🧠Inspiration
Over half of Mexico’s workforce operates informally, without access to formal credit or financial tools. We were inspired by this challenge and the clear connection between informality, lack of trust in financial institutions, and low financial literacy.
We wanted to create a solution that not only scores creditworthiness differently but also rebuilds trust through transparency and education.
đź’ˇ What it does
TrustCredit uses AI and blockchain to make financial inclusion measurable and profitable.
It generates an AI-powered TrustScore from consenting users’ digital footprints and SME sales data, providing a transparent alternative to traditional credit scoring.
The TrustScore is securely stored on blockchain, ensuring transparency and preventing tampering.
SMEs receive blockchain-based reputation certificates that prove credibility and unlock access to financing.
Users complete short financial-literacy lessons and earn points redeemable at participating SMEs—creating a circular economy that rewards learning and drives real local commerce.
🏗️ How we built it
We built TrustCredit using:
React + TypeScript + Vite for a fast and responsive web interface.
Tailwind CSS and shadcn/ui for accessible, clean UI components.
Node.js + Express for backend APIs handling user data and scoring logic.
Capital One’s Nessie API to simulate accounts and transactions for testing credit scenarios.
Blockchain (testnet) integration to store TrustScores and issue verifiable reputation certificates.
Deployed on Vercel for frontend hosting and GitHub for version control.
⚙️ Challenges we ran into
Balancing data privacy and transparency while storing scores on blockchain.
Designing an explainable AI model that lenders could trust and understand.
Integrating multiple data sources smoothly during the hackathon timeframe.
Creating a UI that feels friendly and educational for users with low digital literacy.
🏆 Accomplishments that we're proud of
Built a working prototype demonstrating the complete ecosystem: onboarding, literacy gamification, scoring, and blockchain verification.
Successfully implemented a blockchain layer for score and certificate storage.
Designed a data pipeline and scoring logic that can evolve into a production-ready model for fintech pilots.
Created a reward system that connects users and SMEs in a positive financial cycle.
đź“š What we learned
We learned that trust and inclusion can’t be forced—they have to be earned. By combining education, transparency, and real incentives, we can bridge the gap between informal and formal economies. We also learned how blockchain can be used not just for hype, but to prove data integrity in financial systems.
🚀 What's next for TrustCredit
Expand the AI model to include more alternative data signals (transaction patterns, device metadata).
Partner with banks or fintechs to pilot TrustCredit with real SME data.
Launch a mobile-first version to reach informal workers and small business owners directly.
Integrate with government and NGO programs focused on financial literacy and inclusion.
Even formalizing 1 % of Mexico’s informal SMEs could unlock US $3–4 billion in traceable economic value—proving that inclusion is not just a social mission, but a sustainable business opportunity.
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