Tax Liability Prediction System Using Dynamic User Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current tax preparation software is unreliable for predicting tax liabilities at intermediate times in the current tax year due to changes in income, life events, or tax laws, and users are unaware of tax benefits or consequences of tax events, leading to missed opportunities for reducing tax liabilities.
Innovation Solution
A method, system, and computer program that acquires both known and predicted user information, compares it with tax event information, and identifies relevant deductions or credits, projecting the impact of tax events like those reported on a 1099 form on tax liabilities, providing users with actionable recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional tax preparation software is used to determine tax liability, then the user can get a tax calculation based on previous year data, but the prediction is unreliable due to changes in income, life events, or tax laws
Solution Approach 1:
The system dynamically updates tax liability predictions as new information becomes available throughout the tax year. Instead of relying on static previous year data, the system continuously incorporates current income information, life events, and tax law changes to recalculate and update the predicted tax liability, making the prediction adaptive to changing conditions
Solution Approach 2:
The system implements feedback mechanisms by comparing actual tax events and income data against the initial prediction, then using this feedback to refine and update the tax liability estimate. The system notifies users of prediction adjustments and allows them to input new information that feeds back into the prediction model
2Adaptability or versatility
If the system provides comprehensive tax event analysis and deduction identification, then users can maximize tax benefits, but the system complexity increases
Solution Approach 1:
The system automatically performs comprehensive tax analysis by self-identifying applicable deductions and credits based on user information and tax events. Instead of requiring users to manually research and input all possible deductions, the system autonomously analyzes the user's situation, identifies relevant tax benefits, and incorporates them into the prediction, reducing the operational complexity for users while maintaining high adaptability
3Loss of information
If the system provides real-time tax liability prediction during the tax year, then users can make informed financial decisions, but the measurement precision requirements increase
Solution Approach 1:
The system provides tax liability predictions with appropriate precision levels based on the information available at each point in time. Rather than requiring complete certainty, the system delivers useful predictions using partial information and clearly indicates the level of certainty or range of the prediction, allowing users to make informed decisions without demanding unrealistic precision
Data Source
AI summary
A method, a system, and a computer program for predicting an impact of a tax event, such as reportable income on a 1099 form, on a user's tax liabilities at any intermediate time during a current tax year based on a comparison of known and predicted user information related to the user and the user's taxes, tax event information, and a tax deduction database of tax deductions, credits, and eligibility rules. The computer program and method for predicting the impact of the tax event comprise acquiring information about the user from a user profile, acquiring information about the tax event, comparing the user information and the tax event information with requirements for tax deductions and credits offered by a taxing authority, and identifying deductions or credits having requirements related to the user information and the tax event information.