AI Based Personal Finance Management

Abstract

managing personal finances has become increasingly challenging for individuals. Traditional methods such as spreadsheets and manual record-keeping often lack real-time insights and predictive capabilities. This paper presents an AI-powered personal finance assistant that automates financial tracking and analysis using advanced technologies. The proposed system leverages Natural Language Processing (NLP) and time-series forecasting to categorize financial transactions and predict future expenses. Developed using Python, Django, and SQLite, the application integrates NLP techniques through the Natural Language Toolkit (NLTK) and utilizes the ARIMA model for forecasting. It enables users to monitor income and expenses, gain intelligent insights, and plan budgets more effectively. Experimental results on real-world financial datasets show high accuracy in transaction categorization and reliable forecasting performance, with low Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). These findings demonstrate that AI-driven solutions can significantly improve personal finance management by enhancing financial awareness, supporting better planning, and encouraging responsible spending habits. Additionally, the system’s modular design ensures scalability and flexibility, making it a strong foundation for future enhancements in intelligent financial applications