Intelligent AI Finance Advisory System: A Secure and Ethical AI System for Live Financial Advisory Insights

The rapid expansion of digital financial platforms has created an urgent need for intelligent systems that deliver personalised, transparent, and responsible financial guidance. Existing financial advisory chatbots and platforms suffer from critical limitations: they produce generic, context-free responses; fail to integrate real-time financial data; offer no transparency in their reasoning; and provide no safeguards against speculative or unethical queries. In this paper, we propose an Intelligent Ethical and Explainable AI-Based Financial Advisory System that combines Retrieval-Augmented Generation (RAG), dynamic financial risk profiling, an ethical and compliance filtering layer, and an Explainable AI (XAI) module to deliver accountable, personalised, and grounded financial decision support. Unlike profit-prediction engines, our system is designed explicitly as a decision-support tool, preserving user autonomy while reducing misinformation risk. Experimental evaluation on a curated financial query dataset demonstrates an 87.3% factual accuracy rate (versus 61.4% for a vanilla LLM baseline), a hallucination reduction from 34.2% to 9.1%, an ethical filter precision of 93.6%, and a mean user satisfaction score of 4.5/5. These results confirm that RAG-grounded, ethically constrained, and explainable architectures represent a significant advancement over generic conversational agents in the regulated financial domain.