Continuous api-based fraud detection using sequences

Abstract

A state-based continuous detection and monitoring systems detects a fraud ring over time. The present system may perform modular detection (at the state level) and hierarchical detection (at the sequence level) covering different approaches of fraudulent activities, both separately and jointly. Once a fraudulent event is detected in a state or sequence, a severity score is determined using a machine learning. A complete fraud investigation platform is implemented which uses out-of-the-box detection mechanisms while allowing users to define their own event detection as well. The state-based detection and continuous monitoring with visibility into the details of API activity allow the present system to detect fraudulent rings perpetrated by one or more users.

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