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Top 5 APIs for Credit Card Fraud Prevention

Fraud prevention in payments is a layered problem: validating cards, confirming user identities, checking addresses, and monitoring transaction patterns. Different APIs excel at different parts of this stack. For businesses selling expensive products, it’s critical to balance enterprise-grade protection with flexible, pay-as-you-go pricing.

Here’s a breakdown of leading APIs, including Melissa and Loqate, and when to use each.


1. Stripe Radar — Built-in Payment Platform Protection

  • What it is: Fraud detection baked into Stripe’s payments ecosystem.
  • Strengths: Machine learning trained on billions of global transactions, instant fraud scoring, minimal setup.
  • Best for: Teams already using Stripe for checkout who want out-of-the-box card protection without integration overhead.
  • Pricing: Included with Stripe fees; advanced plans add a per-transaction charge.

2. MaxMind minFraud — Transaction Scoring

  • What it is: Real-time risk scoring API using IP, email, device, and card data.
  • Strengths: Highly configurable, long history in fraud prevention, integrates into custom approval logic.
  • Best for: Approval workflows and gating — allowing you to set thresholds and rules for declines or manual review.
  • Pricing: Pay-as-you-go per transaction lookup.

3. Melissa & Loqate — Address and Identity Verification

  • Melissa
    • What it is: Enterprise-grade verification for names, addresses, phones, and emails, widely used in banking and telco.
    • Strengths: Regulatory compliance (KYC/AML), fraud reduction through identity trust.
    • Best for: High-value transactions where customer legitimacy is critical.
    • Pricing: Pay-as-you-go credits for validation; volume discounts available.
  • Loqate
    • What it is: Global address validation and geocoding API.
    • Strengths: Ensures billing/shipping addresses match real-world locations, reducing chargeback risk.
    • Best for: E-commerce merchants selling expensive physical goods who need address accuracy before shipment.
    • Pricing: Flexible pay-as-you-go per lookup.

4. Riskified, Sift, Feedzai, FraudLabs Pro — Advanced Fraud Platforms

  • Riskified: Adaptive checkout workflows, AI-based approval, proven to recover revenue from false declines.
  • Sift: End-to-end fraud detection across user lifecycle (account signup → checkout).
  • Feedzai: Enterprise-grade, real-time fraud analytics at banking scale.
  • FraudLabs Pro: Lightweight REST API with customizable rules, good for small-to-mid businesses.
  • Best for: Custom approval logic and behavioral fraud detection beyond basic card validation.
  • Pricing: Riskified and Feedzai use enterprise contracts; Sift and FraudLabs Pro offer usage-based tiers.

5. SpyCloud Cards API & Ekata — Proactive Monitoring and Identity Defense

  • SpyCloud Compromised Credit Card API
    • What it is: Database of compromised cards from breaches.
    • Strengths: Blocks cards before they’re used fraudulently.
    • Best for: Proactive exposure monitoring.
    • Pricing: Typically subscription-based; scales by query volume.
  • Ekata
    • What it is: Identity trust API (formerly Whitepages Pro).
    • Strengths: Detects synthetic identities and validates customer details against global datasets.
    • Best for: Preventing fraud at account creation and checkout.
    • Pricing: Pay-as-you-go pricing; enterprise packages available.

Quick Recommendation Matrix

GoalBest API(s)
Built-in protection during checkoutStripe Radar
Approval logic / custom workflowsMaxMind, Riskified, Sift, Feedzai, FraudLabs Pro
Proactive exposure monitoringSpyCloud Cards API
Identity verification & synthetic ID defenseEkata, Melissa
Address validation for physical shipmentsLoqate, Melissa

Key Statistics

SourceWhat was measured / ExperimentResult / Metric
Stripe (3DS / Radar)In one experiment, lowering the threshold at which 3DS is triggered (i.e. making it required more often)74% decrease in the fraudulent dispute rate (Stripe)
Stripe Radar (general)Blocked high-risk transactions + decrease in carding attacks over timeAccording to Chargeflow, Stripe blocked 20.9 million fraudulent transactions (≈ $917 million) during BFCM; also reported they reduced carding attacks by ~80% over two years using updated ML models. (Chargeflow)
Sift (PayMongo case)After implementing Sift Payment Protection, PayMongo scaled and reduced lossesThey kept fraud losses and chargebacks “well below threshold,” safely handled 10-20× more transactions with fewer disputes. (Sift)
Sift (Tutory case)False positives & manual reviews reductionReduced manual review volume by ~83%, and achieved a chargeback rate of 0.17% in a case of first-party fraud. (Sift)
Sift (global data, payment fraud attack rate)Year-over-year growth / blocking ratesFrom Sift’s Digital Trust Index: payment fraud attack rate is increasing, but networks are blocking many attacks. For example, “ATO attack rate … up 56% YoY” in Q4 2024. This shows how much fraud is being blocked vs how fast attacks are increasing. (Sift)

Conclusion

No single API covers the full spectrum of fraud. The most resilient approach is layered:

  • Use Stripe Radar for real-time scoring if you’re on Stripe.
  • Add MaxMind or Sift for custom decisioning.
  • Protect identities with Melissa or Ekata.
  • Validate addresses with Loqate.
  • Monitor compromised cards with SpyCloud.

All of these support pay-as-you-go pricing (or tiered usage), making it feasible for e-commerce businesses selling high-value products to scale protection without overcommitting to enterprise contracts.

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