AI-BASED PERSONAL FINANCE MANAGER
DOI:
https://doi.org/10.5281/zenodo.19510161Keywords:
Artificial Intelligence, Personal Finance, Machine Learning, Expense Tracking, Budgeting, Financial Analytics, Predictive Modeling, Fraud Detection, FinTech, Smart FinanceAbstract
The rapid advancement of digital technologies and the increasing complexity of financial ecosystems have made personal finance management a challenging task for individuals. Traditional methods of managing finances, such as manual budgeting and basic tracking tools, often fail to provide real-time insights and intelligent decision support. This project, “AI-Based Personal Finance Manager,” proposes an intelligent and automated solution that leverages Artificial Intelligence (AI) and Machine Learning (ML) to enhance financial planning, monitoring, and decision-making. The proposed system collects and analyzes user financial data, including income, expenses, savings, and transaction history, through secure integration with banking systems or manual input. Advanced machine learning algorithms are applied to categorize expenses, detect spending patterns, and generate personalized financial insights. The system provides features such as automated budgeting, expense tracking, anomaly detection for unusual transactions, and predictive analytics for future financial planning. Additionally, the application offers intelligent recommendations for saving, investment opportunities, and debt management based on user behavior and financial goals. Natural Language Processing (NLP) can also be incorporated to enable chatbot-based financial assistance, making the system more interactive and user-friendly. The AI-Based Personal Finance Manager improves financial awareness and promotes better money management by providing real-time insights and data-driven recommendations. It helps users reduce unnecessary expenses, optimize savings, and achieve financial stability. The system also enhances security by detecting fraudulent activities and alerting users instantly. By combining automation, analytics, and user-centric design, the proposed solution offers a scalable and efficient approach to personal finance management. This research contributes to the development of intelligent financial technologies, supporting individuals in making informed financial decisions and improving their overall financial well-being.







