KK Financial Management

Title page
Expense Tracking
Visualisation of expenses
Analyse Budget
Output of Analysis
Comparison of budget and spending

Inspiration

In today’s world, financial decisions play a crucial role in our lives. Many people struggle to save money or spend wisely, often finding themselves short by the end of the month. To address this, we created a web app that allows users to track their expenses and calculate optimal spending limits for different categories. Our goal is to empower users to make informed financial decisions and avoid overspending, ensuring they have enough money to meet their needs.

What it does

The web app allows users to track their expenses and calculate optimal spending limits for different categories. The users are able to enter their expenses and it will be collected. There will also be graphs and charts that is produced to help users analyse their spendings. Other than that, the users are able to enter their income and expected saving amount and the model will output the expected amount to spend in categories they have selected. Lastly after analysing, the user can go to the expense tracking page and it will show all categories and their expected and actual spendings. This will allow user to keep track of their spendings of every category.

How we built it

Our development journey began with setting up a Git repository, enabling seamless collaboration among team members. We kicked off the process by sourcing and cleaning datasets to ensure accurate and relevant data for our model. The core of our project is a predictive model that estimates the budget for each spending category. Once the model was in place, we focused on building the frontend, which displays the expense tracking and budget analysis, seamlessly integrating with our database. Throughout the development, we continuously debugged, refined our code, and enhanced the user interface to deliver a polished and user-friendly experience.

Our project leverages a user-driven model that requires server-side implementation. Users input their income, desired savings, and spending categories. The model is trained using this data and predicts spending limits based on the available budget (calculated as income minus savings). For expense tracking, we utilize transaction history to generate visual graphs, providing users with clear insights into their spending patterns.

Challenges we ran into

We have faced several challenges throughout the process. The main challenge we faced was that our model will need user input to train and predict, because of that we needed to create a backend server. The server was also used to save data into a database. Doing this was challenging for us as this is something that we have not done before.

Accomplishments that we're proud of

While there are many expense-tracking apps available, our project stands out by offering a unique feature: the ability to predict spending limits for each category. This predictive capability allows users to stay within their budget based on their income and savings goals. By providing personalized spending recommendations, our app helps users avoid overspending and achieve their financial objectives.

What we learned

Through this project, we have learnt the process of creating a project. From brainstorming ideas for a project, finding data, data cleaning, creating model, predicting output, create website and other functions. We also learnt how to work in a group smoothly.

What's next for KK Financial Management

We aim to post the application to a server and publish the application so that everyone can use our application. Other than that, we aim to create more projects and also join more hackathons.

Highlight of our project

This project introduces an optimistic approach to personal finance management by applying location-specific data into a budget prediction model. By leveraging data of spending habits, we have developed a tool that can provide personalised spending limits based on a user’s location, income and saving goals.

The model is trained on data from various states, taking the variations in cost of living across different states in consideration. By accounting for these factors, the model provides budget recommendations that are relevant to the user. The model presented also generates spending limits instantly which then allows the users to make informed financial decisions on the fly.

On the other hand, we have implemented a clean and intuitive interface that simplifies navigation within our web application. A well visualisation of income and expenses are also integrated to offer clear and valuable insights at a glance.

Instructions to run:

All transaction data and analysis are stored securely in our database, and the app’s functionality is powered by a server-side implementation. To view our web app, follow these steps:

Open a terminal, navigate to the ‘my-backend’ directory, and run ‘node server.js’.
Open a second terminal, navigate to the ‘financial-management-webapp’ directory, and run ‘npm start’. If you haven’t already, run ‘npm install’ first. This setup ensures that both the backend and frontend are running smoothly, allowing you to experience the full functionality of our web app.