System and method for generating a finance attribute from tradeline data

• US 8,036,979 B1
• Filed: 10/05/2007
• Issued: 10/11/2011
• Est. Priority Date: 10/05/2006
• Status: Active Grant

• Current Assignee: Experian Information Solutions Incorporated (Experian plc)
• Original Assignee: Experian Information Solutions Incorporated (Experian plc)
• Inventors: Kornegay, Adam Thomas, Torrez, Luz M.
• Primary Examiner(s): Kalinowski; Alexander
• Assistant Examiner(s): Chang; Edward
• Application Number:
  US11/973,300
• Time in Patent Office: 1,467 Days
• Field of Search: 705/38
• US Class Current: 705/38
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof

Abstract

Embodiments of a system and method are described for generating a finance attribute. In one embodiment, the systems and methods retrieve raw tradeline data from a plurality of credit bureaus, retrieve industry code data related to each of the plurality of credit bureaus, determine one or more tradeline leveling characteristics that meet at least one pre-determined threshold, and generate a finance attribute using the selected leveling characteristics.

Claims

1. A computer implemented method for generating an attribute from raw tradeline data from a plurality of credit bureaus, the method comprising:

retrieving raw tradeline data from each of the plurality of credit bureaus;

retrieving classification code data related to each of the plurality of credit bureaus, the classification code data being used to identify a source type of the raw tradeline data and being in a unique format for each of the credit bureaus;

determining one or more selected tradeline leveling characteristics, the selected tradeline leveling characteristics being used to select a portion of the raw tradeline data from each of the credit bureaus, the determining further comprising;

designating a set of classification code data from the classification code data related to each of the plurality of credit bureaus as the selected tradeline leveling characteristics used to select a portion of the raw tradeline data, the set including a minimum overlap in the classification code data for each of the plurality of credit bureaus;

applying the selected tradeline leveling characteristics to a sample set of the raw tradeline data to select a subset of the sample set of the raw tradeline data to generate respective leveled tradeline data indicating quantities of persons who meet a condition indicated by the respective leveled tradeline data;

determining if the respective leveled tradeline data for the plurality of credit bureaus meets a pre-defined correlation threshold, the determining comprising measuring the differences in the leveled tradeline data; and

adjusting at least one of the selected tradeline leveling characteristics in response to determining that the correlation fails to meet the pre-defined threshold, the adjusting comprising at least one of;

(1) narrowing the selected tradeline leveling characteristics for at least one of the credit bureaus to a smaller subset of the classification code data or (2) including additional classification code data for at least one of the credit bureaus not included in the set of classification code data; and

generating an attribute using the selected tradeline leveling characteristics, the attribute indicating a quantity of persons who meet the condition,

wherein the method is performed by a computing system that comprises one or more computing devices.

2. The computer implemented method of claim 1 wherein determining the one or more selected tradeline leveling characteristics further comprises:

excluding extraneous tradeline data from the leveled tradeline data;

repeating said applying, excluding, determining, and adjusting until the leveled tradeline data derived from the sample set of the raw tradeline data meets the at least one pre-defined correlation threshold.

3. The computer implemented method of claim 1 wherein the plurality of credit bureaus includes at least one of Experian, TransUnion or Equifax.

4. The computer implemented method of claim 1 wherein the classification code data includes industry code identifiers.

5. The computer implemented method of claim 1 wherein the selected tradeline leveling characteristics relate to finance data.

6. The computer implemented method of claim 1 wherein the raw tradeline data relates to at least data from a remote credit database.

7. The computer implemented method of claim 1 wherein the raw tradeline data relates to at least data from a local credit database.

8. The computer implemented method of claim 1 further comprising applying the attribute to individual finance data.

9. A non-transitory storage medium having a computer program stored thereon, the computer program comprising computer-program code for causing a suitably configured computing system to perform the following when the computer program is executed on the system:

retrieving raw tradeline data from each of the plurality of credit bureaus;

retrieving classification code data related to each of the plurality of credit bureaus, the classification code data being used to identify a source type of the raw tradeline data and being in a unique format for each of the credit bureaus;

determining one or more selected tradeline leveling characteristics, the selected tradeline leveling characteristics being used to select a portion of the raw tradeline data from each of the credit bureaus, the determining further comprising;

designating a set of classification code data from the classification code data related to each of the plurality of credit bureaus as the selected tradeline leveling characteristics used to select a portion of the raw tradeline data, the set including a minimum overlap in the classification code data for each of the plurality of credit bureaus;

applying the selected tradeline leveling characteristics to a sample set of the raw tradeline data to select a subset of the sample set of the raw tradeline data to generate respective leveled tradeline data indicating quantities of persons who meet a condition indicated by the respective leveled tradeline data;

determining if the respective leveled tradeline data for the plurality of credit bureaus meets a pre-defined correlation threshold, the determining comprising measuring the differences in the leveled tradeline data; and

adjusting at least one of the selected tradeline leveling characteristics in response to determining that the correlation fails to meet the pre-defined threshold, the adjusting comprising at least one of;

(1) narrowing the selected tradeline leveling characteristics for at least one of the credit bureaus to a smaller subset of the classification code data or (2) including additional classification code data for at least one of the credit bureaus not included in the set of classification code data; and

generating an attribute using the selected tradeline leveling characteristics, the attribute indicating a quantity of persons who meet the condition.

10. A computing system comprising:

a computerized system comprising one or more computing devices configured to execute one or more modules comprising;

a communications module configured to receive raw tradeline data related to a plurality of credit bureaus and to receive classification code data related to each of the plurality of credit bureaus, the classification code data being used to identify a source type of the raw tradeline data and being in a unique format for each of the credit bureaus;

an attribute generation module configured to;

determine one or more selected tradeline leveling characteristics, the selected tradeline leveling characteristics being used to select a portion of the raw tradeline data from each of the credit bureaus, the attribute generation module configured to determine by;

designating a set of classification code data from the classification code data related to each of the plurality of credit bureaus as the selected tradeline leveling characteristics used to select a portion of the raw tradeline data, the set including a minimum overlap in the classification code data for each of the plurality of credit bureaus;

applying the selected tradeline leveling characteristics to a sample set of the raw tradeline data to select a subset of the sample set of the raw tradeline data to generate respective leveled tradeline data indicating quantities of persons who meet a condition indicated by the respective leveled tradeline data;

determining if the respective leveled tradeline data for the plurality of credit bureaus meets a pre-defined correlation threshold, the determining comprising measuring the differences in the leveled tradeline data; and

adjusting at least one of the selected tradeline leveling characteristics in response to determining that the correlation fails to meet the pre-defined threshold, the adjusting comprising at least one of;

(1) narrowing the selected leveling characteristics for at least one of the credit bureaus to a smaller subset of the classification code data or (2) including additional classification code data for at least one of the credit bureaus not included in the set of classification code data; and

generate an attribute using the selected tradeline leveling characteristics, the attribute indicating a quantity of persons who meet the condition, and

a processor module configured to execute the attribute generation module.

11. The computing system of claim 10 wherein the attribute generation module is further configured to determine one or more selected tradeline leveling characteristics by:

excluding extraneous tradeline data from the leveled tradeline data;

repeating said applying, excluding, determining, and adjusting until the leveled tradeline data derived from the sample set of the raw tradeline data meets the pre-defined correlation threshold.

12. The computing system of claim 10 wherein the raw tradeline data is received from at least an internal credit database.

13. The computing system of claim 10 wherein the raw tradeline data is received from at least an external credit database.

14. The computing system of claim 10 wherein the plurality of credit bureaus include at least one of Experian, TransUnion or Equifax.

15. The computing system of claim 10 wherein the classification code data includes industry code identifiers.

16. The computing system of claim 10 wherein the selected tradeline leveling characteristics relate to finance data.

17. The computing system of claim 10 wherein the attribute generation module is further configured to apply the finance attribute to individual finance data.