SYSTEM AND METHOD FOR DETERMINISTIC AND PROBABILISTIC MATCH WITH DELAYED CONFIRMATION

• US 20130046560A1
• Filed: 08/19/2011
• Published: 02/21/2013
• Est. Priority Date: 08/19/2011
• Status: Abandoned Application

• Current Assignee: Hartford Fire Insurance Company (The Hartford Financial Services Group, Inc.)
• Original Assignee: Hartford Fire Insurance Company (The Hartford Financial Services Group, Inc.)
• Inventors: Theus, Garry Jean, Pabilonia, James L., Raibeck, Jennifer B., Simpson, Shawn K., Sullivan, Nancy J.
• Application Number:
  US13/213,513
• Publication Number:
  US 20130046560A1
• Time in Patent Office: Days
• US Class Current: 705/4
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

Some embodiments may be directed to matching users, such as employees, with insurance records in an integrated database, wherein the integrated database includes a plurality of insurance records, each record being associated with a unique employee and having a plurality of fields. According to some embodiments, new employee information may be received and it may be determined that the new employee information does not qualify as a strong match with any insurance record in the integrated database. Moreover, it may be determined, based on a probabilistic pattern match of the new employee information with values in the fields of the integrated database, that the new employee information qualifies as a weak match with a particular insurance record in the integrated database. Subsequent to the determination of a weak match, supplemental employee information may be received, and, responsive to the supplemental employee information, the match between the new employee information and the particular insurance record in the integrated database may be upgraded from a weak match to a strong match.

Claims

1. A system for matching employees with group benefits based insurance database records, comprising:

a communication device to receive new employee information;

an integrated database including a plurality of group benefits based insurance records, each group benefits based insurance record being associated with a unique employee and having a plurality of fields;

a processor coupled to the communication device and integrated group benefits based insurance database; and

a storage device in communication with said processor and storing instructions adapted to be executed by said processor to;

determine that the new employee information does not qualify as a strong match with any group benefits based insurance record in the integrated database,

determine, based on a probabilistic pattern match of the new employee information with values in the fields of the integrated database, that the new employee information qualifies as a weak match with a particular group benefits based insurance record in the integrated database,

subsequent to said determination of a weak match, receive supplemental employee information, and

responsive to said supplemental employee information, upgrade the match between the new employee information and the particular group benefits based insurance record in the integrated database from a weak match to a strong match.

2. The system of claim 1, wherein the probabilistic pattern matching is associated with a closeness rule and a confidence level compared to a predetermined threshold.

3. The system of claim 1, wherein the probabilistic pattern matching assigns a matching score to each field in the integrated database.

4. The system of claim 1, wherein the new employee information includes at least one of:

(i) name information, (ii) a Social Security number, (iii) gender information, (iv) a date of birth, (v) a ZIP code, (vi) an employee identifier, (vii) an employer identifier, (viii) an integrated database identifier, (ix) an address, or (x) a telephone number.

5. The system of claim 1, wherein the integrated database is associated with at least one of:

(i) insurance policies, (ii) insurance claims, (iii) leave management, or (iv) insurance claim benefits.

6. A method of matching users with records in an integrated database, wherein the integrated database includes a plurality of records, each record being associated with a unique user and having a plurality of fields, said method comprising:

receiving new user information;

determining that the new user information does not qualify as a strong match with any record in the integrated database;

determining, based on a probabilistic pattern match of the new user information with values in the fields of the integrated database, that the new user information qualifies as a weak match with a particular record in the integrated database;

subsequent to said determination of a weak match, receiving supplemental user information; and

responsive to said supplemental user information, upgrading the match between the new user information and the particular record in the integrated database from a weak match to a strong match.

7. The method of claim 6, further comprising:

determining, based on a second probabilistic pattern match of second new user information with values in the fields of the integrated database, that the second new user information qualifies as a weak match with a second particular record in the integrated database;

receiving second supplemental user information; and

responsive to said second supplemental user information, downgrading the match between the second new user information and the second particular record in the integrated database from a weak match to no match.

8. The method of claim 7, further comprising:

integrating user data input via a plurality of independent methods into the integrated database, wherein said integrating is associated with a data cleansing process.

9. The method of claim 6, wherein the integrated database is associated with at least one of:

(i) employees, (ii) insurance policies, (iii) insurance claims, or (iv) leave management.

10. The method of claim 6, wherein the new user information is received from a remote user device via a communication network.

11. The method of claim 10, wherein the supplemental user information is received from the remote user device via the communication network.

12. The method of claim 10, wherein the supplemental user information is received from a third-party service.

13. The method of claim 6, wherein the new user information includes at least one of:

(i) name information, (ii) a Social Security number, (iii) gender information, (iv) a date of birth, (v) a ZIP code, (vi) an employee identifier, (vii) an employer identifier, (viii) an integrated database identifier, (ix) an address, (x) a telephone number, or (xi) a user name and password.

14. The method of claim 6, wherein the probabilistic pattern matching is associated with a closeness rule and a confidence level compared to a predetermined threshold.

15. The method of claim 14, wherein the closeness rule is associated with a Levenshtein distance.

16. The method of claim 6, wherein the probabilistic pattern matching assigns a matching score to each field in the integrated database.

17. The method of claim 6, further comprising:

prior to upgrading the match between the new user information and the particular record to a strong match, placing the new user information in quarantine.

18. A non-transitory computer-readable medium storing instructions adapted to be executed by a computer processor to perform a method associated with matching users with records in an integrated database, wherein the integrated database includes a plurality of records, each record being associated with a unique user and having a plurality of fields, said method comprising:

receiving new user information;

determining, based on a probabilistic pattern match of the new user information with values in the fields of the integrated database, that the new user information qualifies as a weak match with a particular record in the integrated database;

subsequent to said determination of a weak match, receiving supplemental user information; and

responsive to said supplemental user information, upgrading the match between the new user information and the particular record in the integrated database from a weak match to a strong match.

19. The medium of claim 18, wherein the probabilistic pattern matching is associated with a closeness rule and a confidence level compared to a predetermined threshold.

20. The medium of claim 18, wherein the weak match is determined based on an employee identifier and the supplemental user information comprises at least a portion of a Social Security number.