Smart Expense Manager: Intelligent Personal Finance Management with Machine Learning

Smart Expense Manager: Intelligent Personal Finance Management with Machine Learning

Aayush Patil, Ankit Lukadey, Hrishabh Kulkarni, Abhishek Samanta, Prof. Reetika Kerketta

Dept. Information technology
School of Computing - MIT ADT UNIVERSITY
Pune, India

ABSTRACT

This paper proposes a smart expense manager that incorporates machine learning (ML) techniques to analyze and track user money spending behavior. The system is designed to help users track their spending and identify areas where they can reduce expenses or increase savings. The system leverages ML algorithms to analyze user spending patterns and provide personalized recommendations based on their spending history. The proposed system also includes features such as budget tracking, expense categorization and transaction monitoring through the use of ML algorithms (Random Forest, Linear regression, boosting, neural networks), charts and graphical representation. The results of preliminary testing indicate that the proposed system is effective in helping users manage their expenses, with users reporting improved financial control and better financial outcomes. Overall, the proposed smart expense manager has the potential to improve financial literacy and promote more responsible financial behavior among users.

Keywords

Transactions; Machine learning; Random Forest; Linear regression; boosting; neural networks; financial behavior; expense manager.