Inspiration
We were struck by the reality that impulse is winning and debt is becoming crippling, with over 53 million people now using "Buy Now, Pay Later" (BNPL) services. We wanted to build a tool that intercepts the impulse at the exact moment it strikes—before a bad financial decision is made.
What it does
EarnIt is a fintech platform that replaces "Buy Now, Pay Later" with "Invest Now, Buy Later". Users define a target item, such as a MacBook Pro, and a timeline. The app calculates the required monthly deposit to reach that goal through a risk-adjusted investment portfolio.
How we built it
The platform is built with a Next.js frontend and uses the Plaid API for banking and Alpaca BaaS for brokerage and custody. We developed a mathematical engine based on the Future Value of an Ordinary Annuity to determine fixed monthly payments
Challenges we ran into
The biggest challenge was managing market volatility. To ensure users don't fail their goals due to a market dip, we had to build a Dynamic Auto-Correction Engine that constantly monitors the trajectory and calculates the mathematical shortfall.
Accomplishments that we're proud of
Behavioral Timing: Successfully creating a system that intervenes at the exact moment impulse strikes.
Auto-Correction Logic: Implementing a "Buy the Dip" psychology that turns a market drop into a "sale" notification rather than a reason to panic.
Friction Design: Designing "healthy friction" that slows down spending without removing user autonomy.
What we learned
We learned that the path of least resistance should be investing, not spending. By making users opt out of saving rather than opting in, we can significantly change financial behavior. We also learned the importance of using conservative risk baselines to ensure high probability of goal completion
What's next for EarnIt
We plan to expand our Affiliate Bridge, where the platform can "spot" users the final 5% of their goal through retail partnerships. We are also looking into Retailer Subsidies, offering completion discounts to users who successfully save for specific brands
Built With
- aplaca
- nextjs
- python
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