IntelliFinance: A Rule-Based and AI-Driven Smart Financial Decision Support System for Personalized Financial Planning—Effective personal financial management remains difficult for individuals who lack access to professional, personalized financial advice suited to their income, expenses, and goals. Most existing solutions address only a fragment of this problem: budgeting and expense-tracking applications record transactions but leave analysis and decision-making to the user; robo-advisory platforms focus narrowly on investment allocation; and conversational finance chatbots often generate numerical guidance directly from a language model, which can be inconsistent or unverifiable. This paper presents IntelliFinance, a web-based Smart Financial Decision Support System (SFDSS) that unifies these fragmented capabilities into a single, explainable platform. The system separates deterministic financial computation from natural-language explanation: a rule-based calculation engine computes budget allocations, emergency-fund targets, SIP/investment contributions, EMI and debt-repayment strategies, and an overall Financial Health Score, while a large-language-model-based AI Advisor interprets these results for the user in plain language and answers user-specific financial queries. The platform further introduces a Family Financial Mode for household-level planning and visibility. Drawing on evidence from a randomized controlled trial of low-income personal finance apps, a review of AI-based robo-advisory systems, and a machine-learning-based expense analytics platform, this paper positions IntelliFinance within the existing literature, identifies the specific gaps it addresses, and describes its proposed architecture, data flow, research hypotheses, and technology stack. The system is intended to function as an accessible, transparent, and trustworthy decision-support and financial-education tool, particularly for students, young professionals, and first-time earners.

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