Method and apparatus for obtaining, organizing, and analyzing multi-source data

• US 8,271,364 B2
• Filed: 06/09/2005
• Issued: 09/18/2012
• Est. Priority Date: 06/09/2005
• Status: Active Grant

• Current Assignee: Bank of America Corp.
• Original Assignee: Bank of America Corp.
• Inventors: Nobili, William A., Bonn, Michael S.
• Primary Examiner(s): ROSEN, ELIZABETH H
• Application Number:
  US11/160,117
• Publication Number:
  US 20060282359A1
• Time in Patent Office: 2,658 Days
• Field of Search: None
• 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

The tool of the invention is a data gathering and analytical process that uses internal customer data and external CRA data to build a consumer credit market data base and data structure. The internal customer data is classified according to identified Customer Attributes, the CRA data is also classified according to identified Consumer Attributes and the combined data is further classified according to additional Value Added Attributes. The resulting data structure is organized at the individual level such that each individual has associated therewith values for each of the Customer Attributes, Consumer Attributes and Value Added Attributes. The resulting analysis can be used to set institutional strategies and/or to make predictive decisions on individual borrower credit requests.

Claims

1. A system for creating a credit market database for a first institution, wherein the system populates the credit market database with information about customers and consumers, wherein customers are individuals that have an existing relationship with the first institution and consumers are individuals that have an existing relationship with a second institution, the system comprising:

a communication device;

a memory device in communication with the communication device and comprising customer attribute data stored therein, wherein the customer attribute data comprises a plurality of customer entries, each entry of the plurality of customer entries represents a customer and includes at least one customer-relationship attribute; and

a processing device in communication with the communication device and the memory device, wherein the processing device is configured to;

use the communication device to;

receive the at least one customer-relationship attribute, wherein the customer-relationship attribute is selected by the first institution and defines an aspect of the relationship between the first institution and its customers;

receive a plurality of customer values, each corresponding to one or more of the first institution'"'"'s customers, each customer value representing at least one customer-relationship attribute of each customer;

receive criteria that define a consumer type, wherein the first institution selects the criteria;

request a list of consumers based on the criteria, wherein each of the listed consumers matches the consumer type and wherein each of the listed consumers is an individual that has a relationship with the second institution;

receive the list of consumers as well as information about each of the listed consumers;

receive a consumer-relationship attribute that defines at least one aspect of the relationship between the listed consumers and the second institution, wherein the first institution selects the consumer-relationship attribute so that the system will populate the credit market database with information about the aspect of the relationship between the listed consumers and the second institution that is of interest to the first institution; and

receive a plurality of consumer values, each corresponding to one or more of the listed consumers, each consumer value representing at least one consumer-relationship attribute of each listed consumer; and

the processing device further configured to;

determine a value of a value-added attribute corresponding to the customer-relationship attribute, wherein the value-added attribute corresponding to the customer-relationship attribute represents the total value of the customer-relationship attribute across all of the first institution'"'"'s customers, the determining comprising;

determining a weighted value at least in part by adjusting the customer values based on one or more scaling factors thereby creating weighted customer values, and

summing one or more of the weighted customer values;

determine a value of a value-added attribute corresponding to the consumer-relationship attribute, wherein the value-added attribute represents the total value of the consumer-relationship attribute across all of the listed consumers, the determining comprising;

determining a weighted value at least in part by adjusting the consumer values based on one or more scaling factors thereby creating weighted consumer values, and

summing one or more of the weighted consumer values;

develop the credit market database by;

for each individual that is a customer but not a consumer, populate the credit market database with the value that represents the individual'"'"'s customer-relationship attribute and the value that represents the value-added attribute corresponding to the customer-relationship attribute;

for each individual that is a consumer but not a customer, populate the credit market database with the value that represents the individual'"'"'s consumer-relationship attribute and the value that represents the value-added attribute corresponding to the consumer-relationship attribute; and

for each individual that is both a consumer and a customer, populate the credit market database with the value that represents the individual'"'"'s customer-relationship attribute, the value that represents individual'"'"'s consumer-relationship attribute, the value that represents the value-added attribute corresponding to the customer-relationship attribute, and the value that represents the value-added attribute corresponding to the consumer-relationship attribute.

2. The system of claim 1, wherein the list of consumers includes individuals that have relationships with all institutions in a relevant market.

3. The system of claim 1, wherein the list of consumers that match the consumer type as well as the information about each listed consumer are received from a credit bureau.

4. The system of claim 1, wherein the criteria define a random sample of all consumers known to the credit bureau.

5. The system of claim 1, wherein the value that represents a customer'"'"'s customer-relationship attribute is determined based on information stored in a customer-data file, which is maintained by the first institution.

6. The system of claim 1, wherein one or more of the scaling factors comprises a scaling-up factor representative of a portion of the entire market.

7. The system of claim 6, wherein the scaling-up factor is representative of an entire consumer market.

8. The system of claim 1, wherein one or more of the scaling factors comprises a scaling-down factor.

9. The system of claim 8, wherein the scaling-down factor is configured to account for duplicative data.

10. The system of claim 8, wherein one or more of the scaling factors comprises a scaling-up factor.

11. The system of claim 10, wherein one of the scaling factors comprises both a scaling-down factor and a scaling-up factor.

12. The system of claim 1, wherein, during determining a value of a value-added attribute corresponding to the customer-relationship attribute, the processing device is further configured to:

divide the weighted and summed customer values in order to determine an average weighted customer value and thereby the value of the value-added attribute corresponding to the customer-relationship attribute.

13. The system of claim 1, wherein, during determining a value of a value-added attribute corresponding to the consumer-relationship attribute, the processing device is further configured to:

divide the weighted and summed consumer values in order to determine an average weighted consumer value and thereby the value of the value-added attribute corresponding to the consumer-relationship attribute.

14. The system of claim 1, wherein, during determining a value of a value-added attribute corresponding to the customer-relationship attribute, the processing device is further configured to:

divide the weighted and summed customer values in order to determine an average weighted customer value and thereby the value of the value-added attribute corresponding to the customer-relationship attribute; and

wherein, during determining a value of a value-added attribute corresponding to the consumer-relationship attribute, the processing device is further configured to;

divide the weighted and summed consumer values in order to determine an average weighted consumer value and thereby the value of the value-added attribute corresponding to the consumer-relationship attribute.

15. The system of claim 1, wherein the system is further configured to analyze the credit market database, wherein the processing device is further configured to:

compare the value for the customer-relationship attribute with the value for the value-added attribute corresponding to the customer-relationship attribute in order to demonstrate a relationship between the customer'"'"'s behavior versus the total market behavior, thereby providing information useful for future product marketing.

16. The system of claim 1, wherein the system is further configured to analyze the credit market database, wherein the processing device is further configured to:

compare the value for the consumer-relationship attribute with the value for the value-added attribute corresponding to the consumer-relationship attribute in order to demonstrate a relationship between the consumer'"'"'s behavior versus the total market behavior, thereby providing information useful for future product marketing.

17. The system of claim 1, wherein the system is further configured to analyze the credit market database, wherein the processing device is further configured to:

compare the value for the customer-relationship attribute with the value for the value-added attribute corresponding to the customer-relationship attribute in order to demonstrate a relationship between the customer'"'"'s behavior versus the total market behavior;

compare the value for the consumer-relationship attribute with the value for the value-added attribute corresponding to the consumer-relationship attribute in order to demonstrate a relationship between the consumer'"'"'s behavior versus the total market behavior; and

compare the customer'"'"'s behavior versus the total market behavior and the consumer'"'"'s behavior versus the total market behavior, thereby providing information useful for future product marketing.