Abstract: Managing personal finances effectively has become increasingly complex due to rising expenses, digital transactions, and multiple income sources. Traditional budgeting methods lack automation, predictive analysis, and intelligent insights. This paper presents the design and development of an AI Powered Personal Financial Manager, which integrates machine learning, data analytics, and intelligent recommendation systems to assist users in tracking expenses, predicting future spending patterns, and providing personalized financial advice.

The system analyses transaction data, categorizes expenses, predicts monthly budgets, detects unusual spending behaviour, and generates savings recommendations. By leveraging artificial intelligence algorithms such as Linear Regression, Random Forest, and NLP-based financial advisory modules, the proposed system enhances financial decision-making, improves savings habits, and promotes financial stability.

Keywords: Personal Finance, Expense Tracking, Machine Learning, Budget Prediction, Financial Analytics, AI Recommendation System.

Downloads: | DOI: 10.17148/IARJSET.2026.13335