Method and apparatus for computing selection criteria for an automated valuation model

• US 20070033122A1
• Filed: 08/04/2005
• Published: 02/08/2007
• Est. Priority Date: 08/04/2005
• Status: Abandoned Application

• Current Assignee: CoreLogic Information Solutions Incorporated (CoreLogic Incorporated)
• Original Assignee: First American Real Estate Solutions LLC (CoreLogic Incorporated)
• Inventors: Cagan, Christopher
• Application Number:
  US11/197,653
• Publication Number:
  US 20070033122A1
• Time in Patent Office: Days
• US Class Current: 705/35
• 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

Abstract

A method and apparatus for ranking automated valuation model valuations. The method and apparatus involves a multi-step process and means for completing this process for calculating an automated valuation model score and then ranking the automated valuation models for precision based upon the results of this calculation.

Claims

1. A computer-based method of calculating an automated valuation rank, comprising the steps of:

gathering new data on at least one property;

requesting automated valuation model valuations of said at least one property;

calculating an automated valuation model rating based on at least one indicator of precision for said at least one property; and

calculating the automated valuation rank based upon said automated valuation model rating.

2. The method of claim 1, wherein one of said at least one indicator of precision is a hit rate.

3. The method of claim 1, wherein one of said at least one indicator of precision is a useful hit rate.

4. The method of claim 1, wherein one of said at least one indicator of precision is a center score.

5. The method of claim 1, wherein on of said at least one indicator of precision is an accuracy score.

6. The method of claim 1, wherein one of said at least one indicator of precision is an outlier score.

7. The method of claim 1, wherein said calculating step is accomplished using four of said indicators of precision calculated in the following order:

useful hit rate calculation, center score calculation, accuracy score calculation, and outlier point calculation which are used to thereby calculate said automated valuation model rating.

8. The method of claim 3, wherein said useful hit rate calculation is a hit rate calculation with valuations with variances larger than a specified percentage removed.

9. The method of claim 5, wherein said accuracy score is calculated using a state of the art score, whereby only an accuracy score greater than said state of the art score will result in penalties to said automated valuation model rating.

10. The method of claim 6, wherein said outlier score is calculated using a state of the art score, whereby only an outlier score greater than said state of the art score will result in penalties to said automated valuation model rating.

11. The method of claim 4, wherein said center score calculation reduces said automated valuation model rating by multiplying by a percentage equal to one hundred percent minus the percentage median of variance from the true value, converted to a positive number by taking its absolute value and then applying a multiplier to reflect the relative importance of overvaluations and undervaluations.

12. The method of claim 5, wherein said accuracy score calculation reduces said automated valuation model rating by multiplying by a percentage equal to one hundred percent minus the result of a spread error amplifier multiplied by the sum of:

a) the automated valuation model median absolute variance percentage, minus the state of the art median absolute variance percentage, and

b) the automated valuation model square root of mean squared error percentage, minus the state of the art square root of mean squared error percentage.

13. The method of claim 12, wherein said state of the art median absolute error is taken as zero.

14. The method of claim 12, wherein said state of the art square root of mean squared error is taken as zero.

15. The method of claim 5 wherein said accuracy score calculation reduces said automated valuation model rating by subtracting the result of a spread error amplifier multiplied by the sum of:

a) the automated valuation model median absolute variance minus the state of the art median absolute variance, and

b) the automated valuation model square root of mean squared error, minus the state of the art square root of mean squared error.

16. The method of claim 6, wherein said outlier score calculation reduces said automated valuation model rating by multiplying the total score by one hundred percent minus a percentage reflecting the sum of all outlier points minus a predetermined state of the art level of outlier points, where the outlier points themselves represent predetermined percentages which points have been individually been multiplied by a multiplier reflecting the size of the outliers in particular groups based on said predetermined percentages, and wherein said outlier points that represent positive outliers are further multiplied by an additional positive outlier amplifier.

17. The method of claim 15, wherein said state of the art median absolute variance is taken as zero.

18. The method of claim 15, wherein said state of the art square root of mean squared error is taken as zero.

19. The method of claim 16, wherein said state of the art level of outlier points is taken as zero.

20. The method of claim 6, wherein said outlier score calculation reduces said automated valuation model rating by subtracting a value representing the sum of all outlier points minus a predetermined state of the art level of outlier points, where the outlier points themselves represent the valuation variance below and above predetermined values, which points have been multiplied by a multiplier based on the size or magnitude of said values, and wherein said outlier points that represent positive outliers are further multiplied by an additional positive outlier amplifier.

21. The method of claim 20, wherein said state of the art level of outlier points is taken as zero.

22. A computer-based method of calculating an automated valuation rank, comprising the steps of:

gathering new data on at least one property;

requesting automated valuation model valuations of said at least one property;

calculating an automated valuation model rating based on two or more of the following indicators of precision;

a) a hit score

b) a useful hit score

c) a centrality score

d) an accuracy score

e) an outlier score

calculating the automated valuation rank based upon said automated valuation model rating.

23. The method of claim 22, wherein said indicators of precision are said useful hit score, said centrality score, said accuracy score and said outlier score.

24. The method of claim 23, wherein said indicators of precision are applied in the order they are listed.

25. The method of claim 23, wherein said indicators of precision are applied without reference to a predetermined order.

26. The method of claim 22, wherein said indicators of precision are said centrality score, said accuracy score and said outlier score.

27. The method of claim 26, wherein said indicators of precision are applied in the order they are listed.

28. The method of claim 26, wherein said indicators of precision are applied without reference to a predetermined order.

29. A computer-based apparatus for calculating an automated valuation rank, comprising:

temporary data storage means for storing relevant data;

input means connected to said temporary data storage means for receiving new data on at least one property;

automated valuation model connection means connected to said temporary data storage means for requesting automated valuation model valuations of said at least one property; and

calculation means connected to said temporary data storage means for calculating an automated valuation model rating based on at least one indicator of precision for said at least one property and further for calculating the automated valuation model rank based upon said automated valuation model rating.

30. The apparatus of claim 29, wherein one of said at least one indicator of precision is a hit rate score.

31. The apparatus of claim 29, wherein one of said at least one indicator of precision is a useful hit rate score.

32. The apparatus of claim 29, wherein one of said at least one indicator of precision is a center score.

33. The apparatus of claim 29, wherein one of said at least one indicator of precision is an accuracy score.

34. The apparatus of claim 29, wherein one of said at least one indicator of precision is an outlier score.

35. The apparatus of claim 29, wherein said calculation means uses four of said indicators of precision calculated in the following order:

useful hit rate calculation, center score calculation, accuracy score calculation, and outlier point calculation which are used to thereby calculate an automated valuation model rating and the automated valuation rank.

36. The apparatus of claim 31, wherein said useful hit rate calculation is a hit rate calculation with valuations with variances larger than a specified percentage removed.

37. The apparatus of claim 33, wherein said accuracy score is calculated using a state of the art score, whereby only an accuracy score greater than the state of the art score will result in penalties to said automated valuation model rating.

38. The apparatus of claim 34, wherein said outlier score is calculated using a state of the art score, whereby only an outlier score greater than the state of the art score will result in penalties to said automated valuation model rating.

39. The apparatus of claim 32, wherein said center score calculation reduces said automated valuation model rating by multiplying by a percentage equal to one hundred percent minus the absolute value of the percentage median of variance from the true value, multiplied by a multiplier based on whether that median is positive or negative.

40. The method of claim 33, wherein said accuracy score calculation reduces said automated valuation model rating by multiplying by one hundred percent minus a percentage equal to the result of a spread error amplifier multiplied by the sum of:

a) the automated valuation model median absolute variance percentage minus the state of the art median absolute variance percentage, and

b) the automated valuation model square root of mean squared error percentage, minus the state of the art square root of mean squared error percentage.

41. The method of claim 34, wherein said outlier score calculation reduces said automated valuation model rating by multiplying by one hundred percent minus a percentage representing the sum of all outlier points minus a predetermined state of the art level of outlier points, where the outlier points themselves represent the percentages of valuation variance below and above predetermined percentages, which points have been multiplied by a multiplier based on the size or magnitude of said predetermined percentages, and wherein said outlier points that represent positive outliers are further multiplied by an additional positive outlier amplifier.

42. The method of claim 41, wherein said predetermined state of the art level of outlier points is taken as zero.

43. The method of claim 33 wherein said accuracy score calculation reduces said automated valuation model rating by subtracting the result of a spread error amplifier multiplied by the sum of:

a) the automated valuation model median absolute variance minus the state of the art median absolute variance, and

b) the automated valuation model square root of mean squared error, minus the state of the art square root of mean squared error.

44. The method of claim 34, wherein said outlier score calculation reduces said automated valuation model rating by subtracting a value representing the sum of all outlier points minus a predetermined state of the art level of outlier points, where the outlier points themselves represent the valuation variance below and above predetermined values, which points have been multiplied by a multiplier based on the size or magnitude of said values, and wherein said outlier points that represent positive outliers are further multiplied by an additional positive outlier amplifier.

45. A computer-based apparatus for calculating an automated valuation rank, comprising:

temporary data storage means for storing relevant data;

input means connected to said temporary data storage means for receiving new data on at least one property;

automated valuation model connection means connected to said temporary data storage means for requesting automated valuation model valuations of said at least one property; and

calculation means connected to said temporary data storage means for calculating an automated valuation model rating based on. two or more of the following indicators of precision;

a) a hit score

b) a useful hit score

c) a centrality score

d) an accuracy score

e) an outlier score

said calculation means also used for calculating the automated valuation model rank based upon said automated valuation model rating.

46. The apparatus of claim 45, wherein said indicators of precision are said useful hit score, said centrality score, said accuracy score and said outlier score.

47. The apparatus of claim 46, wherein said indicators of precision are applied in the order they are listed.

48. The apparatus of claim 46, wherein said indicators of precision are applied without reference to a predetermined order.

49. The apparatus of claim 45, wherein said indicators of precision are said centrality score, said accuracy score and said outlier score.

50. The apparatus of claim 49, wherein said indicators of precision are applied in the order they are listed.

51. The apparatus of claim 49, wherein said indicators of precision are applied without reference to a predetermined order.