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AI Based Financial Advisor

Mandar Mali1, Sagar Gundwade2, Arif Shaikh3 Prof. N. S. Hunnargi.

Department of Electronics & Telecommunication Engineering, ATS’s Sanjay Bhokare Group of Institutes, Miraj

Abstract - This paper presents the development of an AI-powered financial advisory system designed to provide personalized investment recommendations. The platform collects user-specific financial data such as salary, expenses, savings, profession, city, risk appetite, and investment horizon. It employs machine learning models, including Random Forest Regressor and Multi Output Regressor, along with a rule-based logic engine to generate asset allocation suggestions across equity, debt, gold, and fixed deposits. The web application is built using FastAPI and features secure authentication, an admin dashboard, a chatbot interface, and real-time stock data integration. The system was tested using both functional and model validation methods to ensure accuracy and user-friendliness. Results indicate that the platform offers reliable and personalized financial recommendations, making it a cost-effective and scalable alternative to traditional advisory services.