Id Analytics, Inc.

Symantec Corporation

Fair Isaac Corporation

Jianjun Xie

Xuhui Shao

Tao Hong

Allen P Jost

Scott Michael Zoldi

Ted E Dunning

Stephen V Coggeshall

Shanji Xiong

Yinghua Lin

Maria Edna Derderian

Jeremy Mamer Schmitt

Guowei Wu

Joe Blue

Quan Lu

Systems, methods, and products for detection of selective omissions in an open data sharing computing platform comprises monitoring a plurality of events associated with a first digital record stored in a database of digital records, the first digital record uniquely identifying a first entity; associating a first detected event with a first set of words at least partially descriptive of the first detected event; associating a second detected event with a second set of words at least partially descriptive of the second detected event, the first event and the second event being detected, in response to digital records associated with the first event and the second event being shared over an open data sharing computing platform with express authorization provided by the first entity.

Assessing the presence of selective omission via collaborative counterfactual interventions

A method for determining a likelihood of fraud associated with an input identity record is disclosed herein. The disclosed method contemplates determining characteristics of the input identity record by examining content of one or more fields of the input identity record. Historical identity records related to the input identity record may then be retrieved so as to define a set of linked identity records. The method further includes computing one or more network-based features of the set of linked identity records. A fraud score may then be generated based upon the characteristics of the input identity record and the one or more network-based features.

System and method for identity-based fraud detection

A technique is provided for determining credit ratings without the need for traditional credit bureau data. In at least one embodiment of the invention, a method comprises the steps of providing a network of linked identity records, each identity record comprising identity related information; receiving an identity record comprising identity related information of the entity; linking the received identity record with at least one of the identity records in the network of linked identity records, quantifying a plurality of linked identity records related to the entity; and generating a credit rating for the entity based on the quantified identity records. Application of the invention is particularly useful for individuals with less than a few years credit behavior recorded on a credit bureau, such as immigrants or young people with limited traditional historical information ('thin file') and individuals with no traditional historical information ('no hit').

System and method for credit scoring using an identity network connectivity

A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can be performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.

System and method for identity-based fraud detection through graph anomaly detection

A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.

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San Diego, CA, United States of America

Jianjun Xie