SYSTEM AND METHOD FOR DETERMINING VEHICLE PRICE VALUES

• US 20140058956A1
• Filed: 10/28/2013
• Published: 02/27/2014
• Est. Priority Date: 11/26/2003
• Status: Abandoned Application

• Current Assignee: CARFAX Incorporated (S&P Global Inc.)
• Original Assignee: CARFAX Incorporated (S&P Global Inc.)
• Inventors: RAINES, Richard T., AYRAULT, Renan, MOORE, Philip D., ANDRINGS, Mark D.
• Application Number:
  US14/064,952
• Publication Number:
  US 20140058956A1
• Time in Patent Office: Days
• US Class Current: 705/306
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0278 Product appraisal
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions

Abstract

System and method for computing price values associated with vehicle history attributes including a vehicle history database with vehicle history records, a transaction database, a vehicle history knowledge determination module adapted to determine whether a sale transaction related to a transaction record occurred with buyer'"'"'s knowledge of the vehicle history attributes associated with the vehicle of the transaction record and to classify each transaction record based on whether buyer possessed knowledge of the vehicle history attributes, and a price adjustment module adapted to determine price values for the vehicle history attributes based on the vehicle history datasets and classification of the plurality of transaction records. In accordance with one aspect, the present invention may be implemented as a computer readable medium with instructions.

Claims

1. A method for obtaining at least one price value for a specific used vehicle based on vehicle history attributes of the specific used vehicle, said method comprising:

receiving a vehicle identification indicating a specific used vehicle;

receiving at least one vehicle history attribute indicator of the specific used vehicle;

querying a pricing model based on said at least one vehicle history attribute of the specific vehicle, said pricing model being based on a plurality of vehicle history records related to a plurality of vehicles and having vehicle history attributes regarding said vehicles and a plurality of transaction records including a transaction price, said pricing model obtained by performing mathematical modeling on vehicle history attributes from said vehicle history records and transaction prices obtained from said transaction records to obtain price values corresponding to said at least one vehicle history attribute; and

retrieving a price value for the specific vehicle from said pricing model based on said at least one vehicle history attribute indicator.

2. The method as recited in claim 1, wherein the vehicle transaction records are related to transactions of said plurality of vehicles.

3. The method as recited in claim 1, wherein each transaction record is related to a type of vehicle.

4. The method as recited in claim 1, wherein the price value is a price adjustment to be applied to a base price of the vehicle.

5. The method as recited in claim 1, wherein the price value is a vehicle price.

6. The method as recited in claim 1, wherein the transaction prices are at least one of a survey price, a sales price, an offer price, and an auction price, or any combination thereof.

7. The method as recited in claim 1, wherein said transaction records are survey records and said transaction prices are prices based on surveys.

8. The method as recited in claim 1, wherein said mathematical model is created by performing multivariate analysis on the vehicle history attributes and the transaction prices.

9. The method as recited in claim 1, wherein said mathematical model is created by a first stage of performing multivariate analysis on a collection of vehicle history attributes for various types of vehicles, and a second stage of performing multivariate analysis on a collection of vehicle history attributes for a specific type of vehicle.

10. The method as recited in claim 8, wherein the multivariate analysis is regression analysis.

11. A method as recited in claim 1, wherein said pricing model is further based on determining a likelihood of whether a purchaser had knowledge of relevant vehicle history attributes at a time of transactions corresponding to said transaction records, and performing mathematical modeling on the determined likelihood.

12. The method as recited in claim 11, wherein said likelihood is a rating of a transaction in one of the categories of KNOWN, UNKNOWN, OR UNCERTAIN.

13. The method as recited in claim 11, wherein the likelihood of whether a purchaser had knowledge is based on whether a vehicle history report for a particular vehicle corresponding to a transaction record was generated.

14. The method as recited in claim 11, wherein the likelihood of whether a purchaser had knowledge is based on whether a vehicle history report for a particular vehicle corresponding to a transaction record was generated within a predetermined time frame of the corresponding transaction.

15. A system for obtaining at least one price value for a specific used vehicle based on vehicle history attributes of the specific used vehicle, said system comprising:

a vehicle history report module implemented on a computing device and configured to receive a vehicle identification indicating a specific used vehicle, said vehicle history report module also being configured to receive at least one vehicle history attribute indicator of the specific used vehicle;

a user interface module implemented on hardware and configured to receive a query for a pricing model based on said at least one vehicle history attribute of the specific vehicle, said pricing model being based on a plurality of vehicle history records related to a plurality of vehicles and having vehicle history attributes regarding said vehicles and a plurality of transaction records including a transaction price, said pricing model obtained by performing mathematical modeling on vehicle history attributes from said vehicle history records and transaction prices obtained from said transaction records to obtain price values corresponding to said at least one vehicle history attribute; and

a vehicle price adjustment module configured to retrieve a price value for the specific vehicle from said pricing model based on said at least one vehicle history attribute indicator.

16. The system as recited in claim 15, wherein the vehicle transaction records are related to transactions of said plurality of vehicles.

17. The system as recited in claim 15, wherein each transaction record is related to a type of vehicle.

18. The system as recited in claim 15, wherein the price value is a price adjustment to be applied to a base price of the vehicle.

19. The system as recited in claim 15, wherein the price value is a vehicle price.

20. The system as recited in claim 15, wherein the transaction prices are at least one of a survey price, a sales price, an offer price, and an auction price, or any combination thereof.

21. The system as recited in claim 15, wherein said transaction records are survey records and said transaction prices are prices based on surveys.

22. The system as recited in claim 15, wherein said mathematical model is created by performing multivariate analysis on the vehicle history attributes and the transaction prices.

23. The system as recited in claim 15, wherein said mathematical model is created by a first stage of performing multivariate analysis on a collection of vehicle history attributes for various types of vehicles, and a second stage of performing multivariate analysis on a collection of vehicle history attributes for a specific type of vehicle.

24. The system as recited in claim 22, wherein the multivariate analysis is regression analysis.

25. The system as recited in claim 15, wherein said pricing model is further based on determining a likelihood of whether a purchaser had knowledge of relevant vehicle history attributes at a time of transactions corresponding to said transaction records, and performing mathematical modeling on the determined likelihood.

26. The system as recited in claim 25, wherein said likelihood is a rating of a transaction in one of the categories of KNOWN, UNKNOWN, OR UNCERTAIN.

27. The system as recited in claim 25, wherein the likelihood of whether a purchaser had knowledge is based on whether a vehicle history report for a particular vehicle corresponding to a transaction record was generated.

28. The system as recited in claim 25, wherein the likelihood of whether a purchaser had knowledge is based on whether a vehicle history report for a particular vehicle corresponding to a transaction record was generated within a predetermined time frame of the corresponding transaction.