METHOD AND SYSTEM FOR EVALUATING CUSTOMERS OF A FINANCIAL INSTITUTION USING CUSTOMER RELATIONSHIP VALUE TAGS

• US 20080208677A1
• Filed: 04/29/2008
• Published: 08/28/2008
• Est. Priority Date: 08/19/1997
• Status: Active Grant

• Current Assignee: Citibank NA (Citigroup Incorporated), Fair Isaac Corporation
• Original Assignee: Fair Isaac Corporation
• Inventors: Lin, Yinghua, Coggeshall, Stephen V., Mayr, Mona, Wu, Guowei, Walker, Darcy
• Granted Patent: US 8,600,854 B2
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Abstract

A computerized method and system for evaluating customers of a financial institution using customer relationship value tags associated customer treatment actions includes automatically analyzing information about a customer from a database of the financial institution by a customer assessment engine using a predefined statistical model to assess the value of the customer to the financial institution. At least one customer treatment action associated with the assessed value is identified by the assessment engine, and the assessment engine marks a file associated with the customer with a mark representing the assessed value and the associated customer treatment action. The marked file is then accessed by other financial systems of the financial institution, or by customer representatives of the financial institution, and the associated customer treatment action is implemented by such systems or representatives in dealing with the customer.

Claims

1. A computer-implemented method comprising:

determining present and future values for a plurality of customers of a financial institution, the present values characterizing a current value of a customer to the financial institution, the future values characterizing a forecasted value of a customer to the financial institution;

segmenting the plurality of customers into a set of groups based on the determined values;

first modeling each of a first subset of the set of groups using acquisition decision processes of the financial institution;

second modeling each of a second subset of the set of groups using value-based decision processes of the financial institution; and

characterizing performance of the acquisition decision processes and the value-based decision processes based on the first and second modeling.

2. A method as in claim 1, wherein the present value is a weighted average value for the customer over a predefined time period.

3. A method as in claim 1, wherein the present value for a customer is a sum all of present values of the customer'"'"'s products less total transaction products for such products.

4. A method as in claim 1 further comprising:

modifying data records associated with each customer to include value tags characterizing the corresponding present and future values.

5. A method as in claim 1 further comprising:

initiating customer treatment actions based on the characterized performance.

6. A method as in claim 1 further comprising:

generating a report characterizing the performance of the of the acquisition decision processes and the value-based decision processes.

7. A method as in claim 1, wherein the financial institution is a bank.

8. A computer program product tangibly embodied on computer storage media comprising instructions to execute operations comprising:

determining present and future values for a plurality of customers of a financial institution, the present values characterizing a current value of a customer to the financial institution, the future values characterizing a forecasted value of a customer to the financial institution;

segmenting the plurality of customers into a set of groups based on the determined values;

first modeling each of a first subset of the set of groups using acquisition decision processes of the financial institution;

second modeling each of a second subset of the set of groups using value-based decision processes of the financial institution; and

characterizing performance of the acquisition decision processes and the value-based decision processes based on the first and second modeling.

9. A computer program product as in claim 8, wherein the present value is a weighted average value for the customer over a predefined time period.

10. A computer program product as in claim 8, wherein the present value for a customer is a sum all of present values of the customer'"'"'s products less total transaction products for such products.

11. A computer program product as in claim 8, further comprising instructions to execute operations comprising:

modifying data records associated with each customer to include value tags characterizing the corresponding present and future values.

12. A computer program product as in claim 8, further comprising instructions to execute operations comprising:

initiating customer treatment actions based on the characterized performance.

13. A computer program product as in claim 8, further comprising instructions to execute operations comprising:

generating a report characterizing the performance of the of the acquisition decision processes and the value-based decision processes.

14. A computer program product as in claim 8, wherein the financial institution is a bank.

15. A computer-implemented method comprising:

accessing a remote database to obtain a value tag characterizing a first value for a customer of a financial institution, the first value being based on an assessed value for the customer less transaction costs associated with products of the financial institution held by the customer;

associating the customer with at least one customer treatment action based on the value tag; and

initiating the at least one customer treatment action.

16. A method as in claim 15, wherein the accessing comprises polling the remote database via the Internet.

17. A method as in claim 15, wherein the financial institution is a bank.

18. A method as in claim 15, wherein at least one of the products is a loan product.

19. A method as in claim 15, wherein the value tag further characterizes a second value for the customer of the financial institution.

20. A method as in claim 19, wherein the second value is based on a segment associated with the customer, the segment being determined by the first value and including a set of variables each with an associated coefficient, the second value being based on a sum a product of each of the variables and the associated coefficient, and wherein the at least one customer treatment action is associated based on the first value and the second value.