AI-Driven Personal Finance and Investment Recommendation System - An Intelligent System for Personalized Financial Planning and Investment

Effective management of personal finances has become increasingly important in the digital age, yet many individuals lack the necessary knowledge and tools to handle their financial activities efficiently. This research introduces an intelligent Digital Finance Assistant powered by Artificial Intelligence, designed to automate expense monitoring, budgeting, and investment planning. The proposed system integrates modern technologies such as Next.js for frontend development, Supabase for secure backend services, Prisma ORM for scalable data handling, and Optical Character Recognition (OCR) for extracting transaction details from receipts. Additionally, machine learning techniques are employed to categorize expenses and generate personalized financial recommendations based on user behavior. The platform offers key functionalities including automated receipt processing, multi-account aggregation, budget alerts, and interactive financial reporting. The development process follows an Agile Software Development Life Cycle to ensure flexibility and continuous improvement. Experimental evaluation demonstrates that the system provides accurate insights, enhances financial awareness, and supports better decision-making. While certain limitations such as OCR accuracy and dependency on connectivity exist, future improvements aim to include mobile support, multi-currency handling, predictive analytics, and enhanced explainability. This study highlights how intelligent systems can improve financial literacy and promote disciplined financial behavior.