CHATBOT IN BANKING DOMAIN USING NLP AND MACHINE LEARNING

There are a lot of applications in the banking domain such as YONO SBI, Phonepe bot etc. There are a lot of queries which are being asked by the customers at every stage of transaction classes such as money transfers, loan updates and other issues. Now the problem of this applications is that they are facing several interrupt issues where the responses are very slow and the sites keep on loading, this reduces the number of customers using the applications, so we need an agent which provides a very good customer interaction and is very appealing to the customers. In this project, we propose the development of a Bank Chatbot, which acts as an intelligent agent and provides personalized customer experience using Natural Language Processing (NLP) and Machine Learning (ML) techniques. The model developed in the project works with a very large dataset and a huge load applied on the model to estimate the predictions. The data for this project is collected from open source like Github or Kaggle and perform the implementation. In this project the dataset is first preprocessed using language processing tools, the data is also unstructured in the csv file. The conclusion is based on the efficiency of the model on application of the machine learning algorithms which are classification algorithms such as Naïve Bayes and Support Vector Classifier and the predictions are estimated accordingly using a front-end local host application which is dedicated to work for the customer queries. This is a very good initiate which will help various banks to provide a very good interface where in the customers can solve their queries.