Identity protection

• US 8,359,278 B2
• Filed: 08/28/2007
• Issued: 01/22/2013
• Est. Priority Date: 10/25/2006
• Status: Active Grant

• Current Assignee: Csidentity Corporation (Experian plc)
• Original Assignee: Indentitytruth Incorporated
• Inventors: Domenikos, Steven D., Astras, Stamatis, Seri, Iris
• Primary Examiner(s): Casler, Traci
• Application Number:
  US11/846,305
• Publication Number:
  US 20080103799A1
• Time in Patent Office: 1,974 Days
• Field of Search: 705/325
• US Class Current: 705/325
• CPC Class Codes: G06Q 30/0185 Product, service or business identity fraud
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

In general, in one aspect, the invention relates to a system for providing identity protection that, in one embodiment, includes a fraud model for specifying patterns of events indicative of identity fraud and a business rules subsystem used to identify fraud that is specified by the fraud models. The system aggregates data from a variety of sources, and has an analytical engine that operates on the aggregated data and determines, using the business rules, whether there are events that are correlative with the fraud models that are indicative of fraud.

Claims

1. A computing system for providing identity fraud risk indicia, the system comprising:

a fraud model subsystem that specifies patterns of events indicative of identity fraud, wherein each pattern comprises a type of fraud and information related to event timing;

a business rules subsystem that, based on the patterns of events, specifies rules to identify fraud;

a data aggregation subsystem that collects data input from a variety of sources, the data comprising demographic data for individuals, asset data for individuals, event occurrence data, identity theft statistical data, and personal data; and

a processor for executing computer readable instructions that, when executed, employ the rules to;

examine a static structure of a subset of the data that relates to an individual relative to underlying financial and physical assets and personal attributes of the individual;

correlate interconnectivity of the subset with events that have changed the static structure in the past;

correlate interconnectivity of the subset with new events discovered during a monitoring process; and

determine whether the events and the new events are correlative with at least one of the patterns based on the rules.

2. The system of claim 1, wherein the processor further executes computer readable instructions that provide a prediction of fraud events that are likely to occur.

3. The system of claim 2, wherein the prediction comprises a probability that such fraud events are likely to occur.

4. The system of claim 2, wherein the processor further executes computer readable instructions that provide recommendations of steps to be taken to avoid predicted fraud events.

5. The system of claim 1, wherein the processor further executes computer readable instructions that identify fraud events that are likely to occur.

6. The system of claim 5, wherein the identified fraud events are compared to fraud scenarios specified in the patterns of events indicative of identity fraud.

7. The system of claim 5, further comprising rulesets, and wherein the processor further executes computer readable instructions that use the rulesets to evaluate fraud events that have occurred.

8. The system of claim 1, further comprising a communication subsystem for communicating to the first individual fraud events that are likely to occur.

9. The system of claim 1, further comprising a communication subsystem for communicating with a financial organization.

10. The system of claim 1, further comprising a communication subsystem for alerting the first individual.

11. The system of claim 1, wherein the processor further executes computer readable instructions that cause at least some of the data input from the variety of sources to be normalized.