V3I6P25

A Conversational Investment Risk Assessment and Return Analytics Chatbot Using Data-Driven Models

Mr. Aditya Ghadigaonkar¹, Ms. Sandhya Kaprawan²

Abstract

The increasing participation of retail investors in financial markets has created a growing demand for intelligent systems capable of providing personalized investment guidance and risk assessment. Traditional investment advisory services often require extensive financial expertise which makes them inaccessible to many individuals. Recent advancements in Artificial Intelligence (AI), Natural Language Processing (NLP) and data-driven analytics have enabled the development of conversational chatbots capable of delivering financial insights through intuitive human-computer interactions. However, existing financial chatbots primarily focus on customer support and portfolio tracking with limited capabilities in comprehensive risk evaluation and return forecasting.

This research proposes a Conversational Investment Risk Assessment and Return Analytics Chatbot that utilizes data-driven machine learning models to analyze investment portfolios, assess risk levels, predict potential returns and provide personalized recommendations through a natural language interface. The system integrates financial indicators, historical market data, portfolio diversification metrics and predictive analytics techniques to generate a real-time investment insights. Furthermore, Explainable AI (XAI) mechanisms are incorporated to improve transparency and user trust in automated investment decisions.

The study reviews existing literature on financial chatbots, investment analytics, machine learning-based risk assessment and conversational AI systems. It identifies the critical research gaps related to personalization, explainability and real-time market adaptability. The proposed framework aims to bridge these gaps by combining the conversational intelligence with advanced risk analytics and enabling users to make informed investment decisions while improving accessibility to financial advisory services. The research contributes toward the development of intelligent, transparent, and user-centric financial decision-support systems.