Call Screening Service Analyzing Voice Transcriptions for Fund Transfer Actions
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Solution Overview
Problem
Current call screening systems are inefficient in handling incoming calls that require specific actions, such as transferring funds, as they often necessitate additional steps on the user device and can be vulnerable to fraudulent requests, wasting computing resources and potentially leading to fraudulent transactions.
Innovation Solution
A user device equipped with a call screening service that analyzes voice input transcriptions for keywords related to fund requests, provides tailored input options, and performs actions like transferring funds directly upon user interaction, while incorporating a fraud detection system to assess the likelihood of fraudulent requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the user device performs additional steps to handle fund transfer requests during call screening, then the ability to perform custom actions is improved, but the device complexity and computing resource consumption increase
Solution Approach 1:
The call screening service is enhanced to perform multiple functions: it not only screens calls but also detects fund transfer requests, analyzes transcriptions for keywords, presents input options, and executes fund transfers. This multi-functionality allows the system to handle diverse call purposes through a single integrated service, improving adaptability without requiring separate systems for each function.
Solution Approach 2:
The system automatically analyzes voice transcriptions, detects fund transfer requests, and presents appropriate input options without requiring additional user configuration or manual intervention. The call screening service autonomously performs keyword analysis, fraud likelihood assessment, and action execution based on the call context, reducing the need for complex user-side configurations.
2Reliability
If the user device requires additional interactions to handle fund transfers, then the security is improved, but the ease of operation deteriorates
Solution Approach 1:
The system presents input options during the call screening process itself, allowing the user to authorize fund transfers before the call is fully answered. By obtaining user consent in advance during the screening phase, the system ensures security through explicit user authorization while streamlining the operation to require only a single interaction decision rather than multiple subsequent steps.
Solution Approach 2:
The system provides real-time feedback to the user by analyzing the voice transcription and presenting relevant input options related to the detected fund transfer request. This feedback loop allows the user to see what actions are available based on the call content and make informed decisions, improving ease of operation while maintaining security through user-aware authorization.
3Productivity
If the call screening service analyzes voice transcriptions for fund requests, then the productivity is improved, but the computing resource consumption increases
Solution Approach 1:
The system applies targeted keyword analysis specifically focused on fund transfer-related terms rather than performing comprehensive natural language processing on the entire transcription. By concentrating computational resources on detecting specific keywords and phrases related to fund requests, the system achieves high productivity in identifying relevant calls while minimizing overall computing resource consumption.
Solution Approach 2:
The system dynamically adjusts its analysis depth based on the call context and detected relevance. When fund transfer keywords are detected, the system performs detailed analysis and presents input options; for other calls, it performs minimal analysis. This parameter-based approach allows the system to optimize computing resource usage by intensifying processing only when necessary for productivity.
4Reliability
If the system provides tailored input options based on fraud likelihood, then the reliability is improved, but the device complexity increases
Solution Approach 1:
The system employs asymmetric processing where the level of analysis and input options provided varies based on the detected fraud likelihood. For calls with low fraud risk, minimal analysis is performed with standard options. For calls with high fraud risk indicators, more detailed keyword analysis is conducted and tailored input options are presented. This asymmetric approach improves reliability by focusing fraud detection resources on high-risk cases while avoiding unnecessary complexity for low-risk calls.
Data Source
AI summary
A user device may output an indication of an incoming call from a calling device. The user device may receive a request to screen the incoming call. The user device may analyze a transcription of voice input, received from the calling device, for one or more keywords related to a request for funds. The user device may output one or more input options, which permit a user of the user device to respond to the request for funds, including an input option to transfer funds from a first account associated with the user device to a second account associated with the calling device. The user device may detect a user interaction with the input option to transfer funds from the first account to the second account. The user device may transmit a request that causes funds to be transferred from the first account to the second account.