Tax Calculation Engine Completeness Graph Dynamic Interface
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Solution Overview
Problem
Tax preparation is a time-consuming and laborious process due to the complexity of tax laws and the need for extensive user input, with existing software relying on rigid user interfaces that do not efficiently guide users through the necessary data collection for accurate tax calculations.
Innovation Solution
The use of declarative data structures, such as completeness graphs and tax calculation graphs, allows for a dynamic and adaptive user interface that suggests questions to fill in missing data, enabling the tax logic agent to evaluate current data and propose questions until all tax topics are covered, thereby preparing a complete tax return.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If rigid user interfaces are used for tax preparation, then the system structure is simple and stable, but the time required for tax preparation increases and user effort increases
Solution Approach 1:
The patent segments the tax preparation system into distinct modular components: a calculation engine that performs tax computations, a completeness graph that tracks required data elements, and a user interface manager that handles user interactions. This segmentation allows each component to operate independently and efficiently, improving overall productivity without overwhelming system complexity.
Solution Approach 2:
The system performs preliminary actions by pre-defining completeness graphs that identify all necessary tax data elements before the actual tax preparation begins. The calculation engine pre-calculates tax liabilities based on available data, and the system proactively identifies missing information, allowing users to provide data in any order rather than following a rigid sequential process.
2Measurement precision
If extensive user input is required for tax preparation, then the accuracy of tax calculations is improved, but the time and effort required increases
Solution Approach 1:
The system implements feedback mechanisms where the calculation engine continuously evaluates tax calculations based on user input and provides real-time feedback through the user interface manager. The completeness graph tracks which data elements have been provided and which are still needed, giving users feedback on their progress and guiding them to provide only the necessary missing information without redundant data entry.
Solution Approach 2:
The system performs self-service functions by automatically calculating tax liabilities, determining completeness status, and identifying missing data requirements without requiring users to manually verify each calculation step. The calculation engine autonomously processes user input and generates accurate tax results, while the interface manager automatically guides users through the data collection process.
3Ease of operation
If a dynamic and adaptive user interface is implemented, then the ease of operation is improved and tax preparation time is reduced, but the device complexity increases
Solution Approach 1:
The patent introduces an intermediary user interface manager that sits between the user and the complex calculation engine. This intermediary translates user interactions into calculation engine commands and presents results in an easy-to-understand format. The completeness graph serves as another intermediary layer that automatically tracks data completeness and guides the user interface manager, shielding users from the underlying system complexity while maintaining ease of operation.
Solution Approach 2:
The user interface is designed to be dynamic and adaptive, changing its behavior based on the current state of data completeness and the specific tax situation. The interface manager dynamically adjusts which questions are presented to users and in what order, based on real-time evaluation by the calculation engine and completeness graph, making the system adaptable to different user needs and situations.
Data Source
AI summary
A computer-implemented method of calculating tax liability using automatically generated estimates uses a computing device connecting to a shared data store configured to store user-specific tax data therein. The computing device executes an estimation module configured to estimate user-specific tax data and write the estimated user-specific tax data to the shared data store. A tax calculation engine configured to read user-specific tax data from the shared data store and write calculated tax data to the shared data store is executed, wherein at least some of the read data comprises estimated user-specific tax data.