SMARTER BANKING CHATFIN

Abstract

By including a chatbot, which acts as an interface for customers to inquire about services, our initiative aims to improve the usability of banking websites. Customers' time is valuable, and this method maximizes their experience by minimizing the amount of time they spend engaging with websites. We focused on developing an intelligent chatbot capable of extracting relevant information, recognizing various intents, and executing predefined actions. We created a contextual assistant using the RASA framework to accomplish this. We used a bespoke dataset with a wide range of intents and entities to train the model. Python scripts (RASA actions) that we wrote are also performed when certain intents are detected. Building a pipeline that incorporates a chatbot and many activities prompted by it is our answer. The user's query determines which actions connect to the database; these actions then display the result to the user via the chat widget after retrieving the relevant information or making any necessary adjustments.