Tax Return System Using Analytics Models for Dynamic Interview Sequencing

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Traditional tax return preparation systems are inflexible and delay the presentation of earned income tax credit benefits, leading to user frustration and increased abandonment of the tax return preparation session, as they require users to complete a lengthy interview process before providing relevant information.

Innovation Solution

Applying analytics models to determine a user's likelihood of qualifying for the earned income tax credit, allowing for early estimation and presentation of benefits, and selectively omitting or delaying irrelevant questions based on user data, thereby reducing the duration of the tax return preparation session.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If traditional tax return preparation systems use a fixed, predetermined sequence of interview questions, then the system structure is simple and easy to implement, but the user experience becomes frustrating and users abandon the session due to delayed presentation of earned income tax credit benefits

Engineering Contradiction:

Improveuser experienceVSAvoidsystem structure

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The patent implements dynamic question sequencing that adapts to user responses and characteristics. The system transitions from static, predetermined question sequences to dynamic sequences that are customized in real-time based on user inputs, allowing the interview flow to adapt and evolve during the tax preparation session.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes parameters such as question selection, sequencing, and presentation based on user characteristics and responses. By dynamically adjusting these parameters, the system optimizes the user experience while maintaining operational simplicity through automated parameter management.

Inventive Principle:

Principle #35Parameter changes

2Productivity

If the system presents all interview questions in a fixed sequence, then the system is easy to implement, but the duration of the tax return preparation session increases leading to user frustration and abandonment

Engineering Contradiction:

Improvesession completion rateVSAvoidsession duration

Core Design Contradiction:

ProductivityVSDuration of action of moving object

Solution Approach 1:

The patent extracts and prioritizes critical information about earned income tax credit eligibility early in the interview process. By identifying and presenting key benefits upfront based on user characteristics, the system removes the frustration of waiting through lengthy question sequences without sacrificing thoroughness.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system performs preliminary analysis of user characteristics and preliminary presentation of earned income tax credit benefits before completing the full interview sequence. This allows users to see potential benefits early, motivating them to complete the remaining questions while reducing overall session duration.

Inventive Principle:

Principle #10Preliminary action

3Productivity

If the system provides detailed earned income tax credit information early in the interview, then user motivation and completion rate improve, but the system complexity and processing requirements increase

Engineering Contradiction:

Improvesession completion rateVSAvoidanalytics model complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent introduces analytics models as intermediaries that process user characteristics and predict earned income tax credit eligibility. These models act as mediators between raw user data and the interview system, enabling early presentation of relevant benefits without requiring complex custom logic throughout the entire system.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system uses feedback from analytics models about user eligibility characteristics to dynamically adjust the interview sequence and information presentation. This feedback mechanism allows the system to provide targeted early information about earned income tax credit benefits based on predicted eligibility, improving completion rates while managing complexity through model-driven decisions.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS10169828B1Method and system for applying analytics models to a tax return preparation system to determine a likelihood of receiving earned income tax credit by a user

Publication Date: 2019.01.01 INTUIT INC

AI summary

A method and system applies analytics models to a tax return preparation system to determine a likelihood of qualification for an earned income tax credit by a user, according to one embodiment. The method and system receive user data and applying the user data to a predictive model to cause the predictive model to determine, at least partially based on the user data, a likelihood of qualification for an earned income tax credit for the user, according to one embodiment. The method and system display, for the user, an estimated tax return benefit to the user, at least partially based on the likelihood of qualification for the earned income tax credit exceeding a predetermined threshold, to reduce delays in presenting estimated earned income tax credit benefits to the user during a tax return preparation session in a tax return preparation system, according to one embodiment.