At step 402, process 400 (e.g., using one or more components in system 200 (FIG. 2)) receives a user action. For example, the system may receive one or more user inputs to a user interface (e.g., user interface 100 (FIG. 1)). The system may then determine a likely intent of the user in order to generate one or more dynamic conversational responses based on that intent. The user action may take various forms include speech commands, textual inputs, responses to system queries, and/or other user actions (e.g., logging into a mobile application of the system). In each case, the system may aggregate information about the user action, information about the user, and/or other circumstances related to the user action (e.g., time of day, previous user actions, current account settings, etc.) in order to determine a likely intent of the user.

At step 404, process 400 (e.g., using one or more components in system 200 (FIG. 2)) determines an intent of a user based on a two-tier machine learning model. For example, the system may first use a first tier of a model (e.g., model 320 (FIG. 3)) to determine an intent cluster of the user's intent. The system may then determine a second tier of a model (e.g., model 330 (FIG. 3)) to determine a specific intent of the user's intent.