Tax Calculation Engine Using Dynamic Graphs
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Solution Overview
Problem
Current tax return preparation systems are inefficient and labor-intensive, requiring users to navigate rigidly defined interfaces and perform unnecessary calculations, which can lead to increased time and computational resources being used.
Innovation Solution
The system employs declarative data structures such as completeness graphs and tax calculation graphs to dynamically calculate tax returns, allowing the user interface to be loosely connected from the tax calculation engine, with a smart tax logic agent suggesting questions to fill in missing data until all tax topics are covered, and only performing calculations affected by new user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional tax return preparation systems are used with rigidly defined interfaces and comprehensive calculations, then all tax topics are covered, but the system requires increased time and computational resources
Solution Approach 1:
The patent segments the tax calculation process into modular calculation graphs representing different tax topics (income, deductions, credits, etc.). Each graph can be independently evaluated for completeness, allowing the system to process only necessary portions rather than performing comprehensive calculations on all topics simultaneously. This segmentation enables selective processing that reduces overall preparation time while maintaining completeness of required tax topics.
Solution Approach 2:
The patent implements dynamic calculation graphs that adapt their structure and scope based on user inputs and detected completeness status. The system dynamically determines which calculation graphs need to be executed and to what depth, adjusting the calculation process in real-time based on the specific tax situation and missing data identification. This dynamic approach prevents unnecessary calculations while ensuring all required tax topics are covered.
2Measurement precision
If traditional tax return preparation systems perform comprehensive calculations, then accurate tax liability is determined, but computational resources are excessively consumed
Solution Approach 1:
The patent applies partial action by performing only the necessary subset of calculations required to determine accurate tax liability. The system identifies and executes only those calculation graphs that are relevant to the user's specific situation and that contain missing data, rather than performing exhaustive calculations on all possible tax topics. This partial processing maintains calculation accuracy for required topics while significantly reducing computational resource consumption.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors calculation progress, data completeness status, and intermediate results. Based on this feedback, the system dynamically adjusts which calculation graphs to execute next and prioritizes calculations that will most efficiently lead to complete and accurate tax liability determination. This feedback-driven approach prevents redundant calculations and optimizes computational resource usage.
3Reliability
If rigidly defined user interfaces are used in tax return preparation, then comprehensive data collection is achieved, but user experience becomes complex and time-consuming
Solution Approach 1:
The patent segments the user interface into context-relevant sections based on the current calculation state and identified missing data. Instead of presenting users with a comprehensive, static form containing all possible tax questions, the interface dynamically displays only the relevant calculation graphs and data entry fields needed at each step. This segmented approach maintains data completeness while significantly reducing perceived interface complexity and user time requirements.
Solution Approach 2:
The patent implements a dynamic user interface that adapts its content and structure based on real-time assessment of data completeness and calculation progress. The system dynamically determines which tax topics require user input and presents those specific areas through the interface, rather than displaying a fixed comprehensive form. This dynamic adaptation simplifies the user experience by showing only relevant information while ensuring all necessary tax data is collected.
Data Source
AI summary
Methods, systems and articles of manufacture for efficiently calculating an electronic tax return, such as within a tax return preparation system. A computerized tax return preparation system accesses taxpayer-specific tax data from a shared data store. The system executes a tax calculation engine configured to perform a plurality of tax calculations based on a tax calculation graph and the taxpayer-specific tax data from the shared data store. The system is configured to perform only the calculations in the tax calculation graph which are changed by new taxpayer-specific tax data received since the preceding tax calculation executed by the tax calculation engine. The system may also determine whether the new taxpayer-specific tax data does, or does not change the calculated tax return and the reason why.