FeeSight – Financial Advisory
Feesight - Financial Navigator & Advisory
Feesight is a financial navigation and advisory app built as our Bangkit 2024 Capstone Project. The app helps users manage their finances by forecasting expenses, calculating discretionary income, optimizing spending habits, and offering personalized investment insights in cryptocurrency and stocks. As the project leader, I oversaw the entire development process while also contributing to machine learning, backend coordination, and mobile development integration.
Category
Mobile App, Machine Learning
Client
Bangkit Academy
Start Date
May 2024
End Date
June 2024
Description
Feesight was created to address the growing financial uncertainty experienced by many young adults, especially with the rise of impulsive spending and unpredictable monthly expenses. Traditional financial apps only record transactions, but they rarely help users understand how their finances will look in the near future. Feesight bridges this gap by analyzing income, expenses, and planned commitments to give users a clear picture of their financial stability. It also provides investment suggestions when spare money is available, supported by predictive models to estimate potential crypto and stock movements. The goal was to build an assistant-like experience that helps users make confident and well-informed decisions.
THE STORY
The idea for Feesight came from a simple observation: people often record their finances but still feel uncertain about what they can or cannot spend. Budget plans fail due to unexpected needs, and many users end up stressed about money despite tracking everything manually. As a team, we wanted to build something more intuitive—an app that could behave like a personal financial consultant. Leading the project, I coordinated the workflows between machine learning, cloud computing, and mobile development, ensuring each component aligned with the core experience we envisioned. Our collaborative process allowed us to combine predictive analytics, a reliable backend, and a user-friendly mobile interface into a single, cohesive product designed to guide users toward financial clarity.
OUR APPROACH
Our approach centered on building a seamless system that could track real financial behavior while predicting future conditions accurately. Working across multiple roles, I designed ML workflows for price prediction models, assisted the cloud team in structuring APIs, and supported the mobile team in integrating app logic smoothly. Together, we developed an ecosystem where data, predictions, and user interactions all worked in harmony. We aimed not only to help users understand their current financial status but also to give them the confidence to make decisions that support long-term stability and growth.