Secure Budget Tracker

Inspiration

This project was inspired by our friend who was spending too much money and struggling to manage her finances. She often ran out of money before the month ended and didn’t know where it all went. We wanted to create a tool that would help her track spending, plan budgets realistically, and see the long-term impact of her choices.

What it does

Secure Budget Tracker is a Python-based app that helps users:

• Enter and track income and expenses
• Receive realistic budget recommendations based on monthly income
• Detect unusually large or risky spending (anomaly detection)
• Log all financial actions for security and transparency
• Projected a 5-year financial outlook using:

[ \text{Total Savings}_{5y} = \text{Current Balance} + (\text{Monthly Income} - \text{Monthly Expenses}) \times 12 \times 5 ]

Users can also override budgets while the app automatically scales them if total budgets exceed income.

How we built it

We built the app in Codehs using Python we are very new to coding Core features include:

• Input validation to prevent invalid or malicious entries
• Logging of all transactions for audit purposes
• Anomaly detection to flag unusual spending
• Budget recommendation system using monthly income
• 5-year savings projection calculations We structured the app as a menu-driven program for easy navigation and usability.

Challenges we ran into

• Early budget recommendations were based on total balance, which caused unrealistic spending plans. We fixed this by switching to monthly-income-based recommendations and scaling budgets automatically if necessary.
• Balancing security features with usability, so the app remained simple for the user.
• Designing the 5-year outlook so it would be both accurate and easy to understand.
• A LOT of syntax errors.

Accomplishments that we're proud of

• Created a secure budgeting tool that combines financial planning with cybersecurity principles.
• Developed a dynamic recommendation system that adapts to user income.
• Integrated anomaly detection and logging, demonstrating secure programming practices in a practical app.
• Built a 5-year financial outlook hat helps users understand long-term impacts of spending habits.

What we learned

• How cybersecurity practices like input validation, logging, and anomaly detection can apply to everyday apps.
• How to calculate long-term financial projections realistically.
• How to balance user experience with security features.
• The importance of making budgeting tools intuitive for real-world use.

What's next for Secure Budget Tracker

• Add visual charts and graphs for spending trends and savings growth.
• Include goal-setting features so users can track specific savings goals.
• Expand multi-user support, for families or roommates managing shared budgets.
• Add mobile or web version for accessibility on the go.

Built With

• and-calculations-run-in-python.-we-used-standard-python-libraries-like-datetime-and-hashlib-for-logging
• and-date-handling.-the-app-runs-entirely-in-codehs
• input/output
• so-no-local-installation-is-required.-all-data-is-stored-in-memory
• transaction-ids
• we-built-secure-budget-tracker-using-python-3-in-the-codehs-online-python-environment.-all-logic