Total structural risk model
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.
1. A method for obtaining a consumer default risk value for a consumer, wherein said consumer default risk value is derived by a risk analysis computer, said method comprising:
receiving, at a requestor host system and in response to a credit inquiry request, said consumer default risk value for said consumer from said risk analysis computer, wherein said risk analysis computer comprises a processor, a memory, and a data store, and wherein said consumer default risk value represents a risk associated with said consumer defaulting on an existing debt obligation, wherein said comprehensive consumer default risk value comprises a probability value between 0 and 1 and is calculated by said risk analysis computer by:
obtaining, by said risk analysis computer, consumer credit data relating to said consumer;
obtaining, by said risk analysis computer, internal data relating to said consumer wherein said internal data comprises consumer transactional data;
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; and
calculating, by said risk analysis computer, said consumer default risk value for said consumer based upon said consumer credit data, said internal data, and said estimated spend capacity wherein said calculating comprises:
assigning said consumer to a consumer population segment based upon primary residence value, and
selecting an appropriate risk factor relationship based upon said consumer credit data and said internal data.
2. The method of claim 1 , farther comprising determining a strategy to interact with said consumer based on said consumer default risk value.
3. The method of claim 1 , further comprising making credit approval decisions for said consumer based upon said consumer default risk value.
4. The method of claim 1 , further comprising soliciting said consumer for additional products in accordance with said consumer default risk value.
5. The method of claim 1 , further comprising establishing a new credit card account based upon said consumer default risk value.
6. The method of claim 1 , further comprising establishing a new student loan based upon said consumer default risk value.
7. The method of claim 1 , further comprising establishing a new automobile loan based upon said consumer default risk value.
8. The method of claim 1 , further comprising discontinuing a relationship with said consumer based upon said consumer default risk value.
9. The method of claim 1 , wherein said consumer default risk value is further calculated by:
receiving credit bureau data comprising a plurality of accounts of said consumer over a previous period of time;
identifying a balance transfer into at least one of said plurality of accounts based upon said credit bureau data;
discounting spending identified for at least one of said plurality of accounts for at least a portion of said previous period of time in which a balance transfer to such account is identified; and
estimating a purchasing ability of said consumer based on said credit bureau data and said discounting.
10. The method of claim 1 , wherein said credit inquiry request is incident to a credit rating for an asset backed securities issuer.
11. The method of claim 1 , wherein said internal data comprises transactional data comprising merchant location, transaction amount, and time of day of transaction.
12. The method of claim 1 , wherein said internal data comprises consumer payment data.
13. The method of claim 1 , wherein said internal data comprises at least one of consumer service call data, consumer complaint data, or consumer comments.