International Journal of Scientific Research and Engineering Development

The Conversational Financial Analytics is mainly building a Conversational system that allows users to interact with financial market data by using natural language pro- cessing, instead of navigating different platforms, dashboards, or financial data. To overcome this problem users can simply ask questions and retrieve the answers by using NLP. This project involves a Conversational AI system to give financial data interaction with users by using stock trends, market sentiment and financial reports through natural language pipelines. The proposed solution is deploying a chatbot for maintaining the real time financial data. The OpenDialog framework is a core component for conversational AI to retrieve real time market data and financial data and also it is used in advanced natural language processing pipelines and it is implemented in Python. The OpenDialog is mainly used for multiple dialogues where the users can ask multiple questions without repeating. The REST APIs are responsible for effective communication between user and chatbot without interruption. NLP pipelines manage the user language and converts understandable ways and gives the relevant information using intent recognition, entity extraction and response generation. Chatbot reduces the time of the user by giving real time information and as well as predictions for better decisions in financial situations.

Ms.P.Anuradha, S.Hemanth, M.Divya Kiran Kumar, R. Tejesh, P.Bharath,"Conversational Financial Analytics and Market Trend Interpretation Using OpenDialog Framework and NLP Pipelines" International Journal of Scientific Research and Engineering Development, V9(2): Page(475-478) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.