Smart Expense Tracker and Budget Predictor

Managing personal finances can be challenging without clear visibility into spending habits. Manual tracking is tedious, and people often overspend without realizing it. Building an intelligent expense tracking and budget prediction app solves this by automating tracking, providing spending insights, and predicting future budget requirements using machine learning, helping users manage money smarter and plan financially for upcoming months.

The system automatically logs daily expenses, categorizes them (food, travel, bills), and analyzes spending patterns using simple ML models. Time-series forecasting models like ARIMA, Prophet, or LSTM can predict future monthly expenses. The app provides users with monthly savings targets, budget recommendations, and alerts when they're likely to overspend based on predictive analysis.

Users input expenses manually or connect accounts for automated expense tracking (optional advanced feature). Categorization algorithms organize expenses, and analytics modules provide summaries like daily spend, category-wise breakdown, and monthly trends. Machine learning models forecast next month's expenses based on past behavior. Smart notifications advise users when they are nearing their limits or suggest adjustments to stay on budget.

• Build a simple mobile or web app for users to log and track expenses daily under different categories.
• Aggregate expense data by category and time (daily, weekly, monthly) to detect spending patterns and seasonal trends.
• Use time-series models like ARIMA, Prophet, or LSTM to predict the user's future expenses and monthly budgets.
• Provide savings goals, budget recommendations, and smart notifications to guide user behavior proactively.
• Optionally deploy to Android/iOS stores as a personal finance management tool for students, freelancers, and families.

• Facebook Prophet Documentation for Forecasting
• Building a Personal Finance Tracker App
• LSTM Time Series Prediction Tutorial