Intuit, Inc.

Per-Kristian G Halvorsen

Gang Wang

Luis Felipe Cabrera

Kevin M McCluskey

William Taylor Laaser

Michael J Graves

David Alan Hanekamp, Jr

Arien C Ferrell

Cem Unsal

Alex G Balazs

Saikat Mukherjee

Anu Sreepathy

Mritunjay Kumar

Roger Charles Meike

Amir R Eftekhari

Jay J Yu

Gerald Baron Huff

Daniel P Dunbar

Michael A Artamonov

Calum G Murray

Jennifer Lynn Keenan

Esmé Manandise

Todd Elliott

Matthew A Lisowski

Jason Hardiman

Thac S Pham

Kevin M Mccluskey

This disclosure provides systems, methods and apparatuses for converting natural language text in financial documents to mathematical operations for a financial management program. In some implementations, a computing device may obtain a first segment of computer readable text associated with a text capture in a financial document, parse only a portion of the first segment to generate a parsed segment, and determine translation information associated with the parsed segment to translate the parsed segment. The computing device may also store the parsed segment and the translation information in a data structure in memory, translate the parsed segment in the data structure based on the translation information, and output one or more computer readable mathematical operations corresponding to the translated segment. In this manner, the computing device may output the one or more computer readable mathematical operations without parsing all of the segment.

Financial document text conversion to computer readable operations

A method and system to learn new forms to be incorporated into an electronic document preparation system, or to learn the behavior of existing systems, receive form data related to a new form having a plurality of data fields that expect data values based on specific functions. The method and system gather training set data including previously filled forms having completed data fields corresponding to the data fields of the new form. The method and system include multiple analysis modules that each generate candidate functions for providing data values for the data fields of the new form. The method and system evaluate the candidate functions from each analysis technique and select the candidate functions that are most accurate based on comparisons with the training set data.

System and method for automatically generating calculations for fields in compliance forms

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.

System and method of generating estimates used to calculate taxes

A computer-implemented method for inferring or estimating user-related data for use with tax preparation software is disclosed. The method uses a computer that connects to the one or more remotely located data sources and executing a data capture utility, the data capture utility capturing at least some tax data pertaining to the user. The computing device executes an estimation module that receives the captured tax data pertaining to the user and generates one or more estimates and stores the one or more estimates in a data store associated with the tax preparation software, the data store configured to store user-specific tax data therein. The computing device executes a tax calculation engine of the tax preparation software configured to read the user-specific tax data contained in the data store and compute an intermediate or final tax liability or refund amount.

System and method for automated data estimation for tax preparation

Systems, methods and articles of manufacture for analyzing past year tax data for a taxpayer and determining an estimated current year tax liability in order to compute estimated tax payments. The tax preparation system comprises a tax estimate engine configured to access a plurality of calculated past year tax calculation graphs. The tax estimate engine analyzes and compares the calculated past year tax calculation graphs to determine similar node(s) and/or dissimilar node(s) and also determines a similar node estimating value for the similar nodes and/or a dissimilar node estimating value for the dissimilar nodes. A tax calculation engine calculates a current year tax calculation graph using the similar node estimating values and/or dissimilar node estimating values. The calculated current year tax calculation graph includes an estimated tax liability for the current year, which the system uses to compute estimated tax payments for the taxpayer for the current tax year.

Systems and methods for analyzing and determining estimated data

Methods, systems and articles of manufacture for a method for generating a database of tax correlation data which can be used for tailoring a user experience in preparing an electronic tax return. A computing device accesses a data source having a plurality of data records. Each data record comprises a taxpayer attribute and a tax related aspect for a respective taxpayer. The computing device analyzes the plurality of data records and determines a correlation between the taxpayer attribute and the tax related aspect and determines a probability for the correlation. The computing device utilizes the probability for the correlation to determine a quantitative relevancy score for a tax matter, which can be incorporated into the tax correlation data of the life/knowledge module.

Methods systems and articles of manufacture for tailoring a user experience in preparing an electronic tax return

A computer-implemented method for generating an explanation for changes in tax liability over different tax reporting periods includes a computing device executing a tax calculation engine associated with tax preparation software. The tax calculation engine operates on first and second tax calculation graphs representing different tax reporting periods. The first and second tax calculation graphs are different in at least one respect. The first and second tax calculation graphs each describe data dependent tax operations comprising a plurality of interconnecting functional nodes connected by one of a plurality of functions. The computing device automatically identifies the differences among nodes within the respective first and second tax calculation graphs and executes an explanation engine associated with the tax preparation software to generate a textual explanation identifying one or more differences among the nodes.

System and method for generating explanations for year-over-year tax changes

Computer-implemented systems, methods and articles for preparing and/or submitting a plurality of different types of compliance forms for submission to a regulatory agency. The system includes a computing device, a data store, and a compliance form software program executable by the computing device. The compliance program includes a universal calculation engine, logic agent and user interface manager which are configured to process a respective domain model configured for each type of compliance form. Each domain model includes a calculation graph, a completeness model comprising decision table(s) and/or completeness graph(s), user interface assets and filing rules configured specifically for a particular type of compliance form. The rules and regulations for each type of compliance form are embodied in the declaratory data structures of the respective calculation graph and completeness graph for each domain model. The calculation engine and logic agent are configured to process the calculation graph and completeness graph, respectively.

Computer-implemented systems and methods for preparing compliance forms to meet regulatory requirements

A computer-implemented method for gathering user-related tax data for use with tax preparation software includes a computing device executing a data capture utility configured to connect to one or more remotely located data sources, wherein the data capture utility captures user-specific tax data from the one or more remotely located data sources and stores the captured data in a data store. The computing device executes a tax logic engine configured to read data from the data store and determine the completeness of the data contained within the data store. The computing device communicates a message to the user regarding the level of completeness of the data contained within the data store.

System and method for automated data gathering for completing form

System and method for automated data gathering for tax preparation

Systems and methods for analyzing and determining estimated taxes

A method for collecting a payment. The method includes sending, to a payor, a request for the payment, wherein the request comprises an original payment amount and an original payment due date, generating, based on a set of payment collection records from an online financial management application used by payees, a payment statistical measure representing a payment behavior of payors paying the payees, generating, based on the payment statistical measure, the original payment amount, and the original payment due date, an adjusted payment amount and a condition to qualify the adjusted payment amount for completing the payment, enabling, prior to the payor completing the payment, the payor to view the adjusted payment amount and the condition, wherein the payor completes the payment in response to at least the payor viewing the adjusted payment amount and the condition, and collecting the payment completed by the payor.

Gamification of fields in online e-commerce documents

The disclosed embodiments relate to a tax-information assembly technique, which extracts tax information and associated context information from income-tax documents, where these income-tax documents are associated with an income-tax agency, and some of the income-tax documents include the same tax information in different document formats. During this technique, semantic and structural heuristics are used to identify tax phrases in the extracted tax information. Moreover, additional tax phrases in the extracted tax information are identified using a statistical identification technique. Next, relationships between the tax phrases and the additional tax phrases are determined, and the context information is used to consolidate the tax phrases and the additional tax phrases into a tax-information data structure.

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Mountain View, CA, United States of America

Per-Kristian G Halvorsen