Chatbot - Shera is developed to answer the queries of the customers about the bank and its products which includes the services like opening of the bank account, loans and other digital products. The chatbot is trained using the customised dataset and then fed into a deep learning model integrated using the pytorch framework. Natural Language processing(NLP) is used for stemming, tokenisation and lemmatization of the given dataset(sentences) in the .json file. Chatbot - Shera is then trained with the customised dataset and it responses to almost every questions accurately asked by the customers of the bank regarding the services.
As customers nowadays are have hectic schedules, they don't find time to wait on calls to get in touch with a customer care representative. The most important thing is to ensure the immediate response when it comes to the case of the customer service. Shera offers an immediate response facility to provide instant solutions and resolves their queries. Shera is integrated with leveraging technologies like NLP that posses semantic analytics features and offer more human like conversations.
We can usually motice that customers are more comfortable with the chatbots as they are more robust and efficient when responding to queries than human agents. The Chatbot - Shera is able to answer the customer's basic questions regarding the different types of accounts or the other banking products available in ABC bank.
