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AssigneeBank of America Corporation
InventorsSivashalini Sivajothi, Maneesh Kumar Sethia, Boddu Vikas Teja, Ankit Kumar Sahoo
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Systems and processes are disclosed for a multi-layered approach to fraud prevention by leveraging a machine learning engine integrated with the Session Initiation Protocol (SIP) to attempt caller identification before transitioning to a voice call, allowing for the potential blocking of unwanted calls. If SIP-based identification remains inconclusive, an anomaly detection engine employing the Viterbi algorithm analyzes the caller’s speech patterns during voicemail messages. The Viterbi algorithm converts spoken language into text, identifying suspicious characteristics such as unusual speech patterns, inconsistencies, and keywords associated with scams. If suspicious characteristics are detected, the system automatically blocks callback attempts and notifies the customer of potential spam or unwanted calls. This proactive approach addresses both live and recorded fraudulent calls, enhancing the security of telecommunications by preventing fraudulent interactions before they can cause harm. The system continuously learns from new data, adapting to evolving fraud tactics, providing robust, long-term protection for telecommunications users.
A computer-implemented method for detecting potential fraud during an in-person banking interaction, performed by a computing system comprising a processor and memory storing instructions that, when executed, cause the computing system to:
A fraud-detection system for in-person banking interactions, comprising:
A computer-implemented method for detecting potential fraud during an in-person banking interaction, performed by a computing system comprising a processor and memory storing instructions that, when executed, cause the computing system to:
Dependencies are inferred from the claim text.