Continual Graph Neural Risk Scoring for Millisecond-Scale Fraud Prevention
Keywords:
graph neural networks, continual learning, fraud detection, risk scoring, adaptive embeddings, behavioral driftAbstract
Millisecond-scale decisioning under the evolved behavioural pattern which allows real-time fraud prevention in financial systems. The objective of this research paper is to introduce a Continual Graph Neural Risk Scoring (CGNRS) framework which is a synergy of graph neural network and continual learning to assess transaction risk adaptively.
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