FinTech Engineering Interview Framework

Core System Design Patterns

Payment Processing Architecture

Critical Components

• ✅ Token Vault (never store raw payment data)
• ✅ Idempotency mechanism (prevent duplicate charges)
• ✅ Reconciliation system (match processor reports)
• ✅ Error handling + retry logic

Common Questions

• "How would you design a system that processes 10,000 transactions per second?"
• "How do you handle payment processor downtime?"
• "How would you implement a multi-currency payment system?"

Transaction Processing Pattern

Critical Guarantees

• ✅ Atomicity (all or nothing)
• ✅ Consistency (valid state transitions)
• ✅ Isolation (concurrent transactions)
• ✅ Durability (survive failures)

Common Questions

• "How would you implement money transfers between accounts?"
• "How do you ensure consistency across distributed databases?"
• "Design a system that handles peak trading volumes"

Fraud Detection Pipeline

Key Components

• ✅ Real-time feature computation (<100ms)
• ✅ Multi-model ensemble approach
• ✅ Human review workflow for edge cases
• ✅ Feedback loop for model improvement

Common Questions

• "Design a fraud detection system for credit card transactions"
• "How would you balance false positives and false negatives?"
• "How would you handle model explainability for compliance?"

API Gateway & Versioning

Key Versioning Strategies

• ✅ URL path (/api/v1/resource, /api/v2/resource)
• ✅ Custom header (X-API-Version: 2.0)
• ✅ Content negotiation (Accept: application/vnd.company.v2+json)

Common Questions

• "How would you version an API that mobile apps depend on?"
• "How would you implement a breaking change without disrupting users?"
• "Design an API that must meet regulatory requirements"

Security Architecture

PCI Compliance Critical Points

• ✅ Tokenize card data immediately
• ✅ Segment networks with card data
• ✅ Implement least-privilege access
• ✅ Maintain comprehensive audit trails

Common Questions

• "How would you design a PCI-compliant payment system?"
• "How would you implement secure key management?"
• "Design a system for storing sensitive customer data"

Interview Quick-Reference

Technical Trade-offs

Critical Interview Gotchas

1. Forgetting Compliance: Always mention regulatory requirements (PCI, KYC, AML)
2. Skipping Idempotency: Critical for any payment or money movement operation
3. Ignoring Reconciliation: Every FinTech system needs reconciliation mechanisms
4. Security as Afterthought: Start with security principles, not add them later
5. Missing Audit Trails: Financial systems must log all sensitive operations

Performance Benchmarks

Interview Problem Solving Framework

1. Clarify Requirements

Example Questions

• What transaction volumes need to be supported?
• What latency requirements exist?
• What regulatory requirements apply?
• What are the critical vs. non-critical operations?
• What consistency guarantees are required?

2. System Architecture Components

Critical Checklist

• Client-facing APIs with versioning strategy
• Service boundaries and communication patterns
• Data storage and partitioning approach
• Consistency and transaction model
• Security and compliance implementation

3. Deep Dive Areas

Be Prepared To Explain

• How you ensure data consistency
• How you handle system failures
• How you scale each component
• How you secure sensitive data
• How you monitor and troubleshoot

4. Trade-off Discussion

Framework for Decisions

• Justify consistency vs. availability choices
• Explain security vs. performance decisions
• Discuss build vs. buy considerations
• Detail scaling approach with cost considerations
• Address operational complexity trade-offs

5. Evolution and Future-Proofing

Key Points

• How the system adapts to changing regulations
• How new payment methods would be added
• How you'd handle 10x growth in transaction volume
• How you'd migrate to a new architecture component

Real Interview Questions & Solutions

Payment Gateway Design (Stripe)

Question: Design a payment gateway that can handle 10,000 transactions per second with 99.99% availability.

Winning Approach:

1. Architecture: API Gateway → Payment Service → Tokenization Service → Multiple Payment Processors
2. Key Components:
   • Stateless API servers behind load balancers
   • Redis clusters for idempotency keys and rate limiting
   • Multiple payment processor integrations with failover
   • Kafka for async event processing
   • Read replicas for reporting queries
3. Scale Strategy:
   • Horizontal scaling of stateless services
   • Database sharding by merchant ID
   • Regional deployment for latency optimization
4. Resilience:
   • Circuit breakers for downstream dependencies
   • Retry mechanisms with exponential backoff
   • Automated failover between payment processors

Common Mistakes:

• Not addressing PCI compliance
• Missing idempotency implementation
• No reconciliation mechanism
• Inadequate error handling

Real-time Balance System (Square/Block)

Question: Design a system that maintains real-time account balances for millions of users performing thousands of transactions per second.

Winning Approach:

1. Architecture: API Gateway → Transaction Service → Account Service → Ledger Service
2. Key Components:
   • Transaction journal for durability
   • Optimistic concurrency for high throughput
   • In-memory cache layer for balance reads
   • Event sourcing for account state
3. Consistency:
   • Two-phase commits for multi-account transactions
   • Sequential transaction IDs for ordering
   • Write-ahead logging for crash recovery
4. Performance:
   • Read/write path separation
   • Account-based sharding
   • Materialized views for balance calculations

Common Mistakes:

• Using distributed transactions without understanding costs
• No strategy for cache consistency
• Missing reconciliation mechanism
• Not addressing race conditions

Fraud Detection System (PayPal)

Question: Design a fraud detection system that processes transactions in real-time (<200ms) with a false positive rate below 3%.

Winning Approach:

1. Architecture: Real-time Feature Service → Rules Engine → ML Scoring Service → Decision Service
2. Key Components:
   • Feature store with pre-computed user profiles
   • Tiered detection approach (rules → ML)
   • Ensemble model architecture
   • Human review workflow for edge cases
3. Performance:
   • Parallel feature computation
   • Model optimization for inference speed
   • Feature caching strategy
4. Business Integration:
   • Risk-based authentication triggers
   • Dynamic threshold adjustment
   • Comprehensive explainability system

Common Mistakes:

• Complex ML without practical latency considerations
• No strategy for feature freshness
• Missing explainability for regulatory compliance
• No feedback loop for continuous improvement

System Design Worksheets

Payment Gateway Worksheet

Problem: Design a payment gateway for an e-commerce platform

Critical Components to Include:

• API layer with authentication/authorization
• Tokenization service for PCI compliance
• Payment processor integration
• Transaction storage and state management
• Idempotency mechanism
• Notification/webhook system
• Reconciliation system
• Error handling and retry logic

Key Questions to Address:

1. How do you handle payment processor outages?
2. How do you prevent duplicate charges?
3. How do you handle partial refunds?
4. How do you ensure PCI compliance?
5. How do you scale during peak shopping periods?

Fraud Detection Worksheet

Problem: Design a real-time fraud detection system

Critical Components to Include:

• Feature engineering pipeline
• Rules engine for obvious cases
• Machine learning model ensemble
• Decision engine with thresholds
• Feedback loop mechanism
• Explanation system
• Manual review workflow
• Performance monitoring system

Key Questions to Address:

1. How do you balance false positives and false negatives?
2. How do you handle feature computation latency?
3. How do you explain model decisions for compliance?
4. How do you update models without disrupting detection?
5. How do you handle different fraud patterns by region/product?

Trading Platform Worksheet

Problem: Design a stock trading platform

Critical Components to Include:

• Market data integration
• Order management system
• Matching engine
• Position management
• Risk management system
• Settlement and clearing
• Notification system
• Regulatory reporting

Key Questions to Address:

1. How do you handle market volatility?
2. How do you ensure order execution fairness?
3. How do you prevent front-running?
4. How do you scale during market open/close?
5. How do you implement circuit breakers?

Role Progression Markers

Junior Engineer Focus

• Implement specific components within established architecture
• Understand basic security requirements for financial data
• Follow team patterns for idempotency and error handling
• Implement proper logging and monitoring
• Write thorough unit and integration tests

Mid-Level Engineer Focus

• Design service-level architecture with proper interfaces
• Implement security and compliance requirements independently
• Optimize performance for specific services/components
• Design proper data models for financial information
• Implement resilience patterns like circuit breakers

Senior Engineer Focus

• Design system-wide architecture with proper boundaries
• Make appropriate trade-offs between consistency, availability, and performance
• Design for regulatory compliance from ground up
• Create scalable and resilient systems
• Define technical standards for the team

Staff/Principal Engineer Focus

• Design enterprise-wide architectures
• Define security and compliance architecture
• Optimize for global scale and multi-region deployment
• Create systems that adapt to regulatory changes
• Design for 10x scale with appropriate cost considerations