Method and apparatus for determining credit characteristics of a consumer

• US 20080221972A1
• Filed: 10/25/2007
• Published: 09/11/2008
• Est. Priority Date: 10/24/2005
• Status: Abandoned Application

• Current Assignee: Experian Marketing Solutions Incorporated (Experian plc)
• Original Assignee: Experian Marketing Solutions Incorporated (Experian plc)
• Inventors: Granger, Angela, Kornegay, Adam T., Megdal, Myles G.
• Application Number:
  US11/977,753
• Publication Number:
  US 20080221972A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• 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
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumers spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. The outputs include the size of the consumer'"'"'s spending wallet over a particular time period, the total number of the consumer'"'"'s revolving cards, the consumer'"'"'s revolving balance, the consumer'"'"'s average pay-down percentage for revolving cards, total number of the consumer'"'"'s transacting cards, the consumer'"'"'s transacting balance, a number of balance transfers transacted by the consumer, the total amount of the consumer'"'"'s balance transfers, the consumer'"'"'s maximum revolving balance, the consumer'"'"'s maximum transacting balance, the consumer'"'"'s credit limit, size of the consumer'"'"'s revolving spending, and the size of the consumer'"'"'s transacting spending.

Claims

1. A method of managing a consumer lifecycle in a credit-related industry, comprising:

(a) modeling consumer spending patterns using individual and aggregate consumer data, including tradeline data, internal customer data, and consumer panel data;

(b) estimating a credit-related characteristic of an individual consumer based on tradeline data of the individual consumer, balance transfers of the individual consumer, and the model of consumer spending patterns; and

(c) outputting the credit-related characteristic of the individual consumer.

2. The method of claim 1, wherein the credit-related characteristic is a size of the individual consumer'"'"'s spending wallet.

3. The method of claim 2, wherein the spending wallet is a twelve-month spending wallet.

4. The method of claim 2, wherein the spending wallet is a quarterly spending wallet.

5. The method of claim 2, wherein the size of the spending wallet is output as a monetary amount.

6. The method of claim 1, wherein the credit-related characteristic is a consumer'"'"'s average pay-down percentage of revolving cards.

7. The method of claim 1, wherein the credit-related characteristic is a size of the consumer'"'"'s revolving spending.

8. The method of claim 1, wherein the credit-related characteristic is a size of the consumer'"'"'s transacting spending.

9. The method of claim 1, wherein the credit-related characteristic is a share of wallet size for a particular spend category.

10. The method of claim 9, wherein the particular spend category is plastic spend.

11. The method of claim 1, wherein the credit-related characteristic is a spend capacity of the consumer.

12. The method of claim 1, wherein the spend capacity of the consumer is a plastic spend capacity.

13. The method of claim 1, wherein the credit-related characteristic is an amount of balance transfers transacted by the consumer.

14. An apparatus for managing a consumer lifecycle in a credit-related industry, comprising:

a processor; and

a memory in communication with the processor, wherein the memory stores a plurality of processing instructions for directing the processor to;

model consumer spending patterns using individual and aggregate consumer data, including tradeline data, internal customer data, and consumer panel data;

estimate a credit-related characteristic of an individual consumer based on tradeline data of the individual consumer, balance transfers of the individual consumer, and the model of consumer spending patterns;

and output the credit-related characteristic of the individual consumer.

15. The apparatus of claim 14, wherein the credit-related characteristic is a size of the individual consumer'"'"'s spending wallet.

16. The apparatus of claim 15, wherein the spending wallet is a twelve-month spending wallet.

17. The apparatus of claim 15, wherein the spending wallet is a quarterly spending wallet.

18. The apparatus of claim 15, wherein the size of the spending wallet is output as a monetary amount.

19. The apparatus of claim 14, wherein the credit-related characteristic is a consumer'"'"'s average pay-down percentage of revolving cards.

20. The apparatus of claim 14, wherein the credit-related characteristic is a size of the consumer'"'"'s revolving spending.

21. The apparatus of claim 14, wherein the credit-related characteristic is a size of the consumer'"'"'s transacting spending.

22. The apparatus of claim 14, wherein the credit-related characteristic is a share of wallet size for a particular spend category.

23. The apparatus of claim 22, wherein the particular spend category is plastic spend.

24. The apparatus of claim 14, wherein the credit-related characteristic is a spend capacity of the consumer.

25. The apparatus of claim 24, wherein the spend capacity of the consumer is a plastic spend capacity.

26. The apparatus of claim 14, wherein the credit-related characteristic is an amount of balance transfers transacted by the consumer.

27. A computer program product comprising a computer usable medium having control logic stored therein for causing a computer to manage a consumer lifecycle in a credit-related industry, the control logic comprising:

first computer readable program code means for causing the computer to model consumer spending patterns using individual and aggregate consumer data, including tradeline data, internal customer data, and consumer panel data;

second computer readable program code means for causing the computer to estimate a credit-related characteristic of an individual consumer based on tradeline data of the individual consumer, balance transfers of the individual consumer, and the model of consumer spending patterns; and

third computer readable program code means for causing the computer to output the credit-related characteristic of the individual consumer.

28. The computer program product of claim 27, wherein the credit-related characteristic is a size of the individual consumer'"'"'s spending wallet.

29. The computer program product of claim 28, wherein the spending wallet is a twelve-month spending wallet.

30. The computer program product of claim 28, wherein the spending wallet is a quarterly spending wallet.

31. The computer program product of claim 28, wherein the size of the spending wallet is output as a monetary amount.

32. The computer program product of claim 27, wherein the credit-related characteristic is a consumer'"'"'s average pay-down percentage of revolving cards.

33. The computer program product of claim 27, wherein the credit-related characteristic is a size of the consumer'"'"'s revolving spending.

34. The computer program product of claim 27, wherein the credit-related characteristic is a size of the consumer'"'"'s transacting spending.

35. The computer program product of claim 27, wherein the credit-related characteristic is a share of wallet size for a particular spend category.

36. The computer program product of claim 35, wherein the particular spend category is plastic spend.

37. The computer program product of claim 27, wherein the credit-related characteristic is a spend capacity of the consumer.

38. The computer program product of claim 37, wherein the spend capacity of the consumer is a plastic spend capacity.

39. The computer program product of claim 27, wherein the credit-related characteristic is an amount of balance transfers transacted by the consumer.