ShellHacks Project - Capital 01 Health

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Inspiration

Our goal is to empower individuals with bank accounts to make better financial decisions, especially those aged 25-60 with recurring expenses.

What it does

Our system leverages a Generative Adversarial Network (GAN) to analyze users' bank transactions. The model compares income with inflation rates and predicts future deposits, withdrawals, and account balances. We trained the GAN using simulated bank transaction data (in CSV format) to provide personalized financial guidance, helping users improve their financial health.

Challenges we ran into

We encountered difficulties in sourcing high-quality, reliable data for training the AI model. Many datasets we tried initially resulted in poor performance. After evaluating several sources, we eventually found more suitable datasets and improved the model's accuracy.

Accomplishments that we're proud of

We are proud of working as a team to accomplish creating a successful GAN furthermore, we triumphed over many problems and worked on them together to find the most efficient and time saving solution we could.

What we learned

For several team members, working with GANs was a new experience, making this project a steep learning curve. We gained valuable skills in data parsing, cleaning, and pre/post-processing, which significantly enhanced the model's performance.