Q Smart Banking Chatbot

Abstract

The purpose of the project is to make any domain-specific website, in our case banking, more usable by integrating a chatbot that serves as an
interface for customer inquiries about services. This reduces customer interaction time with websites, thereby valuing their time and improving
their overall experience. As part of this project, we explored and attempted to create an intelligent chatbot that could extract relevant
information, recognize various intents and execute the pre-mapped actions. To create a contextual assistant for the above purpose, we used the
RASA framework. To train the model, we constructed a custom dataset that includes multiple intents and entities. Additionally, we provide
some python scripts (RASA actions) that will be executed when some intents are detected. Our solution consisted of creating a pipeline having
a chatbot and several actions triggered by the chatbot. These actions will connect with the database and then provide the required data or make
changes according to the user’s query and display the feedback back to the user via the chat widget