Cardfinderpro

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  Main Screen of Cardfinderpro

Inspiration

In our freshman year, we made it a goal to find the best credit card for us Every time we started, we got overwhelmed by the amount of information out there: fees, reward rates, signup bonuses, and fine print spread across dozens of websites. Over three years, we would picked this project up at least three times, and each time we got lost in the information and ran out of time to sort through it, so we stopped.

We realized the problem wasn't a lack of effort. There was too much information and no easy way to sort through it. I'm not the only one: my peers feel the same way, and recently a co-worker told me she was struggling to find the right credit card too.

So we built Cardfinderpro for anyone opening their first credit card, from students to working adults, and for anyone who wants to pick a card without being overwhelmed. You can enter how you actually spend money, and it shows which cards are worth the most for you.

What it does

Cardfinderpro lets users filter and rank US credit cards based on how they actually spend.

• Personalized value calculator: enter your monthly spending by category (dining, groceries, gas, travel, everything else) and every card is ranked by estimated net yearly value, meaning rewards earned minus the annual fee, with statement credits and signup bonuses taken into account.
• Smart filters: credit score tier, reward type, max annual fee, bank, payment network, no foreign transaction fee, lounge access, and 0% intro APR.
• Best two-card combo: finds the pair of cards that earns the most for your spending.
• Compare view: put up to four cards side by side.
• My Wallet: track the cards you already own and see which card to use for each type of purchase.
• Bank Intel: a guide to each issuer's approval rules and transfer partners.
• Export and share: download a CSV or share your spending setup with a link.
• Gemini Powered Chatbot: for more in-depth discussion
• AI Assistant: Allows the user to upload their own bank statement once will calculate their budget for them

How we built it

We built Cardfinderpro with plain HTML, CSS, and JavaScript, with no framework or backend, so it runs entirely in the browser. The card data lives in a structured JavaScript dataset, and one reactive calculation engine recomputes the rankings every time a filter or spending slider changes. We tracked and verified our data in a spreadsheet, and we collaborated through GitHub and VS Code. We used AI tools to speed up coding and to help us debug.

Challenges we ran into

Our biggest challenge was data. There is no public API for credit card rewards, fees, or bank approval rules, so we collected the data ourselves and checked card details against the issuers’ official pages. Because these details change often, we built a data-freshness system: a feed that should update rates and fees without touching the code, a status bar that shows users exactly how old the data is, and warnings when it gets stale. We also struggled with the math behind our recommendations. Early on, our reward and fee calculations gave wrong rankings, and small bugs in individual functions were hard to spot. To keep the numbers trustworthy, we made the app do all the calculations itself and use Gemini only for sorting transactions and explaining results.

We also had a huge learning curve because we were using new tools like Gemini API and creating and connect our GitHub to a domain name.

Finally, designing the interface in plain HTML, CSS, and JavaScript took more effort than we expected, especially keeping the layout correct as we added new features.

Accomplishments that we're proud of

We’re proud that this was our first HackTX, and that we pushed ourselves well beyond our comfort zone to finish a working product and present it here. Most of all, we’re proud that we kept going through bugs, wrong calculations, and late-night fixes, and learned a lot as a team along the way.

What we learned

We learned how a hackathon works, how to collaborate as a team, how to build a product within a limited time, and how to manage that time under pressure. Along the way, we also learned how to work with the Gemini API, why data accuracy matters so much for a finance tool, and how to design an app so that AI explains the results while our own code does the math.

What's next for Cardfinderpro

We believe that this information would be very beneficial for a lot of people which is why we brainstormed a lot of future updates that Cardfinderpro should have.

• A system or program that would verify, update, and add card info. (Could be separate systems)
• Potentially add a local or country filters as some credit cards are regionally based
• Add another topic to focus on such as saving accounts
• Automatic data checks since credit card benefits and terms change often
• Find a way to standardize what information is gathered
• Smarter rewards math
• Would like for the AI Chatbot to be a tool for users to dive deeper into the card that they are interested in. For example, a user uses the website filters and comparison tools to find the card that they want. Then they can ask AI chatbot for the more in-depth benefit analysis and etc.
• Enhance cybersecurity for our website because it contains customers' information especially if they use the upload your bank statement option and API keys

Built With

• css
• html
• javascript
• python