Date of Publication :20th March 2024

Abstract:Fraud prevention is an important capability to detect unlawful transactions and minimize the losses due to unlawful transactions. All companies and banks want their framework and infrastructure secure for money transfer in this activity. The challenge of controlling fraud has increased substantially, demanding fraud analysts with adequate mechanisms for defining fraud policies and system architecture for large-scale real-time streaming applications arising from multiple channels at different windows. In this paper, I describe a fraud management framework, including a rule-based financial model language for the conceptual level of modeling and validation for fraud policies, fraud prevention techniques, and implementation of fraud policies using stream SQL. The critical element in streaming is detecting fraud proactively, blocking the transactions encompassing suspicious click stream patterns. This framework is designed for multi-transaction processing and micro-transaction processing.

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