Total structural risk model

• US 7,849,004 B2
• Filed: 02/29/2008
• Issued: 12/07/2010
• Est. Priority Date: 02/29/2008
• 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: Choudhuri, Tirthankar, Xu, Di, Haggerty, Kathleen, Gupta, Amber, Yuan, Chao, Dewan, Anjali
• Primary Examiner(s): Cheung; Mary
• Assistant Examiner(s): Nguyen; Tien C
• Application Number:
  US12/040,757
• Publication Number:
  US 20090222374A1
• Time in Patent Office: 1,012 Days
• Field of Search: 210/605, 273/274, 700/99, 705 10- 45, 707/694, 707/810, 709/203
• US Class Current: 705/38
• 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
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

The present invention generally relates to financial data processing, and in particular it relates to credit scoring, consumer profiling, consumer behavior analysis and modeling. More specifically, it relates to risk modeling using the inputs of credit bureau data, size of wallet data, and, optionally, internal data.

Claims

1. A method for determining a comprehensive consumer default risk value for a consumer, wherein said consumer default risk value is derived by a risk analysis computer, said method comprising:

obtaining consumer credit data relating to said consumer, at a risk analysis computer wherein said risk analysis computer comprises a processor, a memory, and a data store;

modeling, by said risk analysis computer, consumer spending patterns of said consumer using said consumer credit data to obtain an estimated spend capacity of said consumer;

obtaining, by said risk analysis computer, internal data relating to said consumer, said internal data comprising consumer transactional data;

calculating, by said risk analysis computer, said comprehensive consumer default risk value for said consumer based upon said consumer credit data, said internal data and said estimated spend capacity, wherein said comprehensive consumer default risk value represents a risk associated with said consumer defaulting on an existing debt obligation and

wherein said calculating comprises

assigning, by said risk analysis computer, said consumer to a consumer population segment based upon primary residence value,

selecting, by said risk analysis computer, an appropriate risk factor relationship based upon said consumer credit data and said internal data.

2. The method of claim 1, further comprising determining a strategy to interact with said consumer based on said comprehensive consumer default risk value for said consumer.

3. The method of claim 2, wherein said determining a strategy further comprises making credit approval decisions for said consumer based upon said comprehensive consumer default risk value.

4. The method of claim 2, wherein said determining a strategy further comprises soliciting said consumer for additional products in accordance with said comprehensive consumer default risk value.

5. The method of claim 2, wherein said determining a strategy further comprises discontinuing a relationship with said consumer based upon said comprehensive consumer default risk value.

6. The method of claim 5 wherein said modeling consumer spending patterns further comprises:

identifying , using said risk analysis computer, at least two categories wherein a first category includes consumers that primarily pay down credit account balances and a second category including consumers that primarily revolve credit account balances; and

assigning, using said risk analysis computer, said consumer to at least one of said categories.

7. The method of claim 5, further comprising establishing a new mortgage based upon said comprehensive consumer default risk value.

8. The method of claim 1, further comprising establishing at least one of a new credit card account, a new mortgage, and a new automobile loan based upon said comprehensive consumer default risk value.

9. The method of claim 1, further comprising establishing a new student loan based upon said comprehensive consumer default risk value.

10. The method of claim 1 wherein said modeling consumer spending patterns further comprises:

receiving, using said risk analysis computer, credit bureau data comprising a plurality of accounts of said consumer over a previous period of time;

identifying, using said risk analysis computer, any balance transfers into at least one of said plurality of accounts based upon said credit bureau data;

discounting, using said risk analysis computer, any spending identified for any of said plurality of accounts for any portion of said previous period of time in which a balance transfer to such account is identified; and

estimating , using said risk analysis computer, a purchasing ability of said consumer based on said credit bureau data and said discounting.

11. The method of claim 10, further comprising determining, using said risk analysis computer, a strategy to interact with said consumer based on said comprehensive consumer default risk value for said consumer.

12. The method of claim 11, wherein said determining a strategy further comprises making credit approval decisions for said consumer based upon said comprehensive consumer default risk value.

13. The method of claim 11, wherein said determining a strategy further comprises soliciting said consumer for products in accordance with said comprehensive consumer default risk value.

14. The method of claim 10, further comprising establishing a new credit card account based upon said comprehensive consumer default risk value.

15. The method of claim 10, further comprising establishing a new automobile loan based upon said comprehensive consumer default risk value.

16. The method of claim 10, further comprising establishing a new student loan based upon said comprehensive consumer default risk value.

17. The method of claim 1, wherein said calculating further comprises:

querying said data store to retrieve said internal data;

storing said internal data in said memory;

performing a calculation using said processor to obtain said comprehensive consumer default risk value;

storing said comprehensive consumer default risk value in said memory.

18. The method of claim 17, wherein said calculating further comprises:

storing said comprehensive consumer default risk value in said data store in a database transaction;

committing said database transaction.

19. An article of manufacture including a computer readable medium having non-transitory instructions stored thereon that, in response to execution by a computing device, cause the computing device to perform operations comprising:

obtaining consumer credit data relating to said consumer;

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

obtaining internal data relating to said consumer, said internal data comprising consumer transactional data; and

calculating said comprehensive consumer default risk value for said consumer based upon said consumer credit data, said internal data and said estimated spend capacity, wherein said comprehensive consumer default risk value represents a risk associated with said consumer defaulting on an existing debt obligation and

wherein said calculating comprises

assigning said consumer to a consumer population segment based upon primary residence value,

selecting an appropriate risk factor relationship based upon said consumer credit data and said internal data

20. The article of manufacture of claim 19, wherein the non-transitory instructions stored thereon that, in response to execution by a computing device, cause the computing device to further perform operations comprising determining a strategy to interact with said consumer based on said comprehensive consumer default risk value for said consumer.