Communication Analysis Using NLP for Accurate Issue Recording
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Solution Overview
Problem
Bank customers often face challenges in accurately recording issues and concerns during calls with bank representatives, leading to potential misinterpretation and delayed resolution of issues.
Innovation Solution
The implementation of a computing system that leverages speech-to-text and natural language processing algorithms to transcribe conversations, generate word clouds, and determine appropriate actions, thereby facilitating more accurate note-taking and issue resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual note-taking is used during customer calls, then agents can document issues discussed, but the accuracy and completeness of recorded information deteriorates due to human error and distraction
Solution Approach 1:
The system enables self-service by automatically transcribing conversations and generating notes without requiring manual agent intervention. The speech-to-text algorithm and NLP processing occur autonomously, capturing all conversation details accurately while freeing agents from manual note-taking tasks.
Solution Approach 2:
The patent replaces the mechanical system of manual note-taking with an automated computational system. Speech-to-text algorithms and natural language processing substitute human agents' writing and listening tasks, dramatically improving accuracy and completeness of recorded information.
2Loss of information
If agents focus on making manual notes during calls, then documentation can be created, but the quality of customer service deteriorates due to divided attention
Solution Approach 1:
The automated transcription and note-generation system performs documentation tasks independently, allowing agents to maintain full attention on customers. The system serves itself by capturing, transcribing, and structuring conversation data without human intervention, thereby improving both documentation quality and service quality simultaneously.
3Loss of information
If comprehensive notes are taken manually during calls, then more details are captured, but the time required for note-taking increases
Solution Approach 1:
The patent replaces time-consuming manual note-taking with automated speech-to-text and NLP processing. The system captures comprehensive conversation details in real-time or near-real-time, eliminating the time agents would spend manually documenting while maintaining or improving detail levels through automated transcription of the entire conversation.
4Productivity
If manual processing of conversation data is used, then simple notes can be created quickly, but the accuracy of identifying appropriate actions deteriorates
Solution Approach 1:
The patent replaces simple manual note-taking with sophisticated automated processing using speech-to-text algorithms and natural language processing. The system quickly transcribes conversations and accurately identifies appropriate actions by analyzing conversation context, customer issues, and required resolutions, achieving both high speed and high accuracy simultaneously.
Data Source
AI summary
This disclosure describes techniques that include facilitating note-taking in various contexts, including when a customer is speaking to an agent of a business. In one example, this disclosure describes a method that includes analyzing, by a computing system, communications between a customer of an organization and an agent of the organization, where the communications include an issue to be addressed by the organization; generating, by the computing system, artifacts of the communication between the customer and the agent; determining, based on the artifacts of the communication, an action to be taken to address the issue; and generating, by the computing system, a user interface providing options associated with addressing the issue.