Methods, Systems, and Computer Program Products for Estimating Accuracy of Linking of Customer Relationships

• US 20090070289A1
• Filed: 09/12/2007
• Published: 03/12/2009
• Est. Priority Date: 09/12/2007
• Status: Active Grant

• Current Assignee: Liberty Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: American Express Travel Related Services Company, Inc. (American Express Company)
• Inventors: WEISSMAN, Mary, CHURI, Prashant Sharad, FITZGERALD, Gary Stephen, TRESCH, Sara
• Granted Patent: US 8,170,998 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03

Abstract

The disclosed methods, systems, and computer-program products allow a business to estimate linking errors in customer relationships in a database and to identify metrics that improve the linking accuracy. In an embodiment, a plurality of sample customer relationships are selected from a database to form a sample data set that is statistically representative of the database. Potential linking errors are then identified within the sample data set. The identified potential linking errors are then validated to identify actual linking errors in the sample data set. Once validated, the actual linking errors within the sample data set are used to estimate linking errors within the database. Further, the estimated linking errors in the database may be analyzed to identify one or more factors that contribute to the linking errors.

Claims

1. A method for estimating accuracy of linking of customer relationships in a database, comprising:

selecting from the database a plurality of sample customer relationships to form a sample data set;

identifying potential linking errors in the sample data set;

validating the potential linking errors to identify actual linking errors; and

using the identified linking errors to estimate linking errors within the database.

2. The method of claim 1, wherein the identifying step comprises identifying potential linking errors resulting from at least one of (i) linked relationships associated with different customers and (ii) unlinked relationships associated with the same customer.

3. The method of claim 1, wherein the selecting step comprises selecting from the database a plurality of sample customer relationships, wherein each relationship includes at least one of (i) a name, (ii) a street address, (iii) a city, (iv) a state, (v) a zip code, (vi) a social security number, (vii) a date of birth, (viii) a supplemental social security number, (ix) an relationship number, (x) a telephone number, and/or (xi) a customer number associated with the respective customer relationship.

4. The method of claim 1, wherein the identifying step comprises:

selecting a plurality of pairs of linked relationships from the database to form the sample data set;

comparing, for each selected pair of linked relationships, elements of data associated with each relationship within the selected pair of linked relationships to generate a set of elemental scores;

combining, for each selected pair of linked relationships, the set of elemental scores to generate a composite score; and

analyzing the composite score of each selected pair of linked relationships to identify a potential linking error associated with the selected pair of linked relationships.

5. The method of claim 4, wherein the comparing step comprises applying a rule to each element to determine an elemental score;

and wherein the combining step comprises applying a rule to generate the composite score from the set of elemental scores.

6. The method of claim 1, wherein the identifying step comprises:

selecting from the database a plurality of relationships linked to customers to form the sample data set;

retrieving, for each customer in the sample data set, a set of candidate relationships that are potentially linked to the respective customer;

comparing, for each customer in the sample data set, elements of data associated with (i) an relationship linked to the respective customer and (ii) each candidate relationship potentially linked to the respective customer to generate a set of elemental scores for each candidate relationship;

combining, for each candidate relationship, the set of elemental scores to generate a composite score; and

analyzing the composite score of each candidate relationship to identify a potential linking error associated with the candidate relationship.

7. The method of claim 6, wherein the retrieving step comprises applying a key based on a portion of at least one element of data associated with the respective customer to the plurality of relationships within the sample to identify the set of candidate relationships.

8. The method of claim 6, wherein the comparing step comprises applying a rule to each element to determine an elemental score;

and wherein the combining step comprises applying a rule to generate the composite score from the set of elemental scores.

9. The method of claim 1, wherein the using step further comprises extrapolating the linking errors within the sample data set to estimate the linking errors within the database.

10. The method of claim 1, further comprising:

analyzing the estimated linking errors to identify at least one factor contributing to the linking errors; and

modifying a linking procedure in response to the at least one identified factor.

11. A system for estimating accuracy of linking of customer relationships in a database, comprising:

means for selecting from the database a plurality of sample customer relationships to form a sample data set;

means for identifying potential linking errors in the sample data set;

means for validating the potential linking errors to identify actual linking errors; and

means for estimating linking errors within the database using the identified linking errors.

12. The system of claim 11, wherein the potential linking errors comprise at least one of (i) linked relationships respectively associated with different customers and (ii) unlinked relationships associated with the same customer.

13. The system of claim 11, wherein each sample customer relationship includes at least one of (i) a name, (ii) a street address, (iii) a city, (iv) a state, (v) a zip code, (vi) a social security number, (vii) a date of birth, (viii) a supplemental social security number, (ix) an relationship number, (x) a telephone number, and/or (xi) a customer number associated with the respective customer relationship.

14. The system of claim 11, wherein the means for identifying comprises:

means for selecting a plurality of pairs of linked relationships from the database to form the sample data set;

means for comparing, for each selected pair of linked relationships, elements of data associated with each relationship within the selected pair of linked relationships to generate a set of elemental scores;

means for combining, for each selected pair of linked relationships, the set of elemental scores to generate a composite score; and

means for analyzing the composite score of selected each pair of linked relationships to identify a potential linking error associated with the selected pair of linked relationships.

15. The system of claim 14, wherein the means for comparing comprises means for applying a rule to each element to determine an elemental score;

and wherein the means for combining comprises means for applying a rule to generate the composite score from the set of elemental scores.

16. The system of claim 11, wherein the means for identifying comprises:

means for selecting from the database a plurality of relationships linked to customers to form the sample data set;

means for retrieving, for each customer in the sample data set, a set of candidate relationships that are potentially linked to the respective customer;

means for comparing, for each customer in the sample data set, elements of obtained data associated with (i) an relationship linked to the respective customer and (ii) each candidate relationship potentially linked to the respective customer to generate a set of elemental scores for each candidate relationship;

means for combining, for each candidate relationship, the set of elemental scores to generate a composite score; and

means for analyzing the composite score of each candidate relationship to identify a potential linking error associated with the candidate relationship.

17. The system of claim 16, wherein the means for retrieving comprises means for applying a key based on a portion of at least one element of data associated with the respective customer to the plurality of relationships within the sample to identify the set of candidate relationships.

18. The system of claim 16, wherein the means for comparing comprises means for applying a rule to each element to determine an elemental score and wherein the means for combining comprises means for applying a rule to generate the composite score from the set of elemental scores.

19. The system of claim 11, further comprising:

means for analyzing the estimated linking errors to identify at least one factor contributing to the linking errors; and

means for modifying a linking procedure in response to the at least one identified factor.

20. A computer program product comprising a computer usable medium having control logic stored therein for causing a computer to estimate accuracy of linking of customer relationships in a database, comprising:

first computer readable program code means for causing the computer to select from the database a plurality of sample customer relationships to form a sample data set;

second computer readable program code means for causing the computer to identify potential linking errors in the sample data set;

third computer readable program code means for causing the computer to validate the potential linking errors to identify actual linking errors; and

fourth computer readable program code means for causing the computer to estimate linking errors within the database using the identified linking errors.

21. The computer program product of claim 20, wherein the second computer readable program code means comprises:

fifth computer readable program code means for causing the computer to select a plurality of pairs of linked relationships from the database to form the sample data set;

sixth computer readable program code means for causing the computer to compare, for each selected pair of linked relationships, elements of obtained data associated with each relationship within the selected pair of linked relationships to generate a set of elemental scores;

seventh computer readable program code means for causing the computer to combine, for each selected pair of linked relationships, the set of elemental scores to generate a composite score; and

eighth computer readable program code means for causing the computer to analyze the composite score of each selected pair of linked relationships to identify a potential linking error associated with the selected pair of linked relationships.

22. The computer program product of claim 20, wherein second computer readable program code means comprises:

fifth computer readable program code means for causing the computer to select from the database a plurality of relationships linked to customers to form the sample data set;

sixth computer readable program code means for causing the computer to retrieve, for each customer in the sample data set, a set of candidate relationships that are potentially linked to the respective customer;

seventh computer readable program code means for causing the computer to compare, for each customer in the sample data set, elements of data associated with (i) an relationship linked to the respective customer and (ii) each candidate relationship potentially linked to the respective customer to generate a set of elemental scores for each candidate relationship;

eighth computer readable program code means for causing the computer to combine, for each candidate relationship, the set of elemental scores to generate a composite score; and

ninth computer readable program code means for causing the computer to analyze the composite score of each candidate relationship to identify a potential linking error associated with the candidate relationship.