Expense Tracker using AL and ML

Managing personal costs can be difficult in today's fast-paced environment. This article introduces an AI and machine learning-based cost tracker that automates expense categorization based on bank transaction data. The technology also allows users to manually enter their spending using a simple web interface. The user can also set limitations for particular categories and create their own categories, such as food, clothing, rent, and bills. The user will see visual data on expenditures by transaction date or category. Anyone who wants to track their costs can use this software; it is not designed for a specific user or age group. Thus, the primary objective of this article is to help customers monitor and analyze their overall spending habits by developing a mobile application that, by just scanning the receipts, analyzes all of the user's transactions. By safely connecting with bank accounts to automate spending classification and offer tailored insights, the AI- and ML-powered expense tracker streamlines financial management. It is based on the MERN stack and has a user-friendly chatbot with natural language processing for tracking, goal-setting, and budgeting. By examining expenditure trends, forecasting future costs, and providing practical guidance, machine learning improves functionality. This tool enables users to effectively manage their funds and attain financial stability with cross-device accessibility, real-time visualizations, and comprehensive reports.