Method and system for predicting user intentions within a digital banking application

A non-transitory computer readable medium have stored thereon computer program code that is executable by at least one processor and that, when executed by the at least one processor, causes the at least one processor to perform a method comprising:

• acquiring a pathway dataset excluding financial information as a user navigates in a digital banking application in a current user session, the pathway dataset comprising a time-ordered sequence of navigation events that have occurred in the current user session, wherein each of the navigation events is an interactive action by the user with an application interface of the digital banking application;
• converting the pathway dataset into a sequence of latent space representations;
• inputting the sequence of latent space representations to a classifier trained by:
• acquiring a training dataset excluding the financial information, the training dataset comprising a plurality of historical navigation events, wherein at least one of the plurality of historical navigation events is annotated with one of a plurality of intention labels as ground truth;
• converting the training dataset into at least one training sequence of latent space representations;
• and
• training the classifier using the at least one training sequence of latent space representations and the annotated one of the plurality of intention labels;
• and
• in response to the classifier identifying the sequence of latent space representations to be one of the plurality of intention labels, assigning the identified intention label as a predicted user intention;
• and
• suggesting a service corresponding to the predicted user intention via a graphic user interface (GUI) of the digital banking application.