“Intelligent Web-Based Personal Finance Management System Using AI and Predictive Analytics”

The rapid growth of digital financial transactions and multiple income streams has made personal finance management increasingly complex. Traditional financial management systems provide limited functionality, focusing mainly on manual expense tracking and basic budgeting, without offering intelligent insights or predictive capabilities. This paper proposes an intelligent web-based personal finance management system that leverages Artificial Intelligence (AI) and predictive analytics to enhance financial decision-making. The proposed system utilizes machine learning algorithms to automatically categorize transactions, analyze user spending behavior, and forecast future financial trends. By incorporating predictive analytics, the system enables users to anticipate expenses, optimize budgets, and improve savings strategies. Additionally, a recommendation engine provides personalized suggestions based on individual financial habits, while anomaly detection identifies unusual transactions and potential financial risks. The system is implemented as a web-based platform, ensuring accessibility, scalability, and ease of use across multiple devices. An interactive dashboard is designed to visualize financial data through charts and graphs, providing users with real-time insights. Advanced security measures, including encryption and authentication protocols, are integrated to protect sensitive financial information. Experimental analysis indicates that the proposed system significantly improves financial awareness, promotes disciplined spending, and enhances decision-making efficiency. This research demonstrates the potential of AI and predictive analytics in transforming traditional finance management systems into intelligent, adaptive, and user-centric platforms.