Personal Finance Agent: Tracks Expenses, Categorizes Transactions, Suggests Budgets, and Alerts Overspending

Abstract

Managing personal finances efficiently is a persistent challenge for individuals in today’s fast-paced digital economy. Many people struggle to track expenses, allocate budgets, and identify overspending patterns, resulting in financial stress and poor savings habits. This research presents a Personal Finance Agent, a comprehensive web-based platform designed to automate expense tracking, categorize transactions, generate budget suggestions, and issue alerts for overspending.The system leverages machine learningbased categorization rules to automatically classify financial transactions into predefined categories such as Food & Drink, Transport, Shopping, Rent, Utilities, Healthcare, Entertainment, and Salary. This automation eliminates manual classification, saving time and minimizing human error. Users can add transactions manually or synchronize them from digital banking sources in future extensions.Budgeting is another core feature. Each user is assigned default budget limits for each category, which can be customized. The system calculates monthly expenditure per category and presents visual analytics such as pie charts and summary dashboards, allowing users to monitor spending patterns. A real-time alerting mechanism notifies users when they approach or exceed budget limits. Alerts are categorized by severity: info, warning, or danger, helping users make timely financial decisions.The platform is developed using the Django framework, integrating secure user authentication, role-based access control, and a relational database for persistent storage of transactions, budgets, alerts, and user preferences. The system architecture ensures modularity, allowing future extensions such as integrating bank APIs, AI-driven savings recommendations, and predictive financial planning.Evaluation shows that automated categorization achieves high accuracy in grouping diverse transactions, while visual dashboards and alerts improve user awareness and engagement. By combining automation, machine learning, and interactive analytics, the proposed system empowers individuals to maintain financial discipline, prevent overspending, and plan budgets effectively. This research demonstrates that intelligent personal finance management systems can significantly enhance financial literacy and assist users in achieving long-term economic stability.