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What it does

Our homebuyer tool guides clients step by step to determine if they would be eligible for a home loan. If they are not eligible, it provides suggestions on what factors they should improve. The tool also accepts CSV files of homeowner information and provides graphs highlighting the key factors that lead to ineligibility, as well as an output file with eligibility data.

How we built it

We created the app layout on Flask and built HTML/CSS templates using Tailwind. The input data is processed using Pandas, and several calculations are done to determine whether it meets the recommended criteria. The graphs are generated using Pandas and Matplotlib.

Challenges we ran into

Our team had to adapt quickly to the technical expertise the project requires. For example, connecting the graphs to Flask.

Accomplishments that we're proud of

We were able to complete sub-goals in a consistent and timely manner, and we kept clear communication

What we learned

.We discovered the capabilities of Tailwind and Pandas, as well as the factors that go into ensuring that potential homeowners are capable of taking on a mortgage.