Chime Financial, Inc.

Service Management Group, Inc.

Robert Luedeman

Baishi Wu

Paola Heneine

Aoni Wang

Aaron Plante

Rakesh Vemulapally

Shashank Gadda

Aditya Narula

Matt McCormick

James Sheak

Brooke Fraser

Victoria Palmiotto

Akhil Naini

Emily Bernier

Andrew Volpe

Eric H Weiss

Dennis Ehrich, Jr

Andrew Fromm

Qiulu Gong

The present disclosure relates to systems, non-transitory computer-readable media, and methods that, as part of an internetwork facilitation system, facilitate intelligent asset management through user interface elements that present selectable intelligent asset repayment models for user accounts. In particular, the systems can provide for display within a graphical user interface of a computing device corresponding to a user account, a selectable intelligent asset repayment element. Further, the systems can select an intelligent asset repayment model from a plurality of asset repayment models. Additionally, the systems can utilize the intelligent asset repayment model to transfer assets from the user account by: determining that the user account fails to satisfy an asset threshold corresponding to a deadline time, monitoring the user account for a post-deadline asset transfer; and in response to identifying the post-deadline asset transfer, initiating a digital transfer of assets from the user account according to an asset allocation hierarchy.

Facilitating intelligent asset management utilizing graphical user interfaces comprising dynamic asset management user interface elements

The disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that utilize a machine learning model and a credit value model to generate user interface elements that present credit values and credit value conditions in real time for user accounts. For instance, the disclosed systems can generate an activity score using an activity machine learning model with internal user activity data of a user account. Then, utilizing a credit value model with the activity score and a user activity condition, the disclosed systems can determine a dynamic credit value range for the user account. Indeed, the disclosed systems can display user interface elements with selectable credit values from the dynamic credit value range. Additionally, the disclosed systems can utilize the credit value model to determine and display one or more dynamic credit value conditions for a selected credit value received from the selectable credit values.

Generating graphical user interfaces comprising dynamic credit value user interface elements determined from a credit value model

A method and system are provided for providing incentives and rewards to consumers in return for their sharing of their electronically-derived consumer location data and sharing their opinions and feedback. The system may be programmed to determine parameters of a reward offered to an individual consumer or group of consumers based on or more criteria. In addition, location-derived insights and information reported by the consumers may be used to segment and customize the available incentives and rewards for each consumer. Reward redemption analytics may also be used to evaluate the effectiveness of reward customization.

Consumer analytics system that determines, offers, and monitors use of rewards incentivizing consumers to perform tasks

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San Francisco, CA, United States of America

Robert Luedeman