Conversational Flow Prediction for Proactive Banking Assistance
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Solution Overview
Problem
Existing online banking systems lack the ability to anticipate user questions and provide relevant information proactively, requiring users to manually request assistance, which can be inefficient and time-consuming.
Innovation Solution
A system and method that utilizes a back-end server with a processor and memory device to analyze user data flow, enabling a bot to identify the user's process and provide helpful information without explicit user queries, employing artificial intelligence and machine learning techniques such as neural networks to enhance user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the system provides traditional reactive customer service where users must manually request assistance, then the system complexity remains low, but the user experience and efficiency deteriorate due to manual inquiries being time-consuming
Solution Approach 1:
The system performs preliminary actions by proactively analyzing user data flow and predicting questions before users actually ask them. The bot identifies what information the user is entering and displays helpful information in advance, eliminating the need for users to manually request assistance and significantly improving ease of operation.
2Productivity
If the system implements proactive information delivery through AI analysis, then productivity and efficiency improve, but the device complexity increases due to AI and machine learning components
Solution Approach 1:
The system implements self-service by enabling the bot to automatically analyze user data flow, identify process context, predict user questions, and deliver relevant information without human intervention. This automated self-service approach significantly improves transaction efficiency while the AI complexity is managed through specialized modules.
Solution Approach 2:
The bot acts as an intermediary between the user and the banking system. It analyzes data flow, predicts user needs, and delivers information proactively, serving as a mediator that bridges the gap between complex system capabilities and simple user interactions, thereby improving productivity without directly exposing system complexity to users.
3Loss of information
If the bot analyzes user data flow to predict questions, then information relevance improves, but the loss of time for data processing increases
Solution Approach 1:
The system performs preliminary analysis of data flow as users are entering information, predicting their questions before they actually ask them. This preliminary action ensures high information relevance by delivering exactly what the user needs, while the processing is optimized to occur in the background without significant user-perceived delay.
Solution Approach 2:
The bot continuously monitors and analyzes user data flow in real-time as users interact with the application. This continuous analysis enables the system to predict questions and deliver relevant information promptly, maintaining high information relevance while processing data efficiently in the background to minimize time loss.
Data Source
AI summary
A system and method for anticipating a question by a user based on data flow when using a digital application and providing an answer to the question. The system includes a back-end server operating the digital application and having a processor for processing data and information, a communications interface communicatively coupled to the processor, and a memory device storing data and executable code. When the code is executed, the processor can allow a user to enter information into a certain process, cause a bot to identify what process flow the user is entering information into and where in the process flow the user is, cause the bot to identify what information the user is entering into the process flow, and cause the bot to display information to the user in response to the information the user is entering into the process flow without the user asking for the information.