Intuit, Inc.

Madhu Shalini Iyer

Eva Diane Chang

Jeffrey Lewis Kaufman

Richard Neil Preece

Siddharth Ram

Joseph Timothy Callinan, Jr

Kathy Tsitovich

A method for utilizing an externally augmented propensity model for determining a future financial requirement. The method includes obtaining at least one propensity model that models how data associated with a business entity relates to a future financial requirement of the business entity, and gathering the data associated with the business entity. The data includes a first portion created based on a platform utilized by users associated with the business entity, and financial data of an owner of the business entity. The data matches at least a subset of the at least one propensity model. The business entity is scored by applying the at least one propensity model to the data. Further, based on the score, the future financial requirement of the business entity is classified. Still yet, a message is transmitted to the business entity based on the classification of the future financial requirement of the business entity.

Externally augmented propensity model for determining a future financial requirement

A method for modeling risk of a derogatory financial event. The method includes generating a risk profile of a small business (SMB) using a risk model based on accounting data and other third party business management application (BMA) data of the SMB. In particular, the risk model is generated using a training data set that includes accounting data and other third party BMA data of multiple SMBs over particular time periods related to historic derogatory events (e.g., to be delinquent and/or to default on a loan) of these SMBs. Generated using the risk model, the risk profile of the SMB represents the likelihood of a derogatory financial event occurring to the SMB.

Algorithm and models for creditworthiness based on user entered data within financial management application

A method for transmitting a message based on the occurrence of a workflow event and the output of an externally augmented propensity model. The method includes scoring a business entity by applying a propensity model to data. The data includes a first portion created based on a platform utilized by users associated with the business entity, and a second portion that includes financial data of an owner of the business entity. The method includes generating, based on the score, a classification of a future financial requirement of the business entity, and determining that the classification meets a financial requirement threshold. Moreover, the method includes determining, using the first portion of data, that an aspect of the business entity meets a business activity threshold. Also, the method includes detecting that a workflow event has occurred on the platform, and, in response, transmitting a message to a user of the business entity.

Transmission of a message based on the occurrence of a workflow event and the output of an externally augmented propensity model identifying a future financial requirement

A method for determining a future financial requirement of a business entity. The method includes obtaining a propensity model. The propensity model models how data of the business entity relates to a future financial requirement of the business entity. Also, the method includes gathering the data of the business entity. The data is created based on a platform utilized by the business entity, and the data of the business entity matches at least a subset of the propensity model. In addition, the method includes scoring the business entity by applying the propensity model to the data of the business entity. The method also includes generating, based on the score of the business entity, a classification of the future financial requirement of the business entity. Further, the method includes transmitting a message to the business entity based on the classification of the future financial requirement of the business entity.

Propensity model for determining a future financial requirement

A method for determining a future financial requirement of a business entity. The method includes obtaining a propensity model that models how data of a business entity relates to a future financial requirement. Also, the method includes gathering the data of the business entity. The data includes financial data of the business entity, and metadata describing use of a platform by users associated with the business entity. The data matches at least a subset of the propensity model. Further, the method includes scoring the business entity by applying the propensity model to the data of the business entity. In addition, the method includes generating, based on the score of the business entity, a classification of the future financial requirement of the business entity. Still yet, the method includes transmitting a message to the business entity based on the classification of the future financial requirement of the business entity.

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Fremont, CA, United States of America

Madhu Shalini Iyer