AI-Driven Personal Finance Management System Using Machine Learning and Flask

In this paper, an AI-Driven Personal Finance Management System has been proposed and implemented to address the limitations of traditional financial tracking tools. The system integrates Machine Learning techniques with rule-based decision-making to provide an intelligent, automated, and personalized approach to managing personal finances. The developed application successfully enables users to track income and expenses, predict future financial trends, and receive customized investment recommendations based on their financial profile. The use of predictive analytics enhances decision-making by allowing users to anticipate future expenses and plan their budgets more effectively. Additionally, the rule-based recommendation system ensures that investment suggestions are practical, relevant, and aligned with user-specific financial conditions. The results demonstrate that the system performs efficiently in terms of expense prediction, financial data organization, and recommendation generation. By combining automation, prediction, and personalization, the proposed system improves financial awareness and promotes better money management practices. Although the system has certain limitations, such as reliance on manual data entry and lack of real-time integration, it provides a strong foundation for future enhancements. With further development, the system can evolve into a comprehensive financial assistant capable of handling real-world financial scenarios more effectively. In conclusion, the proposed system highlights the potential of artificial intelligence in transforming personal finance management into a smart, data-driven, and user-centric process.

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