Experian Information Solutions, Inc.

Other

Id Analytics, Inc.

Shanji Xiong

Mason Carpenter

Honghao Shan

Christer DiChiara

Gregor Bonin

Hua Li

Kevin Chen

Zhixuan Wang

Yaqi Tao

Lingyun Zhang

Yi He

Alan Tsang

Julian Yarkony

Andrew John Hickman

Mark Hirn

Chi Zhang

Olcay Boz

Sophie Liu

Stephen V Coggeshall

Yinghua Lin

Jianjun Xie

Guowei Wu

Quan Lu

David Zaleta

The present disclosure recites systems and methods for generating record clusters. For example, a computer-implemented method comprises receiving a plurality of records from data sources and providing at least a subset of the records to a scoring model that determines scores for various pairings of the records, a score for a given pair of the records representing a probability that the given pair of records contain data elements about the same entity. The method further comprises generating a graph data structure that includes a plurality of nodes, individual nodes representing a different record from the records. The method also comprises assigning a different unique identifier to individual clusters of the final clusters and responding to a request for data regarding a given entity by providing aggregated data elements from those records of the records associated with a cluster of the final clusters having an identifier that represents the given entity.

Single identifier platform for storing entity data

The features relate to artificial intelligence directed detection of user behavior based on complex analysis of user event data including language modeling to generate distributed representations of user behavior. Further features are described for reducing the amount of data needed to represent relationships between events such as transaction events received from card readers or point of sale systems. Machine learning features for dynamically determining an optimal set of attributes to use as the language model as well as for comparing current event data to historical event data are also included.

Behavior analysis using distributed representations of event data

Systems and methods are described for generating record clusters. The methods comprise receiving a plurality of records from data sources and providing at least a subset of the records to a scoring model that determines scores for various pairings of the records, a score for a given pair of the records representing a probability that the given pair of records contain data elements about the same entity. The method further comprises generating a graph data structure that includes a plurality of nodes, individual nodes representing a different record from the records. The method also comprises assigning a different unique identifier to individual clusters of the final clusters and responding to a request for data regarding a given entity by providing aggregated data elements from those records of the records associated with a cluster of the final clusters having an identifier that represents the given entity.

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

The features relate to artificial intelligence directed compression of user event data based on complex analysis of user event data including latent feature detection and clustering. Further features are described for reducing the size of data transmitted during event processing data flows and devices such as card readers or point of sale systems. Machine learning features for dynamically determining an optimal compression as well as identifying targeted users and providing content to the targeted users based on the compressed data are also included.

User behavior segmentation using latent topic detection

Various systems and methods are disclosed for accessing and traversing disparate, complex, and multi-dimensional data structures to dynamically and interactively generate reports based on automated modeling of complex and non-uniformly formatted data. Automated analysis of probabilistic functions and temporal-based data records enable non-technical users to quickly and dynamically act on time-sensitive information. In response to various user inputs, the system automatically accesses and traverses complex data structures (including, for example, frequency distribution models) calculates complex data based on the traversals, displays the calculated complex data to the user, and enters the calculated complex data into the reports.

Systems and methods for dynamic report generation based on automatic modeling of complex data structures

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

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San Diego, CA, United States of America

Shanji Xiong