Experian Information Solutions, Inc.

Eric Haller

Kelly Kent

Kevin Chen

Zhixuan Wang

Alan Tsang

Mark Hirn

Christer Dichiara

Derek Toub

Christopher Wheeler

Steven Yin

Sreeram Upendran

David Kerry

Jack Yu

Hua Li

Juncheng C Liu

Steve Yin

Shumin Guo

The systems and methods described herein allow consumers to lock or unlock their credit files at multiple credit bureaus in real-time or near real-time. The service may allow a consumer to provide identifying information, such as a personal identifier to lock or unlock credit files at a plurality of credit bureaus over a network. Upon receiving the personal identifier, the system may use the personal identifier to translate the identifier into a plurality of access codes for respective credit bureaus, for example by accessing a data structure, such as a database or table, that stores a personal identifier and access codes that are associated with a consumer. The system may then use the access codes to automatically initiate locking or unlocking of credit files for the consumer at the respective credit bureaus.

Multi-bureau credit file freeze and unfreeze

Systems and methods for data aggregation and processing are provided in manner that is decentralized and preserves privacy. A data aggregation and computation system may include an interface, a controller, and one or more clusters of computation nodes. The interface may receive an inquiry from a requesting entity for computing information regarding an individual based on pieces of information held by a plurality of entities. The controller may communicate an identifier for the individual to a processor system associated with each of the entities based on the inquiry. The clusters of computation nodes may each receive encrypted data fragments from each of the processor systems, the data fragments comprising unrecognizable fragments that no individual processor system can re-assemble to recover the information, perform secure, multi-party computations based on the data fragments, and generate a result based on the secure, multi-party computations for the individual.

Systems and methods for secure data aggregation and computation

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

Systems and methods for verifying data including income and employment, assets, healthcare claims, clinical data, and other types of data subject to various regulatory and/or privacy restrictions.

Systems and methods for data verification

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Escondido, CA, United States of America

Eric Haller