Completeness Graph Engine for Tax Return Explanation Assets
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Solution Overview
Problem
Electronic tax return preparation systems often confuse users with seemingly misplaced or unreasonable tax questions, leading to fear, uncertainty, and doubt, which can result in abandonment of the preparation process, especially when additional questions arise from modified tax data in previously completed topics.
Innovation Solution
A system and method that utilize a completeness graph engine to identify added variables in tax topics, sending them to an explanation engine and user interface controller to generate and present explanation assets alongside tax questions, thereby clarifying the need for specific tax data and reducing user anxiety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the tax return preparation system asks more questions to ensure completeness after modified tax data is entered, then the accuracy and completeness of tax information is improved, but user anxiety and abandonment rate increase
Solution Approach 1:
The system performs preliminary actions by proactively generating and presenting explanation assets before users encounter confusion or anxiety. When tax data is modified, the completeness graph engine预先 identifies what additional questions will be needed and prepares explanation assets that clarify why these questions are asked, so users are not surprised or confused when the questions appear.
Solution Approach 2:
Explanation assets serve as intermediaries between the tax return preparation system and the user. Instead of directly presenting additional questions that may confuse users, the system first presents explanation assets that clarify the purpose and relevance of upcoming questions, acting as a mediator that reduces user anxiety and improves understanding.
2Loss of information
If the system presents additional tax questions after modified tax data, then the completeness of tax information is improved, but user confusion and uncertainty increase
Solution Approach 1:
The system implements feedback by monitoring when tax data is modified and automatically triggering the generation of explanation assets. The completeness graph engine detects changes in tax data, determines what additional information is needed, and presents explanation assets that provide feedback to users about why additional questions are necessary, thereby maintaining clarity while ensuring data completeness.
Solution Approach 2:
The system performs preliminary actions by generating explanation assets before presenting additional tax questions. This preliminary explanation prepares users for the upcoming questions, reducing confusion and uncertainty while ensuring that all necessary tax information is collected.
3Measurement precision
If the system monitors and compares snapshots of completeness graph to identify added variables, then the accuracy of identifying necessary tax questions is improved, but system complexity increases
Solution Approach 1:
The system applies segmentation by dividing the tax return preparation system into distinct functional modules: a completeness graph engine that monitors and compares snapshots to identify added variables, an explanation asset generation component, and a presentation component. This segmentation allows each module to specialize in its specific function, improving the accuracy of identifying necessary tax questions while managing system complexity through modular design.
Solution Approach 2:
The completeness graph engine acts as an intermediary that mediates between the tax data input and the question generation process. It monitors changes in tax data, compares snapshots to identify added variables, and triggers the generation of appropriate explanation assets, thereby improving measurement precision while maintaining manageable system complexity through its intermediary role.
Data Source
AI summary
A system for explaining added tax questions resulting from modified tax data for an electronic tax return preparation program includes a computing device having a completeness graph engine, an explanation engine, and a user interface controller. The computing device executes the completeness graph engine, which takes a first snapshot of input needs for a completeness graph corresponding to a tax topic, takes a second snapshot of input needs for the completeness graph corresponding to the tax topic after receiving modified tax data, and compares the first and second snapshots to identify an added variable in the completeness graph. An explanation engine analyzes the completeness graph and the modified tax data to generate an explanation asset for the added variable. A user interface controller generates a tax question corresponding to the added variable. The computing device presents the tax question and the explanation asset to a user.