About This Project
A security-first platform designed to detect fraudulent transactions by monitoring device fingerprinting, geolocation, and behavioral patterns.
Key Features
Device Fingerprinting
Geolocation Fraud Analysis
Subscription API Management
User Behavioral Guardrails
Strategic Analysis
The Problem
Electronic payments in the region suffered from high rates of card-not-present (CNP) fraud.
The Solution
Developed an AI detection layer that evaluates transactional risk scores in milliseconds based on 15+ data points.
Technologies Used
Next.jsNext ServerNext ClientJavaScripttailwindCssFramer MotionNode.jsMongoDBAxiosRedux ToolkitTanstack QueryFirebaseJWTImbbSSLCommerzVercel
Project Info
Year
2025
Your Role
Security Architect
Key Metrics
94%
Precision
80ms
Latency
99.9%
Uptime
System Architecture
Frontend
Next.js (Edge Functions Support)
Backend
Next.js API Routes
Database
MongoDB (Time-series data)
Infra
Vercel Edge, SSLCommerz API, JWT Auth
Key Engineering Takeaways
01
Explored the integration of behavioral analytics for fraud prevention.
02
Optimized MongoDB aggregations for real-time risk reporting.
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