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Payment Authentication Platform

Led implementation of credit card payment authentication that saved $16M in chargeback liabilities.

January 15, 2024
TypeScriptNest.jsReactMySQLNode.js

Overview

I led the implementation of a comprehensive credit card payment authentication system at Zego that significantly reduced fraudulent transactions and chargebacks. This project saved the company $16 million in chargeback liabilities and strengthened our risk management capabilities.

The Problem

Payment fraud and chargebacks were a significant cost center for the business:

  • Chargebacks were costing millions annually
  • Fraudulent transactions were slipping through basic validation
  • Property managers were losing trust due to payment disputes
  • The existing system lacked modern authentication standards

Solution Architecture

We implemented a multi-layered authentication system that includes:

3D Secure Integration

Integrated 3D Secure 2.0 for card-present and card-not-present transactions, shifting liability to card issuers for authenticated transactions.

Risk Scoring Engine

Built a real-time risk scoring system that evaluates transactions based on:

  • Device fingerprinting
  • Behavioral analytics
  • Historical transaction patterns
  • Velocity checks

Fraud Detection Rules

Implemented configurable rules engine allowing the risk team to quickly respond to emerging fraud patterns.

Implementation Challenges

Balancing Security and UX

Too much friction would hurt conversion rates. We implemented adaptive authentication that only challenges high-risk transactions.

Legacy System Integration

The authentication system needed to work with existing payment flows without disrupting current operations.

Real-time Performance

Risk scoring needed to complete in under 100ms to avoid impacting the checkout experience.

Results

  • $16M saved in chargeback liabilities
  • 60% reduction in fraudulent transactions
  • Improved client retention through better risk management
  • Increased sales as property managers gained confidence in the platform

Technical Stack

  • Backend: Nest.js with TypeScript for type-safe service development
  • Database: MySQL for transactional data with read replicas
  • Frontend: React components for authentication UI flows
  • Monitoring: Real-time dashboards for fraud metrics

Key Takeaways

  1. Fraud prevention is an ongoing battle: Patterns evolve constantly, requiring continuous monitoring and adaptation
  2. Data is your best defense: Historical patterns and behavioral analytics are more effective than static rules
  3. UX matters for security: The most secure system is useless if users abandon it due to friction