Authors - Kalyanasundaram V, Keerthi AJ, Krishnaa RK, Thirumurugan A, Joshua Sunder David Reddipogu Abstract - The volatility of the stock market offers a big challenge to traders depending on timely and correct information for informed decision-making. Security risks, including fraudulent practices and theft of identity, threaten online trading platforms. The present paper presents an AI-based stock trading app that tackles these issues by using predictive analytics with robust security features. The system also employs Azure AutoML to work through historical stock data, identify market trends, and generate livestock predictions to enable traders to respond proactively to fluctuations. For security reasons, the app employs Azure Document Intelligence for live Know Your Customer (KYC) verification to ensure that only valid users have access. Additionally, the platform automates document processing using AI-powered text extraction, minimizing errors from manual input and increasing efficiency. Developed with Flutter for smooth cross-platform use and backed by Azure cloud infrastructure for scalability and dependability, this software solution offers an intelligent, secure, and user-friendly trading experience. Through the integration of AI-based forecasting with robust security measures, this work helps develop more efficient, reliable, and technologically sophisticated stock trading platforms.
