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UpScore
Inspiration
We wanted to help people truly understand their financial health — not just through credit scores, but through their real daily habits.
What it does?
—Up-Score calculates a personalized Financial Health Score using balances, spending, savings, and rewards data. It then provides simple insights and recommendations to help users improve their money habits.
How we built it?
—We combined transaction, balance, and reward data, engineered behavioral features (spending rate, saving trend, liquidity ratio), and built a weighted scoring model using Python and pandas.
Challenges we ran into
—Normalizing diverse financial data, defining fair weights for each behavior, and ensuring the score was both explainable and actionable for users.
Accomplishments that we're proud of
—Creating a working prototype that translates complex financial behavior into an easy-to-understand score and actionable feedback for both users and fintechs.
What we learned
—We learned how to connect financial insights with user experience — turning raw data into meaningful, human-centered metrics.
What's next for Up-Score?
—Integrate with fintech APIs, train the model with real anonymized datasets, and launch a mobile app that gamifies financial wellness.
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