GPIRE-Global Payment Intelligence & Risk Engine

An AI-powered system that detects risky, delayed, or suspicious international payments in real-time.

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Inspiration

Cross-border payments are still opaque, slow, and risky. Users often have no visibility into where their money is, why it’s delayed, or whether it’s secure. Inspired by SWIFT GPI and modern fintech systems, we wanted to build a transparent, intelligent payment tracking system powered by AI.

What it does

GPIRE (Global Payment Intelligence & Risk Engine) is a real-time payment simulation platform that:

Generates SWIFT MT103 and ISO 20022 (pacs.008) messages Tracks transactions using a GPI-style timeline Provides AI-powered fraud and risk scoring Generates bank-grade PDF receipts with barcodes Offers an admin dashboard for monitoring transactions

Users can send a simulated international payment and instantly see:

Its lifecycle (CREATED → SETTLED) Risk level and explanation Full SWIFT message structure Downloadable official-style receipt

How we built it

all built on Zerver Frontend: HTML, CSS, JavaScript (fintech UI) Backend: Firebase Realtime Database (event-driven architecture) PDF Engine: jsPDF (multi-page, SWIFT-style formatting) Barcode: JsBarcode (CODE128 for transaction tracking) AI Logic: Rule-based + simulated anomaly detection Architecture: /transactions → core data /events → timeline tracking /risk → AI scoring

We used an event-driven model where every transaction update triggers a UI update in real time.

Challenges we ran into

Replicating real SWIFT MT103 formatting accurately Making the PDF look like a real bank document Handling multi-page layouts with fixed-width fonts Designing a realistic GPI tracking flow Simulating AI risk scoring without external ML APIs

Accomplishments that we're proud of

Built a fully working SWIFT simulation system Achieved real-time tracking using Firebase Generated professional, bank-grade PDF receipts Implemented a complete payment lifecycle engine Designed a system that feels production-ready, not a prototype

What we learned

Financial systems require precision in formatting and standards Event-driven architecture is powerful for real-time fintech apps Even simple AI models can deliver meaningful insights UX matters deeply in financial trust systems

What's next for GPIRE-Global Payment Intelligence & Risk Engine

Integrate real payment APIs (e.g., SWIFT sandbox, Ripple, or Stripe Treasury) Upgrade AI engine with machine learning anomaly detection Add multi-currency FX simulation Build compliance tools (AML/KYC checks) Launch as a developer API for fintech startups

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