clear

Our slide deck: https://canva.link/kto9uw8d81dsxm1

Framing the Problem
International money transfers are slow, confusing, and opaque. Once money is sent, users lose visibility into where it is, why it's delayed, or what they need to do next. This affects anyone sending money abroad, students paying tuition, workers supporting family, freelancers getting paid, but it hits remittance senders hardest, since they often can't afford the cost or anxiety of an unexplained delay.

Idea Explanation
Clear is a transparency layer that sits on top of existing transfer providers. Before sending, it compares providers and shows the best rate and outcome. While the transfer is moving, it tracks status across providers and explains delays in plain language instead of vague labels like "processing" or "under review." It doesn't replace banks or fintechs, it makes them understandable.

Implementation
The frontend lets users connect accounts and view their transfers in one place. It sends requests to our backend, which pulls status data from provider APIs, normalizes it into a common format, and applies logic to translate raw status codes into plain-language explanations. The database stores user accounts, linked providers, and transfer history, so Clear can compare past transfers and learn which providers perform best for which corridors.

Challenges
The biggest challenge was normalizing data across providers that each return transfer status in different formats with no shared standard. We solved this by building a translation layer that maps each provider's status codes to a common internal schema, so the explanation logic only has to work with one consistent format.

Accomplishments
We learned how fragmented and inconsistent cross-border payment infrastructure actually is, and how much of the "where is my money" anxiety comes from a lack of explanation rather than actual delay. We built a working prototype that takes a real transfer status and turns it into a plain-language update a non-technical user can understand.

Next Steps
Next we'd add real provider integrations beyond our demo data, build out the "best provider" recommendation engine with live rate comparisons, that optimizes the payment, so probably making an optimization engine using ml model and predictors whicc give you a forecast of the conversion rates and then give you a time period of 7 days to send the money, so adding the feature of schedule send and add proactive notifications so users are told about delays before they have to check the app themselves.