Card use risk assessment method and device based on big data behavior analysis

Abstract

The application relates to a card use risk assessment method and device based on big data behavior analysis. When a target card is used, real-time card use environment data is acquired by a card reading terminal integrated with an environment sensing module; based on historical card use records of a target card holder to be evaluated, a big data clustering algorithm is used to extract behavior characteristic indexes of the card holder, and a historical card use behavior characteristic matrix is constructed; real-time card use environment data is associated and mapped with the historical card use behavior characteristic matrix by a processor, and multiple card use behavior consistency characteristic indexes are calculated; a preset risk assessment model is used to score the consistency characteristic indexes, a risk score threshold value is adaptively adjusted according to acquired external dynamic parameters, corresponding risk assessment results are generated and output, and the method has the technical effects of expanding card use risk identification dimensions, improving environment sensing capability and reducing false alarm rates caused by rigid rules.

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