Payment Processing System
Real-time payment processing platform with fraud detection and AR integration
Project Overview
A comprehensive payment processing system that handles real-time transactions with advanced fraud detection, automated reconciliation, and seamless integration with accounts receivable systems. Features live transaction monitoring and intelligent risk assessment.
The Problem
Scalable Payment Processing with Intelligent Fraud Prevention
A growing FinTech startup needed a robust payment processing platform that could handle increasing transaction volumes while maintaining security, compliance, and seamless integration with their existing accounts receivable systems.
Key Pain Points
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Legacy payment system couldn't scale beyond 1,000 transactions per hour
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Manual fraud review process causing payment delays and customer friction
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Disconnected AR systems leading to reconciliation discrepancies
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Lack of real-time visibility into payment flows and fraud attempts
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Compliance reporting taking days to generate manually
Target Users
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Payment operations teams
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Fraud analysts and risk managers
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Accounting and finance teams
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Customer service representatives
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Compliance and audit teams
Business Impact
Payment processing limitations were constraining business growth and increasing operational costs due to manual fraud review and reconciliation processes.
The Solution
Approach
Built a high-performance payment processing platform using FastAPI with machine learning-powered fraud detection, real-time AR integration, and comprehensive monitoring. Implemented WebSocket connections for live updates and automated reconciliation workflows.
Key Technical Decisions
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Used FastAPI for high-throughput async payment processing
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Implemented machine learning models for real-time fraud detection
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Built atomic transaction handling with PostgreSQL and Redis
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Created WebSocket-based real-time monitoring system
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Designed automated reconciliation with AR ledger integration
Implementation Highlights
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Sub-second payment processing with fraud scoring
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Automated AR posting and reconciliation workflows
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Real-time dashboard with live transaction monitoring
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Machine learning models achieving 99.2% fraud detection accuracy
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Comprehensive audit trails meeting regulatory requirements
Architecture Overview
Event-driven microservices architecture with FastAPI payment endpoints, PostgreSQL for transaction storage, Redis for caching and rate limiting, ML models for fraud detection, and WebSocket connections for real-time monitoring.
Results & Impact
Successfully delivered a scalable payment processing platform that increased transaction capacity by 2000% while reducing fraud losses by 85% and automating 95% of reconciliation processes.
Performance
2000% increase in transaction processing capacity
Scalability
Linear scaling supporting 20,000+ transactions per hour
Uptime
99.95% uptime with automated failover and monitoring
Response Time
Average payment processing time under 500ms
User Satisfaction
4.8/5 rating from operations and finance teams
Key Achievements
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Scaled from 1,000 to 20,000+ transactions per hour capacity
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Reduced fraud losses by 85% through ML-powered detection
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Achieved 99.7% payment success rate with sub-second processing
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Automated 95% of manual reconciliation processes
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Implemented comprehensive compliance reporting reducing audit time by 70%
User Feedback
""Payment processing is now lightning fast and fraud detection catches issues we never saw before" - Risk Manager"
""Automated reconciliation has saved us 20+ hours per week" - Finance Director"
""The real-time monitoring gives us unprecedented visibility into our payment flows" - Operations Manager"
Lessons Learned
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Importance of real-time monitoring for payment operations
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Value of machine learning for fraud detection accuracy
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Benefits of automated reconciliation for operational efficiency
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Critical need for comprehensive audit trails in financial systems
Key Features
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Real-time payment processing with sub-second response times
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Advanced fraud detection using machine learning
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Automated AR ledger integration and reconciliation
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Live transaction monitoring dashboard
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Multi-currency support with real-time exchange rates
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Comprehensive audit trails and compliance reporting
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WebSocket-based real-time notifications
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Intelligent risk scoring and transaction analysis
Technical Challenges
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Implementing real-time fraud detection with minimal false positives
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Creating seamless AR integration without data inconsistencies
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Handling high-volume concurrent transactions safely
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Building comprehensive compliance and audit capabilities
Project Details
Status
CompletedDuration
8 weeks
Role
Backend Developer & ML Engineer
Team Size
Solo developer
Client Type
FinTech startup
Technologies Used
Project Timeline
Analysis & Architecture
1 week
- • Payment flow analysis and fraud pattern research
- • AR integration requirements and data mapping
- • Technology selection and architecture design
- • Compliance and security requirements assessment
Core Development
5 weeks
- • Payment processing engine development
- • Machine learning fraud detection models
- • AR integration and reconciliation workflows
- • Real-time monitoring dashboard implementation
Testing & Deployment
2 weeks
- • Load testing with simulated transaction volumes
- • Fraud detection model validation and tuning
- • Integration testing with existing AR systems
- • Production deployment and monitoring setup