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公开(公告)号：US10608936B1
公开(公告)日：2020-03-31
申请号：US16157031
申请日：2018-10-10
Applicant: INTUIT INC.
Inventor： Christopher Z. Lesner , Nirmala Ranganathan
IPC: H04L29/06 , H04L29/08 , H04L12/741 , H04L29/12
Abstract: Certain aspects of the present disclosure provide a method of establishing a mapping between users of different applications to enable them to use contact information to initiate data exchange with each other.
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公开(公告)号：US20230222524A1
公开(公告)日：2023-07-13
申请号：US18180092
申请日：2023-03-07
Applicant: INTUIT INC.
Inventor： Vijay Manikandan JANAKIRAMAN , Kevin Michael Furbish , Nirmala Ranganathan , Kymm K. Kause
IPC: G06Q30/0601 , G06Q30/0201
CPC classification number: G06Q30/0631 , G06Q30/0201
Abstract: A processor may receive user interaction data of a user for a plurality of electronically-presented offers. The processor may generate a plurality of labels, the generating comprising generating a label for each respective offer according to a comparison of the quality of the user interactions of the respective offer to the frequency of the user interactions of the respective offer. Each label may be a positive label or a negative label. The processor may determine whether the generating produced both positive and negative labels. The processor may select one of a plurality of available ML models, wherein a two-class ML model is chosen in response to determining that the generating produced both positive and negative labels and a one-class ML model is chosen in response to determining that the generating did not produce both positive and negative labels. The selected ML model may be trained and/or may be used to process user profile data and provide recommendations.
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公开(公告)号：US20230043430A1
公开(公告)日：2023-02-09
申请号：US17397801
申请日：2021-08-09
Applicant: Intuit Inc.
Inventor： Daniel Ben David , Saikat Mukherjee , Nirmala Ranganathan , Yair Horesh
Abstract: A method including generating, by a state engine from data describing behaviors of users in an environment external to the state engine, an executable process. An agent executes the executable process by determining, from the data describing the behaviors of the users, a problem of at least some of the users, and selects, based on the problem, a chosen action to alter the problem. At a first time, a first electronic communication describing the chosen action to the at least some of the users is transmitted. Ongoing data describing ongoing behaviors of the users is monitored. A reward is generated based on the ongoing data to change a parameter of the agent. The parameter of the agent is changed to generate a modified agent. The modified agent executes the executable process to select a modified action. At a second time, a second electronic communication describing the modified action is transmitted.
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公开(公告)号：US11861633B2
公开(公告)日：2024-01-02
申请号：US18180092
申请日：2023-03-07
Applicant: INTUIT INC.
Inventor： Vijay Manikandan Janakiraman , Kevin Michael Furbish , Nirmala Ranganathan , Kymm K. Kause
IPC: G06Q30/02 , G06Q30/0201 , G06F16/215 , G06N20/10 , G06Q30/0207 , G06F18/24 , G06Q30/0601
CPC classification number: G06Q30/0201 , G06F16/215 , G06F18/24 , G06N20/10 , G06Q30/0239 , G06Q30/0631
Abstract: A processor may receive user interaction data of a user for a plurality of electronically-presented offers. The processor may generate a plurality of labels, the generating comprising generating a label for each respective offer according to a comparison of the quality of the user interactions of the respective offer to the frequency of the user interactions of the respective offer. Each label may be a positive label or a negative label. The processor may determine whether the generating produced both positive and negative labels. The processor may select one of a plurality of available ML models, wherein a two-class ML model is chosen in response to determining that the generating produced both positive and negative labels and a one-class ML model is chosen in response to determining that the generating did not produce both positive and negative labels. The selected ML model may be trained and/or may be used to process user profile data and provide recommendations.
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Patent Agency Ranking
公开(公告)号：US11544780B2
公开(公告)日：2023-01-03
申请号：US16937400
申请日：2020-07-23
Applicant: Intuit Inc.
Inventor： Daniel Ben David , Yehezkel Shraga Resheff , Yair Horesh , Nirmala Ranganathan
Abstract: This disclosure relates to systems and methods for constructing a customized debt reduction plan for a user. In some implementations, a customized debt reduction system obtains a plurality of financial attributes of the user and a plurality of other users, where the plurality of financial attributes are indicative of credit card debt, and identifies users from the plurality of other users who successfully repaid their credit card debt based on their respective financial attributes and one or more repayment techniques that resulted in successful repayment of their credit card debt. The customized debt reduction system correlates the plurality of financial attributes of the user with the plurality of financial attributes of a number of the identified users and determines a personalized score for the user, using a trained machine learning model, based on the correlation to determine a customized debt reduction plan for the user based on the personalized score.
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公开(公告)号：US20220027983A1
公开(公告)日：2022-01-27
申请号：US16937400
申请日：2020-07-23
Applicant: Intuit Inc.
Inventor： Daniel Ben David , Yehezkel Shraga Resheff , Yair Horesh , Nirmala Ranganathan
Abstract: This disclosure relates to systems and methods for constructing a customized debt reduction plan for a user. In some implementations, a customized debt reduction system obtains a plurality of financial attributes of the user and a plurality of other users, where the plurality of financial attributes are indicative of credit card debt, and identifies users from the plurality of other users who successfully repaid their credit card debt based on their respective financial attributes and one or more repayment techniques that resulted in successful repayment of their credit card debt. The customized debt reduction system correlates the plurality of financial attributes of the user with the plurality of financial attributes of a number of the identified users and determines a personalized score for the user, using a trained machine learning model, based on the correlation to determine a customized debt reduction plan for the user based on the personalized score.
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公开(公告)号：US20220253930A1
公开(公告)日：2022-08-11
申请号：US17172551
申请日：2021-02-10
Applicant: Intuit Inc.
Inventor： Daniel Ben David , Saikat Mukherjee , Nirmala Ranganathan , Kymm Kause , Yair Horesh
IPC: G06Q40/02 , G06F16/2458 , G06F16/2457 , G06F16/28
Abstract: Systems and methods for generating a credit profile based on user behavior traits are disclosed. A system may be configured to obtain a plurality of financial based interactions of a user, generate one or more behavior trait indicators based on the plurality of financial based interactions, and generate the credit profile of the user based on the one or more behavior trait indicators. A behavior trait indicator may include a self-control indicator regarding discretionary spending, an ostrich bias indicator regarding user interactions after negative news or events, or a procrastination indicator based on voluntary late payments to user accounts.
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公开(公告)号：US11315177B2
公开(公告)日：2022-04-26
申请号：US16429119
申请日：2019-06-03
Applicant: Intuit Inc.
Inventor： Kevin Furbish , Nirmala Ranganathan , Aaron Dibner-Dunlap , Sumayah Rahman
IPC: G06Q40/02
Abstract: A processor may obtain financial data for a user. The processor may process the financial data to generate feature data indicative of at least one feature. The processor may compare the at least one feature to at least one threshold value to determine that the user has a cognitive bias affecting a financial preference of the user and associated with the at least one threshold value. The at least one threshold value may denote a threshold for membership in a cluster of unlabeled users having the cognitive bias. In response to the comparing, the processor may identify a change applicable to a financial account of the user. The change may be associated with the cognitive bias. The processor may automatically cause the change to be implemented by a network-accessible financial service.
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公开(公告)号：US20210304284A1
公开(公告)日：2021-09-30
申请号：US16836305
申请日：2020-03-31
Applicant: Intuit Inc.
Inventor： Daniel Ben David , Yehezkel Shraga Resheff , Nirmala Ranganathan , Yair Horesh
Abstract: A method may include obtaining, over a network from a financial institution and using login credentials of a user, transactions corresponding to the user, calculating average transaction amounts for merchants based on the transactions, generating a spending propensity score for a category using a harmonic mean of amounts in a subset of the transactions corresponding to the category, generating, for the category, spending match scores between the spending propensity score and the average transaction amounts for the merchants, and recommending a merchant to the user using the spending match scores.
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