Shopify Fraud Score Checker

What it does

Automatically flags Shopify orders with high fraud risk scores and holds them for manual review before fulfilment, preventing chargebacks and protecting your business from fraudulent purchases.

Why I recommend it

Shipping to fraudsters costs you the product, shipping fees, AND the chargeback fee. One $500 fraud order can wipe out the profit from 50 legitimate sales. Automated fraud detection catches suspicious orders before you lose money.

Expected benefits

  • Reduced chargebacks and fraud losses
  • Protected profit margins
  • Less time manually reviewing every order
  • Peace of mind on high-value orders

How it works

New Shopify order created -> check fraud analysis score -> if score above threshold (e.g., “high” risk) -> hold order from fulfilment -> send alert to fraud review team -> require manual approval before shipping.

Quick start

Start by setting Shopify orders with “high” fraud risk to not auto-fulfil. Review these manually daily. Once you trust the system, add automatic alerts and create a review queue.

Level-up version

Combine Shopify’s fraud score with additional signals (new customer + high value + expedited shipping + mismatched billing/shipping address) to create a custom risk score. Auto-refund and cancel obvious fraud, only flag borderline cases for review.

Tools you can use

E-commerce: Shopify

Fraud detection: Shopify Fraud Analysis, Signifyd, Riskified

Alerts: Email, Slack, SMS

Order management: Shopify admin, ShipStation

Also works with

E-commerce platforms: WooCommerce, BigCommerce, Magento

Fraud tools: Forter, Kount, Sift for advanced fraud detection

Technical implementation solution

  • No-code: Shopify order webhook -> Zapier checks fraud_risk_level field -> if “high”, send Slack alert + add “REVIEW” tag to order + hold from auto-fulfilment app.
  • API-based: Shopify webhook on order creation -> parse risk_level -> if high, update order with hold status via API -> create review task in system -> alert team.

Where it gets tricky

Balancing false positives (legit customers flagged as fraud) with false negatives (fraudsters slipping through), handling international orders with different risk profiles, and creating a smooth review workflow that doesn’t delay legitimate orders.