IP Library Granted Patent US 8,548,934
Granted Patent B2
US 8,548,934 · App. 12/694,243 · Granted Oct 1, 2013

System and method for assessing risk

Inventors: William Michael Lay (Glenwood, MD); Yi Wu (Silver Spring, MD); Fan Tao Pu (Potomac, MD); Alain Kouyaté (Silver Spring, MD)
Assignee: Infozen, Inc.
G06N5/02
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Quick Facts
Patent No.
US 8,548,934
App. No.
12/694,243
Granted
Oct 1, 2013
Kind
B2
Abstract

The invention describes systems and methods of assessing risk using a computer. A computer-based system including an enrollment module, a data aggregation module, a risk assessment module, and a memory is provided for assessing risks. The enrollment receives, at a computer, personal information regarding at least one entity. The data aggregation module receives, at the computer, risk information regarding the entity according to the personal information from at least one data source. The risk assessment module converts the risk information to assessment information. The memory stores the personal information, the risk information, and/or the assessment information on the computer.

Claims (39)

1. A computer-based system for assessing risks, the system comprising:

a storage device to

receive, at a computer, personal information regarding at least one entity;

receive, at the computer, risk information regarding the at least one entity according to the personal information from at least one data source, wherein the risk information includes infraction information, punishment information, and disposition information that correspond to the personal information of the at least one entity,

store the personal information, the risk information, or assessment information on the computer; and

a processor to automatically convert the risk information to assessment information using standardized codes by assigning numerical values including an infraction code that corresponds to the infraction information, a punishment code that corresponds to the punishment information, and a disposition code that corresponds to the disposition information.

2. The computer-based system according to claim 1 , wherein the risk information further comprises:

criminal history, civil history, terrorist watch lists, traffic violations, loan or debt delinquencies, outstanding wants or warrants, academic disciplinary history, or immigration status.

3. The computer-based system according to claim 1 , further comprising:

an adjudication module to determine a level of risk corresponding to the at least one entity according to the assessment information.

4. The computer-based system according to claim 3 , wherein the level of risk corresponding to the at least one entity is determined according to adjudication parameters received by the adjudication module.

5. The computer-based system according to claim 4 , wherein the adjudication parameters are received from a user and are input into the computer or received from a client over a network.

6. A method of assessing risks using a computer, the method comprising:

receiving personal information regarding at least one entity at the computer;

gathering risk information regarding the at least one entity according to the personal information from at least one data source, wherein the gathering of the risk information includes obtaining infraction information, punishment information, and disposition information that correspond to the personal information of the at least one entity;

automatically converting the risk information to assessment information, wherein the automatically converting of the risk information to the assessment information includes converting the infraction information to an infraction code, the punishment information to a punishment code, and the disposition information to a disposition code by assigning standardized numerical values to the infraction information, the punishment information, and the disposition information; and

storing the personal information, the risk information, or the assessment information in a memory of the computer.

7. The method according to claim 6 , wherein the risk information comprises:

criminal history, civil history, terrorist watch lists, traffic violations, loan or debt delinquencies, outstanding wants or warrants, academic disciplinary history, or immigration status.

8. The method according to claim 6 , further comprising:

determining a level of risk corresponding to the at least one entity according to the assessment information.

9. The method according to claim 8 , wherein the level of risk corresponding to the at least one entity is determined according to adjudication parameters.

10. The method according to claim 9 , further comprising:

receiving the adjudication parameters by inputting the adjudication parameters into the computer or receiving the adjudication parameters from a client over a network.

11. The method according to claim 6 ,

wherein the standardized infraction code is derived from infraction information by pre-processing the infraction information and using a predictive model to classify the infraction information into the infraction code along with a confidence factor for the classification;

wherein the standardized punishment code is derived from punishment information by pre-processing the punishment information and using the predictive model to classify the punishment information into the punishment code along with a confidence factor for the classification; and

wherein the standardized disposition code is derived from disposition information by pre-processing the disposition information and using the predictive model to classify the disposition information into the disposition code along with a confidence factor for the classification.

12. The method according to claim 11 , wherein the pre-processing of the infraction information, the punishment information, or the disposition information includes:

performing a number of text-string substitutions to normalize the language of the infraction information, the punishment information, or the disposition information;

removing unnecessary text from the infraction information, the punishment information, or the disposition information; and

creating specific phrases based on the proximity of two or more words.

13. The method according to claim 11 , wherein the predictive model is a statistical pattern learning model which is trained to predict classifications by using examples of text already classified.

14. A computer-readable recording medium containing computer-readable codes providing commands for computers to execute a process including:

receiving personal information regarding at least one entity at the computer;

gathering risk information regarding the at least one entity according to the personal information from at least one data source wherein the gathering of the risk information includes obtaining infraction information, punishment information, and disposition information that correspond to the personal information of the at least one entity;

automatically converting the risk information to assessment information; and

storing the personal information, the risk information, and the assessment information on the computer;

wherein the automatically converting of the risk information to the assessment information includes converting the infraction information to an infraction code, the punishment information to a punishment code, and the disposition information to a disposition code by assigning standardized numerical values to the infraction information, the punishment information, and the disposition information.

Assignments (3)
CHANGE OF NAME Recorded Mar 13, 2017
From: IDENTRIX, LLC
To: ENDERA SYSTEMS, LLC
Reel/Frame 041562/0566 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 10, 2015
From: INFOZEN, INC.
To: IDENTRIX, INC.
Reel/Frame 036289/0808 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 8, 2010
From: LAY, WILLIAM MICHAEL; WU, YIN; PU, FAN TAO; KOUYATE, ALAIN
To: INFOZEN, INC.
Reel/Frame 025332/0602 →
Continuity (2)
Provisional Application 61261873 · Nov 17, 2009
Related Publication 20110119211A1 · May 19, 2011