to generate underwriting data;

valuing each asset in said representative asset sample based on underwriting data;

segmenting each asset in said representative asset sample based on asset characteristics such that each asset in said representative asset sample is categorized with assets having similar asset characteristics;

applying a stopping criteria; and

valuing said portfolio assets for bidding purposes by comparing said asset characteristics of said assets in said representative asset sample to said portfolio assets and extrapolating the value of said portfolio assets from the value of each asset in said representative asset sample.

49. A computer program according to claim 48 further comprising computer code that stores said underwriting data in a centralized database.

50. A computer program according to claim 48 further comprising computer code that underwrites each asset in said representative asset sample by:

collecting financial and business information relating to each asset in said representative asset sample;

performing collateral valuations for at least one asset in said representative asset sample; and

utilizing credit bureau information for at least one asset in said representative asset sample.

51. A computer program according to claim 48 further comprising computer code that applies a stopping criteria by performing an R-Squared analysis.

52. A computer program according to claim 48 further comprising computer code that applies a stopping criteria by:

valuing said representative asset sample based on said underwriting data;

generating a valuation model for valuing said portfolio assets for bidding purposes by extrapolating the value of said portfolio assets from the value of said representative asset sample;

utilizing said valuation model to re-value said representative asset sample; and

determining whether the value of said representative asset sample based on said underwriting data and the value of said representative asset sample based on said valuation model are substantially equal.

53. A computer program according to claim 43 further comprising computer code that calculates a value of said portfolio assets for bidding purposes by:

segmenting each asset in said representative asset sample based on asset characteristics such that each asset in said representative asset sample is categorized with assets having similar asset characteristics;

comparing the asset characteristics of the assets in said representative asset sample to said portfolio assets;

extrapolating the value of said portfolio assets from the value of each asset in said representative asset sample; and

calculating a total value of said portfolio based on said extrapolation.

54. A computer program according to claim 43 further comprising computer code that generates a valuation model for use in bidding on said asset portfolio.

55. A computer program embodied on a computer readable medium for performing snapshot valuation of portfolio assets, said computer program comprising computer code that:

segments portfolio assets into a predetermined number of segments based on financial attributes of each asset;

selects a representative sample of assets from each segment;

performs an iterative and adaptive valuation in which each asset in said representative asset sample is individually valued, said iterative and adaptive valuation comprises underwriting each asset in said representative asset sample to generate underwriting data, valuing each asset in said representative asset sample based on underwriting data, segmenting each asset in said representative asset sample based on asset characteristics such that each asset in said representative asset sample is categorized with assets included in said representative asset sample having similar asset characteristics, and applying a stopping criteria; and

values said portfolio assets for bidding purposes when said stopping criteria is satisfied by comparing asset characteristics of the assets in said representative asset sample to said portfolio assets and extrapolating the value of said portfolio assets from the value of each asset in said representative asset sample.

56. A computer program according to claim 55 further comprising computer code that:

increases the size of the representative sample of assets when said stopping criteria is not satisfied;

performs an iterative and adaptive valuation in which each asset in said increased representative asset sample is individually valued, said iterative and adaptive valuation includes underwriting each asset in said increased representative asset sample to generate underwriting data, valuing each asset in said increased representative asset sample based on underwriting data, segmenting each asset in said increased representative asset sample based on asset characteristics such that each asset in said increased representative asset sample is categorized with assets included in said increased representative asset sample having similar asset characteristics, and applying said stopping criteria; and

values said portfolio assets for bidding purposes when said stopping criteria is satisfied by comparing asset characteristics of the assets in said increased representative asset sample to said portfolio assets and extrapolating the value of said portfolio assets from the value of each asset in said increased representative asset sample.