METHOD FOR MORTGAGE FRAUD DETECTION

• US 20100088242A1
• Filed: 10/05/2009
• Published: 04/08/2010
• Est. Priority Date: 11/14/2003
• Status: Abandoned Application

• Current Assignee: First American CoreLogic Incorporated (CoreLogic Incorporated)
• Original Assignee: First American CoreLogic Incorporated (CoreLogic Incorporated)
• Inventors: Cagan, Christopher L.
• Application Number:
  US12/573,834
• Publication Number:
  US 20100088242A1
• Time in Patent Office: Days
• US Class Current: 705/306
• CPC Class Codes: G06Q 30/018 Certifying business or products
• CPC Class Codes: G06Q 30/0185 Product, service or business identity fraud
• CPC Class Codes: G06Q 30/0278 Product appraisal
• 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 50/167 Closing

Abstract

A method of detection of fraud in a mortgage application: in a computer system, maintaining a database of sales prices of real properties in a geographic area where the property is located; obtaining a valuation history for the property; obtaining historical sales data for similar properties in the geographic area; computing price ratios using these valuation histories; computing a distortion index based on the price ratios, the distortion index indicating the likelihood of a fraudulent valuation.

Claims

1. A method of detecting fraud during a real estate transaction, the method comprising:

using a computer processor to;

receive an estimated value of a subject real property;

access a database of spatial data, the spatial data comprising real estate prices in a geographic area in which the subject real property is located, the geographic area comprising at least one of the same zip code, city, or county as the subject real property;

generate a first spatial variance by computing ratios corresponding to the accessed real estate prices;

generate a second spatial variance by computing ratios corresponding to the accessed real estate prices; and

compute a spatial distortion based on the first spatial variance and the second spatial variance to indicate a likelihood of fraud.

2. The method of claim 1, wherein the spatial data is generated by using sales data for properties in the geographic area.

3. The method of claim 1, wherein the spatial data is generated by using an automated valuation model for properties in the geographic area.

4. The method of claim 1, wherein the spatial data is generated by using a combination of sales data and an automated valuation model for properties in the geographic area.

5. The method of claim 1, wherein the spatial data is generated from real estate prices from previous years.

6. The method of claim 1, wherein the spatial data comprises property characteristics that are shared between the subject real property and properties in the geographic area.

7. The method of claim 1, wherein one of the spatial variances comprise a ratio of the estimated value of the subject real property and a median real estate price of real property in the same zip code.

8. The method of claim 1, wherein the spatial distortion comprises a difference between two years of spatial variances of the subject real property.

9. The method of claim 8, wherein the two years comprise the current year and a previous year having the largest spatial variance.

10. A method of detecting fraud during a real estate transaction, the method comprising:

using a computer processor to;

receive an estimated value of a subject real property;

access a database of spatial data, the spatial data comprising real estate prices in a geographic area in which the subject real property is located, the geographic area comprising at least one of the same zip code, city, or county as the subject real property;

generate a set of spatial variances by computing ratios between a plurality of real estate prices of the subject real property and a plurality of real estate prices of properties in the geographic area;

compute a spatial distortion based on the set of spatial variances; and

produce a distortion ratio score to indicate a likelihood of fraud based on the spatial distortion.

11. The method of claim 10, further comprising accessing a set of temporal data.

12. The method of claim 11, further comprising generating a set of temporal variances, computing a temporal distortion based on the set of temporal variances, and computing a total distortion by adding the temporal distortion to the spatial distortion.

13. A system of detecting fraud during a real estate transaction, the method comprising:

a computer processor; and

a memory storing program instructions, said program instructions when executed by the computer processor causes the computer processor to;

receive an estimated value of a subject real property;

access a database of spatial data, the spatial data comprising real estate prices in a geographic area in which the subject real property is located, the geographic area comprising at least one of the same zip code, city, or county as the subject real property;

generate a set of spatial variances by computing ratios between a plurality of real estate prices of the subject real property and a plurality of real estate prices of properties in the geographic area;

compute a spatial distortion based on the set of spatial variances; and

produce a distortion ratio score to indicate a likelihood of fraud based on the spatial distortion.

14. The system of claim 13, wherein the spatial data is generated by using a combination of sales data and an automated valuation model for properties in the geographic area.

15. The system of claim 13, wherein the spatial data is generated from real estate prices from previous years.

16. The system of claim 13, wherein the spatial data comprises property characteristics that are shared between the subject real property and properties in the geographic area.

17. The system of claim 13, wherein one of the spatial variances comprise a ratio of the estimated value of the subject real property and a median real estate price of real property in the same zip code.

18. The system of claim 13, wherein the spatial distortion comprises a difference between two years of spatial variances of the subject real property.

19. The system of claim 18, wherein the two years comprise the current year and a previous year having the largest spatial variance.

20. A method of detecting fraud during a real estate transaction, the method comprising:

using a computer data processor to;

access a database of real property prices in a geographic area in which a subject real property is located;

using data from the database or data from a requestor to generate a temporal data set comprising a current yearly real property price for the subject real property and a set of past yearly real property prices for the subject real property;

generate from the database a spatial data set comprising a current yearly real property price for real property with similar characteristics as the subject real property and a set of past yearly real property prices for real property with similar characteristics as the subject real property;

generate a set of temporal variances;

generate a set of spatial variances;

compute a spatial distortion based on the set of spatial variances;

compute a temporal distortion based on the set of temporal variances; and

compute a total distortion by adding the temporal distortion to the spatial distortion.