Sas Institute Inc.

Kevin Chaowen Chen

Revathi Subramanian

Paul Charles Dulany

Vijay Desai

Radu Drossu

Ho Ming Luk

Brian Lee Duke

William Szczuka

Andrew Engel

Daniel J Dotson

Systems and methods are provided for operation upon data processing devices are provided for operating with a fraud detection system. As an example, a system and method can be configured for receiving, throughout a current day in real-time or near real-time, financial transaction data representative of financial transactions initiated by different entities. At multiple times throughout the day, a summarization of the financial transaction data (which has been received within a time period within the current day) is generated. The generated summarization is used to determine whether fraud has occurred with respect to a financial transaction contained in the received authorization data or with respect to a subsequently occurring financial transaction.

Computer-implemented multiple entity dynamic summarization systems and methods

Systems and methods for performing fraud detection. As an example, a system and method can be configured to contain a raw data repository for storing raw data related to financial transactions. A data store contains rules to indicate how many generations or to indicate a time period within which data items are to be stored in the raw data repository. Data items stored in the raw data repository are then accessed by a predictive model in order to perform fraud detection.

Computer-implemented data storage systems and methods for use with predictive model systems

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San Diego, CA, United States of America

Kevin Chaowen Chen