Chime Financial, Inc.

Aoni Wang

Baishi Wu

Robert Luedeman

Paola Heneine

Dennis Jiang

Rakesh Vemulapally

Shashank Gadda

Aaron Plante

Aashna Agarwal

Erin Xie

Aditya Narula

Brooke Fraser

Braden Staudacher

Matt McCormick

Emily Bernier

Victoria Palmiotto

Akhil Naini

James Sheak

Lucy Liu

The disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that utilize a variety of machine learning models and a base limit value model to generate user interface elements that transparently and efficiently present current and future base limit values for user accounts. For example, the disclosed systems can utilize a machine learning model to determine a base limit value, subsequent base limit value, and user activity conditions to achieve the subsequent base limit value for a user account. Then, the disclosed systems can display a base limit progress element that indicates progress towards fulfilling the user activity conditions to achieve the subsequent base limit value. For example, the disclosed systems can display, within a graphical user interface, multiple base limit progress elements that indicate progress towards fulfilling the user activity conditions in separate time-based segments (e.g., to represent time elements within the user activity conditions).

Generating dynamic base limit value user interface elements determined from a base limit value model

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

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Redwood City, CA, United States of America

Aoni Wang