MORTGAGE FRAUD DETECTION SYSTEMS AND METHODS

• US 20100241558A1
• Filed: 06/09/2009
• Published: 09/23/2010
• Est. Priority Date: 12/20/2007
• Status: Abandoned Application

• Current Assignee: LexisNexis Risk Solutions, Inc. (RELX PLC)
• Original Assignee: LexisNexis Group Inc. (RELX PLC)
• Inventors: James, Denise, Chmielewski, Thomas
• Application Number:
  US12/481,546
• Publication Number:
  US 20100241558A1
• Time in Patent Office: Days
• US Class Current: 705/38
• CPC Class Codes: G06Q 30/0185 Product, service or business identity fraud
• 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
• CPC Class Codes: G06Q 50/16 Real estate
• CPC Class Codes: G06Q 50/18 Legal services

Abstract

Mortgage fraud detection systems and methods are provided. A fraud detection system can generally comprise a database operator, a database manager, one or more users, and a database. Database components can be implemented as hardware, software, or a combination of both. A fraud detection method can generally comprise providing a database for maintaining a plurality of records. Data records can be continually received by a database in batchwise or single submission protocols. Records can be compared to determine whether they contain common data in one or more predetermined fields. If records contain common data in one or more predetermined fields, records can be examined for inconsistencies in one or more other data fields. Discovered inconsistencies and magnitudes of inconsistencies can be warning signs of fraud. Results of comparisons can be reported to system users to enable such users to investigate additional circumstances. Other embodiments and features are also claimed and described in the application.

Claims

1. A fraud detection system to detect fraud in a financial loan application process by analyzing a plurality of data from multiple sources, the system comprising:

one or more interfaces configured to receive data from a plurality of unique data sources, the data comprising data records comprising at least one of information related to a financial loan application, parties involved in a loan transaction, and property involved in a financial loan;

a database configured to receive data from the plurality of unique data sources and to store the data with an identifier configured to distinguish data received from the plurality of unique data sources;

a processing module configured to determine if one or more of the data records contain one or more matching data fields and to flag data records containing the one or more matching data fields by storing match information in a table; and

the processing module further configured to determine if one or more of the flagged data records contain different information in one or more other data fields contained in the data records and storing information corresponding to differences in the table.

2. The fraud detection system of claim 1, the one or more matching data fields comprising at least one of information about property involved in a financial loan and at least a party involved in a loan transaction.

3. The fraud detection system of claim 1, further comprising a reporting module configured to report at least one of information concerning the data records containing the one or more matching data fields and information concerning the flagged data records containing different information in the one or more predetermined data fields.

4. The fraud detection system of claim 3, the reporting module further configured to order information contained in a report at least partially based on different information contained in the one or more data fields and a magnitude of difference.

5. The fraud detection system of claim 1, the processing module further configured to place one or more received data records in an active state for a predetermined holding period and periodically analyze active-state data records relative existing data and data received after the active-state data records.

6. The fraud detection system of claim 5, wherein the predetermined holding period ranges from approximately one day to approximately one year.

7. The fraud detection system of claim 1, wherein the one or more data sources comprise at least one of information received from unique end users providing data to the one or more data interfaces and information received from existing unique databases operatively coupled to the one or more data interfaces.

8. The fraud detection system of claim 1, wherein the processing module is configured to determine if one or more of the data records contain substantially similar addresses for a real estate property involved in a loan transaction.

9. A method for detecting fraud in a financial credit or loan application process, the fraud detection method comprising:

providing a database operatively configured to receive data comprising details concerning a financial credit or loan application and to store received data as one or more first data records;

configuring the database to receive data from a plurality of unique data sources and store the data with an identifier for distinguishing the unique data sources, the data comprising at least one of, one or more parties involved in a loan transaction, and property involved in a financial application process;

providing a data comparison module operatively configured to flag the one or more first data records containing similar data in one or more predetermined data fields by storing matching information in a table; and

configuring the data comparison module to determine if the flagged data records comprising at least one data field with similar data comprise one or more other data fields having inconsistent data by storing inconsistent data in the table.

10. The fraud detection method of claim 9, further comprising configuring the database to provide reports comprising at least one of details related to the flagged data records comprising at least one data field with similar data and details related to the flagged data records comprising data fields with inconsistent data.

11. The fraud detection method of claim 9, further comprising configuring the database to receive data from a plurality of end users and the one or more databases via a communications network.

12. The fraud detection method of claim 9, wherein providing a data comparison module operatively configured to flag the one or more data records containing similar data in one or more predetermined data fields comprises determining if the one or more data records contain data fields having similar property address information or similar borrower information.

13. The fraud detection method of claim 9, further comprising configuring the database to provide reports to a user with data ordered based on results a two-tier weighted algorithm.

14. The fraud detection method of claim 9, further comprising holding one or more of the data records in the database for a predetermined holding period and configuring the data comparison module to compare existing data records to data records received after the existing data records at predefined intervals.

15. The fraud detection method of claim 9, further comprising operatively configuring the database to receive lender originated data and user incident report data.

16. The fraud detection method of claim 9, further comprising operatively configuring the data comparison module to receive professional license information from one or more existing databases to determine if a licensed party involved in a loan transaction is properly licensed and has any past professional sanctions.

17. A computer-readable medium having computer readable instructions stored thereon for execution by a processor to execute a method for detecting fraud, the fraud detection method comprising:

providing a database configured to receive data from a plurality of unique data sources and associate received data with an identifier to distinguish the unique data sources, the data comprising data records having data fields, the data records comprising at least one of information related to a financial loan application, parties involved in a loan transaction, and property involved in a financial loan;

determining whether one of the data records has a data field containing common data to at least one other data field contained within at least one of the other data records;

determining whether data records having at least one data field in common have other data fields having disparate data; and

providing a report comprising data records based at least partially on the identifier, the report further comprising a listing of data records with data fields having common data and data records containing data fields having disparate data.

18. The computer-readable medium of claim 17, wherein at least a portion of the data records contain mortgage loan application information submitted by unique users and at least another portion of the data records contain information obtained from pre-existing databases containing borrower information.

19. The computer-readable medium of claim 17, wherein the data field reviewed for common data comprises property address information to determine if a single property is subject to multiple loan applications.

20. The computer-readable medium of claim 17, further comprising repeatedly determining on a pre-determined basis whether one of the data records has a data field containing common data to at least one other data field contained within at least one of the other data records and whether data records having at least one data field in common have other data fields having disparate data.

21-45. -45. (canceled)