Apparatus and method for federated tracking of fraudulent activity

Abstract

An apparatus and method for federated fraud risk management. Signals from multiple entities engaged in financial, transactional, or compliance data exchange are securely ingested, normalized, and enriched with external and internal data. A scoring module employs one or more analytical techniques, such as statistical methods or neural and non neural models, to compute one or more risk scores across multiple operational, transactional, or identity linked dimensions. A decision component generates and transmits alerts to authorized systems and may route, hold, or escalate operations based at least in part on the computed score. The apparatus and method support privacy preserving collaborative training using techniques such as federated learning, homomorphic encryption, or approaches. Processing may escalate to external systems, generate or update a record, or supply derived data for model retraining. The operations may be performed in any order or in parallel.

CPC Classifications