Importance

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Abstract

An artificial intelligence fraud management system comprises real-time analytics process for analyzing the behavior of a user from the transaction events they generate over a network. An initial population of smart agent profiles is stored in a computer file system and more smart agent profiles are added as required as transaction data is input. Vectors are assigned to point to a run of profile data that all share the same atomic time interval. The vectors are rolled around to point to newer time intervals as they occur, retiring vectors to expired time intervals, and reassigning those vectors to point to the newer atomic time intervals. Vectors correspond to particular smart agent profiles (P) and are collected into lists stored in profile blocks with a meta-data header. Transactions that involve a particular entity are made quickly accessible and retrievable by such vectors.

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First Claim