BudgetWrite - Interactive Personal Finance Tool

Team Name

Team 2753

Team Members

Project Description

Project Title: BudgetWrite - Interactive Personal Finance Tool

Overview: BudgetWrite is a dynamic web-based personal finance application designed to help users build, track, and optimize their budgets through an interactive and personalized approach. The platform integrates real-time user input with automated financial analysis to provide tailored budgeting advice, progress tracking, and spending insights. Users can enter their demographic details, income, and spending categories, and receive a breakdown of their budget in key areas like housing, transportation, groceries, and savings.

Key Features:

User-Focused Budget Creation: Users fill out a form with their age, income, housing, transportation, and groceries information. The app calculates budget allocations and provides insights into each area.
Real-Time Feedback: BudgetWrite generates a detailed budget summary with progress bars for different spending categories, such as housing, transportation, and groceries, based on the user's input.
AI-Generated Financial Guidance: The app leverages OpenAI's Generative Language Model to provide personalized, coaching-style feedback based on the user's spending habits.
Transaction Analysis: Users can upload their daily transactions and receive detailed feedback on how their spending aligns with their budget, including tailored financial advice.
Seamless Integration: BudgetWrite uses Actix Web for server-side logic, Reqwest for API calls, and Pulldown-CMark for markdown conversion. Bootstrap provides a responsive, user-friendly interface.
Technical Stack:

Backend: Rust (Actix Web framework)
Frontend: HTML, CSS (Bootstrap)
APIs: OpenAI API for generating financial coaching and analysis
Data Management: Mutex-protected data storage for budgets and transactions
Third-party Libraries: actixfiles, serdejson, reqwest, pulldown_cmark, and more.
Target Audience: The platform is designed for individuals looking to gain control of their personal finances. It offers particular value to those who need easy-to-understand financial coaching and tailored advice to stay on track with their budgets.

Future Improvements: The project has the potential to integrate features like account linking for real-time transaction analysis, expanded coaching services, and data visualization tools to further enhance financial literacy and decision-making.

Data Story

Personal finance management is an essential skill for individuals, yet many struggle to track and optimize their spending effectively. The availability of national household data offers an opportunity to design more accurate and personalized budgeting tools that reflect the reality of diverse income brackets, family structures, and spending habits. By leveraging this data, we can help individuals create budgets that are not only realistic but also customized to their specific needs.

The Power of National Household Data: National household data is a goldmine of information that captures critical details about how households across different income levels, age groups, and family sizes manage their finances. This data typically includes:

Income Distribution: Ranges from low-income to high-income households, capturing the financial spectrum.
Expenditure Patterns: Detailed spending across categories such as housing, transportation, groceries, healthcare, education, and entertainment.
Demographic Insights: Age, family structure, housing situation, and regional factors that affect cost of living and financial priorities.
By analyzing these patterns, we can derive insights that allow us to tailor budget models that fit different segments of the population. For example, a household with two working adults and children will have different spending priorities than a single individual renting a small apartment.

Building the Budgeting Model: Using national household data as a foundation, BudgetWrite creates tailored budgeting recommendations. Here's how it works:

Income Matching: Users input their income range (e.g., “Below $20,000” or “$60,000–$80,000”). Using national household income data, we can assign reasonable expectations for spending across various categories. Households in lower income brackets typically spend a higher percentage of their income on essentials like housing and food, while higher income households may have more flexibility in discretionary spending.

Spending Categories: National data helps define spending percentages across major categories:

Housing: National statistics show that housing tends to take up 25–40% of household income depending on factors like homeownership, mortgage, and rental costs.
Transportation: Regional factors play a big role here, with urban households spending more on public transportation and suburban households allocating more for car-related expenses.
Groceries and Essentials: National household data helps predict grocery spending based on household size and income, adjusting for single individuals, couples, and families.
Demographic Tailoring: The platform adjusts recommendations based on user demographics. For instance, younger households might have lower healthcare and insurance costs but higher spending on education and entertainment. Retirees, on the other hand, may need to allocate more for medical expenses and savings.

Utility Bills and Savings: National data on utilities and savings rates further refines the model. For example, energy consumption varies greatly by region and housing type, and we adjust the budget to reflect local utility costs. Additionally, saving rates for different income groups are integrated into the tool, ensuring that users are encouraged to save according to best practices from the data.

Visualizing Financial Health: With the model based on national household data, BudgetWrite generates a visual representation of the user’s budget. For each spending category—housing, transportation, groceries, utilities, and savings—the platform provides a progress bar that reflects how their spending compares to the national averages for similar households. If a user’s housing costs exceed the norm for their income range, BudgetWrite will highlight this and suggest adjustments.

Personalized Financial Coaching: BudgetWrite doesn't just stop at data-driven recommendations. After collecting users' spending data, the platform uses OpenAI's AI models to offer personalized advice. By comparing users' daily transactions to national spending patterns, BudgetWrite generates specific feedback aimed at optimizing their budget. For example, if a user is consistently overspending on dining out, the AI provides tips to reduce these expenses without sacrificing too much enjoyment.

Impact on Financial Literacy: By integrating national household data into a budgeting tool, BudgetWrite enhances financial literacy and empowers individuals to take control of their finances. The use of real-world data ensures that budgets are grounded in reality, reflecting how households across the country manage their money. This personalized approach helps users set realistic financial goals, from building emergency funds to saving for a home or retirement.

Conclusion: BudgetWrite’s approach to building personalized budgets using national household data is a game-changer for personal finance management. By using real, granular data on household income, spending, and demographics, the tool ensures that budgets are not only tailored but also practical for a wide range of users. In doing so, it helps individuals understand their financial landscape, make better spending decisions, and ultimately achieve greater financial security.