CONSUMER BEHAVIORS AT LENDER LEVEL

• US 20090248573A1
• Filed: 03/28/2008
• Published: 10/01/2009
• Est. Priority Date: 03/28/2008
• Status: Abandoned Application

• 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: Sahu, Prasanta, Xu, Di, Haggerty, Kathleen, Yuan, Chao, Prakash, Aashish
• Application Number:
  US12/058,431
• Publication Number:
  US 20090248573A1
• Time in Patent Office: Days
• US Class Current: 705/38
• 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 40/03 Credit; Loans; Processing thereof

Abstract

The present invention generally relates to financial data processing, and in particular it relates to lender credit scoring, lender profiling, lender behavior analysis and modeling. More specifically, it relates to rating lenders based on data derived from their respective consumers. Also, the present invention relates to rating consumer lenders based on the predicted spend capacity of their consumers.

Claims

1. An account default prediction method comprising:

obtaining a first consumer default risk factor associated with a first consumer;

acquiring first credit card data associated with a first consumer, wherein said first credit card data is associated with a first lender;

obtaining a second consumer default risk factor associated with a second consumer;

acquiring second credit card data associated with a second consumer, wherein said second credit card data is associated with a first lender;

calculating a first lender default risk factor based upon said first consumer default risk factor and said second consumer default risk factor;

obtaining a third consumer default risk factor associated with a third consumer;

acquiring third credit card data associated with a third consumer, wherein said third credit card data is associated with a second lender;

obtaining a fourth consumer default risk factor associated with a fourth consumer;

acquiring fourth credit card data associated with a fourth consumer, wherein said fourth credit card data is associated with said second lender;

calculating a second lender default risk factor based upon said third consumer default risk factor and said fourth consumer default risk factor; and

ranking said first lender and said second lender based on said first lender default risk factor and said second lender default risk factor to create a default risk factor ranking.

2. The method of claim 1, further comprising:

receiving a request from a fifth consumer for an account;

determining when said fifth consumer is associated with at least one;

said first lender and said second lender; and

determining said account default prediction based upon said association of said fifth consumer with at least one;

said first lender and said second lender.

3. The method of claim 2, further comprising:

determining first insufficiencies with said first credit card data;

determining second insufficiencies with said second credit card data;

determining third insufficiencies with said third credit card data;

determining fourth insufficiencies with said fourth credit card data;

grouping said first insufficiencies and said second insufficiencies to create first lender insufficiencies;

grouping said third insufficiencies and said fourth insufficiencies to create second lender insufficiencies;

ranking said first lender and said second lender based on said first lender insufficiencies and said second lender insufficiencies to create an insufficiency ranking;

creating a final risk index based upon said default risk factor ranking and said insufficiency ranking; and

wherein said step of determining said account default prediction further comprises using said final risk index.

4. The method of claim 3, further comprising:

receiving a request from a fifth consumer for an account;

determining when said fifth consumer is associated with at least one;

said first lender and said second lender; and

determining said account default prediction based upon said association of said fifth consumer with at least one;

said first lender and said second lender.

5. The method of claim 2, further comprising, determining a strategy to interact with said fifth consumer based upon said association of said fifth consumer with at least one:

said first lender and said second lender.

6. The method of claim 4, further comprising, determining a strategy to interact with said fifth consumer based upon said association of said fifth consumer with at least one:

said first lender and said second lender.

7. The method of claim 5, wherein said strategy further comprises making credit approval decisions for said consumer based upon said association of said fifth consumer with at least one:

said first lender and said second lender.

8. The method of claim 6, wherein said strategy further comprises making credit approval decisions for said consumer based upon said association of said fifth consumer with at least one:

said first lender and said second lender.

9. The method of claim 5, wherein said strategy further comprises discontinuing relationship with said consumer upon said association of said fifth consumer with at least one:

said first lender and said second lender.

10. The method of claim 6, wherein said strategy further comprises discontinuing relationship with said consumer upon said association of said fifth consumer with at least one:

said first lender and said second lender.

11. The method of claim 5, wherein said strategy further comprises soliciting said consumer for additional products in accordance with association of said fifth consumer with at least one:

said first lender and said second lender.

12. The method of claim 6, wherein said strategy further comprises soliciting said consumer for additional products in accordance with association of said fifth consumer with at least one:

said first lender and said second lender.

13. The method of claim 1, wherein said obtaining a first consumer default risk factor further comprises calculating a comprehensive consumer default risk value.

14. The method of claim 13, wherein said calculating a comprehensive consumer default risk value further comprises:

obtaining consumer credit data relating to said first consumer;

modeling consumer spending patterns of said first consumer using said consumer credit data to obtain an estimated spend capacity of said first consumer; and

calculating a comprehensive consumer default risk value for said first consumer based upon said consumer credit data and said estimated spend capacity.

15. The method of claim 14, wherein said calculating a comprehensive consumer default risk value further comprises:

obtaining internal data relating to said first consumer; and

further calculating said comprehensive consumer default risk value for said first consumer based upon said consumer credit data, said internal data and said estimated spend capacity.

16. A consumer spend prediction comprising:

obtaining a first consumer spending pattern associated with a first consumer;

acquiring first credit card data associated with a first consumer, wherein said first credit card data is associated with a first lender;

obtaining a second consumer spending pattern associated with a second consumer;

acquiring second credit card data associated with a second consumer, wherein said second credit card data is associated with a first lender;

calculating a first lender spending pattern based upon said first consumer spending pattern and said second consumer spending pattern;

obtaining a third consumer spending pattern associated with a third consumer;

acquiring third credit card data associated with a third consumer, wherein said third credit card data is associated with a second lender;

obtaining a fourth consumer spending pattern associated with a fourth consumer;

acquiring fourth credit card data associated with a fourth consumer, wherein said fourth credit card data is associated with said second lender;

calculating a second lender spending pattern based upon said third consumer spending pattern and said fourth consumer spending pattern; and

ranking said first lender and said second lender based on said first lender spending pattern and said second lender spending pattern to create a lender spending pattern ranking.

17. The method of claim 16, further comprising

receiving a request from a fifth consumer for an account;

determining when said fifth consumer is associated with at least one;

said first lender and said second lender; and

determining said consumer spend prediction based upon said association of said fifth consumer with at least one;

said first lender and said second lender.

18. A computer readable medium bearing instructions for calculating an account default prediction, the instructions, when executed, being arranged to cause one or more processors to perform the steps of:

obtaining a first consumer default risk factor associated with a first consumer;

acquiring first credit card data associated with a first consumer, wherein said first credit card data is associated with a first lender;

obtaining a second consumer default risk factor associated with a second consumer;

acquiring second credit card data associated with a second consumer, wherein said second credit card data is associated with a first lender;

calculating a first lender default risk factor based upon said first consumer default risk factor and said second consumer default risk factor;

obtaining a third consumer default risk factor associated with a third consumer;

acquiring third credit card data associated with a third consumer, wherein said third credit card data is associated with a second lender;

obtaining a fourth consumer default risk factor associated with a fourth consumer;

acquiring fourth credit card data associated with a fourth consumer, wherein said fourth credit card data is associated with said second lender;

calculating a second lender default risk factor based upon said third consumer default risk factor and said fourth consumer default risk factor; and

ranking said first lender and said second lender based on said first lender default risk factor and said second lender default risk factor to create a default risk factor ranking.

19. The computer readable medium of claim 18 further comprising:

receiving a request from a fifth consumer for an account;

determining when said fifth consumer is associated with at least one;

said first lender and said second lender; and

determining said account default prediction based upon said association of said fifth consumer with at least one;

said first lender and said second lender.

20. The computer readable medium of claim 18 further comprising:

determining first insufficiencies with said first credit card data determining second insufficiencies with said second credit card data;

determining third insufficiencies with said third credit card data;

determining fourth insufficiencies with said fourth credit card data;

grouping said first insufficiencies and said second insufficiencies to create first lender insufficiencies;

grouping said third insufficiencies and said fourth insufficiencies to create second lender insufficiencies;

ranking said first lender and said second lender based on said first lender insufficiencies and said second lender insufficiencies to create an insufficiency ranking;

creating a final risk index based upon said default risk factor ranking and said insufficiency ranking; and

wherein said step of determining said account default prediction further comprises using said final risk index.