Experian Information Solutions, Inc.

Id Analytics, Inc.

Alan Tsang

Yaqi Tao

Andrew John Hickman

Derek Toub

Eric Haller

Shanji Xiong

Zhixuan Wang

Kevin Chen

Honghao Shan

Gregor Bonin

Lingyun Zhang

Sreeram Upendran

Shengjun Pan

Steven Yin

David Kerry

Jack Yu

Christopher Wheeler

Yue Yu

Hua Li

Stephen V Coggeshall

Tao Hong

Allen P Jost

Xuhui Shao

Christer DiChiara

Christer J DiChiara

Mike Cook

Mustafa Yakub Adib

Zehua Guo

Stuart Anthony Mathews

Shervin Sharifi

Wis Kojohnjaratkul

Systems and methods are described for identifying a target entity that a user intends to refer to based on input that may include only a partial name of the entity. A system may receive a user's entity search query, which may include a partial entity name, then may determine initial candidate matching entities and associated name match scores for each of the initial candidate matching entities relative to the input string, such as using string matching or fuzzy matching techniques. The system may apply a probability match model to generate an overall match score for individual ones of the initial candidate matching entities, then may generate a response to the entity search query that includes information regarding one or more of the initial candidate matching entities with an overall match score exceeding a threshold.

Systems and methods for entity resolution

The present disclosure describes systems and methods for providing enhanced location analysis and consumer insights using mobile sightings data. An approximate geographic location is useful to mobile service providers and advertisers who wish to provide targeted content to consumers based on their location. The location analysis described herein provides more depth and detail about the detected geographic location of the consumer and also insights into business locations visited by the user of the device, consumer/market segments and patterns of behavior (for an individual consumer and/or for aggregated group of consumers), retail trends and patterns, and other profile information. For example, a location profile analytics system as described herein can determine a probability that an approximate geographic location actually corresponds to a specific geographic location, such as a business location. The analysis performed by the location profile analytics system may be further refined based on a number of additional input parameters.

Mobile device sighting location analytics and profiling system

Features are described for efficiently and accurately identifying a user of an electronic device with limited user interaction. The features include receiving a mobile device identifier from the mobile device. The features include transmitting the mobile device identifier to a service provider associated with the mobile device. The features include receiving information identifying the user from the service provider. The features include identifying a set of candidates associated with at least a portion of the information. The features include generating a metric for the candidates included in the set of candidates. An individual metric indicates a degree of relatedness between a value for the user for the at least one data field and a value for a candidate for the at least one data field. The features include identifying the user as a specific candidate included in the set of candidates based on the metric corresponding to a threshold.

Disambiguation and authentication of device users

The present disclosure describes systems and methods for automatically rolling-up data associated with one or more geographic units, such as ZIP+4 codes, such that the rollup comprises a minimum number of households to protect anonymity and ensure compliance with privacy regulations, while preserving variance of the underlying data associated with the geographic regions. Data attributes may include demographic data, socio-economic data, lifestyle segmentation, psychographic data, behavioral data, credit data, and other data. The rollup process may involve identifying one or more geographic units with a number of households below a minimum or threshold amount, applying filters to find candidate geographic units for rollup, scoring candidate geographic units to select best pairings for rollup, and repeating until the rollup group has at least the minimum number of households. The process may make trades off between granularity (e.g., number of households), proximity, and similarity of data attributes associated with each geographic unit.

Micro-geographic aggregation system

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 using a plurality of historical identity records

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San Diego, CA, United States of America

Alan Tsang