PAYMENT PORTFOLIO OPTIMIZATION

• US 20090271327A1
• Filed: 04/23/2008
• Published: 10/29/2009
• Est. Priority Date: 04/23/2008
• Status: Abandoned Application

• Current Assignee: Visa USA, Inc. (Visa, Inc.)
• Original Assignee: Visa USA, Inc. (Visa, Inc.)
• Inventors: Rentala, Cindy Y., Lal, Raghav
• Application Number:
  US12/108,354
• Publication Number:
  US 20090271327A1
• Time in Patent Office: Days
• US Class Current: 705/36.R
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A method and system of payment portfolio optimization that retrieves a plurality of consumer segments of a consumer portfolio from a diagnostics module where the consumer segments have potentially profitable opportunities. The method and system also develop a propensity model on a computer based on at least one performance metric, determine a likelihood from the propensity model that consumers in each of the plurality of consumer segments will perform favorably. The method and system also selects a set of consumer segments from the plurality of consumer segments based on the determined likelihood and designs a plurality of marketing treatments for the selected set of consumer segments.

Claims

1. A method for payment portfolio optimization, comprising:

retrieving a plurality of consumer segments of a consumer portfolio from a diagnostics module, the plurality of consumer segments having potentially profitable opportunities;

developing a propensity model on a computer based on at least one performance metric;

determining, using the propensity model, a likelihood that consumers in each of the plurality of consumer segments will perform favorably;

selecting a set of consumer segments from the plurality of consumer segments based on the determined likelihood; and

designing a plurality of marketing treatments for the selected set of consumer segments.

2. The method for payment portfolio optimization of claim 1, further comprising providing to a first issuer a report having the designed plurality of marketing treatments.

3. The method for payment portfolio optimization of claim 1,

testing the designed plurality of marketing treatments;

developing a marketing plan from the designed plurality of marketing treatments based on the testing;

providing a report having the marketing plan to a first issuer.

4. The method for payment portfolio optimization of claim 3,

wherein testing the designed plurality of marketing treatments includes using factorial design.

5. The method for payment portfolio optimization of claim 1, wherein the at least one performance metric comprises penetration, activation, usage, and attrition.

6. The method for payment portfolio optimization of claim 1, wherein one of the designed plurality of marketing treatments is associated with a product for the set of consumer segments.

7. The method for payment portfolio optimization of claim 1, wherein selecting a set of consumer segments from the plurality of consumer segments based on the determined likelihood comprises:

ranking into a plurality of deciles the consumer segments based on the determined likelihood; and

selecting consumer segments in a top tier of deciles from the plurality of deciles.

8. The method for payment portfolio optimization of claim 1, further comprising:

pairing marketing treatments in the designed plurality of marketing treatments;

forming combinations of marketing treatments from the paired marketing treatments;

testing the combinations of marketing treatments;

selecting one of the combinations of marketing treatments based on the testing; and

designing a marketing plan using the selected one of the combinations of marketing treatments.

9. A system of payment portfolio optimization, comprising:

a database storing information; and

a financial modeling module on a computer, the financial modeling module coupled to the database, the financial modeling module configured to;

retrieve a plurality of consumer segments of a consumer portfolio from a diagnostics module, the plurality of consumer segments having profitable opportunities;

develop a propensity model based on at least one performance metric;

determine, using the propensity model, a likelihood that consumers in each of the plurality of consumer segments will perform favorably;

select a set of consumer segments from the plurality of consumer segments based on the determined likelihood; and

design a plurality of marketing treatments for the selected set of consumer segments.

10. The system of payment portfolio optimization of claim 9, wherein the financial modeling module is further configured to provide to a first issuer a report having the designed plurality of marketing treatments.

11. The system of payment portfolio optimization of claim 9, wherein the financial modeling module is further configured to:

test the designed plurality of marketing treatments;

develop a marketing plan from the designed plurality of marketing treatments based on the testing;

provide a report having the marketing plan to a first issuer.

12. The system of payment portfolio optimization of claim 11, wherein the financial modeling module is configured to test the designed plurality of marketing treatments includes using factorial design.

13. The system of payment portfolio optimization of claim 9, wherein the at least one performance metric comprises penetration, activation, usage, and attrition.

14. The system of payment portfolio optimization of claim 9, wherein one of the designed plurality of marketing treatments is associated with a product for the set of consumer segments.

15. The system of payment portfolio optimization of claim 9, wherein the financial modeling module configured to select a set of consumer segments from the plurality of consumer segments based on the determined likelihood is configured to:

rank into a plurality of deciles the consumer segments based on the determined likelihood; and

select consumer segments in a top tier of deciles from the plurality of deciles.

16. The system of payment portfolio optimization of claim 9, wherein the financial modeling module is further configured to:

pair marketing treatments in the designed plurality of marketing treatments;

form combinations of marketing treatments from the paired marketing treatments;

test the combinations of marketing treatments;

select one of the combinations of marketing treatments based on the testing; and

design a marketing plan using the selected one of the combinations of marketing treatments.