Industry size of wallet

• US 8,615,458 B2
• Filed: 02/25/2013
• Issued: 12/24/2013
• Est. Priority Date: 12/01/2006
• Status: Active Grant

• Current Assignee: American Express Travel Related Services Company, Inc. (American Express Company)
• Original Assignee: American Express Travel Related Services Company, Inc. (American Express Company)
• Inventors: Kalia, Prashant, Crotty, Karlyn Heiner, Fusillo, Iwao
• Primary Examiner(s): Nguyen, Nga B.
• Application Number:
  US13/776,178
• Publication Number:
  US 20130191262A1
• Time in Patent Office: 302 Days
• Field of Search: 705/35, 705/36.R, 705/37
• US Class Current: 705/35
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Abstract

Consumer spend by industry is modeled based on the industry sizes of wallet of consumers having a high share of wallet with a financial institution. A size of wallet is calculated for each consumer in a plurality of consumers. A share of wallet for each consumer is also calculated. A subset of the plurality of consumers whose share of wallet is above a given percentage of their size of wallet is then determined. For each consumer in the subset, an industry size of wallet is determined. A correlation between the industry size of wallet of a given consumer and one or more characteristics of the given consumer is then derived using the industry size of wallet for the consumers in the subset.

Claims

1. A method comprising:

calculating, by a computer-based system for modeling consumer spend comprising a processor and a tangible, non-transitory memory, a size of wallet for each consumer in a plurality of consumers; and

determining, by the computer-based system, an industry size of wallet for each consumer using a fixed weighting factor and a graded weighting factor in conjunction with lifestyle variables comprising at least one of a location rank, a length of each consumer'"'"'s tenure with a credit bureau, each consumer'"'"'s gender, and each consumer'"'"'s household size, wherein the graded weighting factor varies in accordance with the value of at least one of the lifestyle variables.

2. The method of claim 1, wherein the calculating the size of wallet for each consumer in the plurality of consumers comprises modeling, by the computer-based system, spending patterns using internal customer data and consumer panel data.

3. The method of claim 1, wherein the calculating the size of wallet for each consumer in the plurality of consumers comprises estimating, by the computer-based system, credit-related information of each consumer based on tradeline data of each consumer, previous balance transfers of each consumer, and a model of consumer spending patterns to arrive at estimated credit-related information.

4. The method of claim 3, wherein the calculating the size of wallet for each consumer in the plurality of consumers further comprises offsetting, by the computer-based system, the previous balance transfers from the estimated credit-related information.

5. The method of claim 1, further comprising:

calculating the share of wallet comprises calculating a share of wallet associated with a given financial institution; and

determining a subset of the plurality of consumers comprises identifying consumers whose share of wallet associated with the financial institution is greater than approximately 90%.

6. The method of claim 1, wherein the determining an industry size of wallet comprises:

determining the amount of spend within the industry using one or more accounts associated with a financial institution; and

equating the amount of spend within the industry with the industry size of wallet.

7. The method of claim 1, further comprising:

determining, by the computer-based system, a subset of the plurality of consumers whose share of wallet is above a given percentage of their size of wallet;

deriving, by the computer-based system, a correlation between an industry size of wallet for a given consumer and one or more characteristics of the given consumer using the industry size of wallet for the consumers in the subset,

wherein the characteristics of the consumer include at least one of;

total size of wallet of the consumer;

residence location;

credit bureau tenure;

age;

gender;

household size; and

number of active transaction cards in a household of the consumer.

8. The method of claim 7, wherein the deriving a correlation comprises:

identifying consumers having substantially similar industry sizes of wallet; and

examining spend habits of the identified consumers to ascertain common characteristics that influence spend in the industry.

9. The method of claim 1, wherein the industry is at least one of a travel industry, a restaurant industry, or an everyday spend industry.

10. The method of claim 1, wherein the industry is at least one of an airline industry, a lodging industry, or a vehicle rental industry.

11. The method of claim 7, further comprising developing a model based on correlations between the industry size of wallet and the characteristics of the consumer.

12. A method comprising:

calculating, by a computer-based system for targeting consumers comprising a processor and a tangible, non-transitory memory, a total share of wallet associated with a financial institution for one or more consumers;

estimating, by the computer-based system, an industry size of wallet of each consumer; and

calculating, by the computer-based system, an external size of the industry size of wallet of each consumer using a fixed weighting factor and a graded weighting factor in conjunction with lifestyle variables comprising at least one of a location rank, a length of each consumer'"'"'s tenure with a credit bureau, each consumer'"'"'s gender, and each consumer'"'"'s household size, wherein the graded weighting factor varies in accordance with the value of at least one of the lifestyle variables.

13. The method of claim 12, wherein the industry size of wallet of each consumer is calculated by modeling, by the computer-based system, spending patterns using internal customer data, and consumer panel data.

14. The method of claim 12, wherein the industry size of wallet of each consumer is calculated by:

estimating, by the computer-based system, credit-related information of each consumer based on tradeline data of each consumer, previous balance transfers of each consumer, and a model of consumer spending patterns to arrive at estimated credit-related information; and

offsetting, by the computer-based system, the previous balance transfers from the estimated credit-related information.

15. The method of claim 12, further comprising targeting, by the computer-based system, one or more consumers having a relatively high external size of the industry size of wallet and a given minimal total share of wallet with offers to increase an industry share of wallet associated with the financial institution.

16. The method of claim 12, wherein the calculating an external size of the industry size of wallet of the consumer comprises subtracting industry spend of the consumer associated with the financial institution from the industry size of wallet of the consumer.

17. The method of claim 12, wherein the calculating an external size of the industry size of wallet of the consumer further comprises determining the amount of industry spend of the consumer associated with the financial institution from internal records of the financial institution.

18. The method of claim 15, wherein the targeting comprises targeting the consumer with an offer for a new product.

19. The method of claim 15, wherein the targeting one or more consumers comprises targeting the consumer with an incentive to increase spending on an existing product associated with the financial institution.

20. A computer readable storage medium bearing instructions, the instructions, when executed by a processor for modeling consumer spend by industry, cause said processor to perform operations comprising:

calculating, by the processor, a size of wallet for each consumer in a plurality of consumers; and

determining, by the processor, an industry size of wallet for each consumer using a fixed weighting factor and a graded weighting factor in conjunction with lifestyle variables comprising at least one of a location rank, a length of each consumer'"'"'s tenure with a credit bureau, each consumer'"'"'s gender, and each consumer'"'"'s household size, wherein the graded weighting factor varies in accordance with the value of at least one of the lifestyle variables.