Fraud Prevention protects your business from fake orders, stolen credit cards, and other malicious transactions. Effective fraud prevention balances security with customer experience. Block too little and you lose money to fraud. Block too much and you reject legitimate customers.
What is E-commerce Fraud?
E-commerce fraud occurs when someone makes purchases using stolen payment information or with intent to dispute legitimate charges.
Common fraud types:
- Card-not-present fraud: Using stolen credit card numbers online
- Account takeover: Accessing legitimate customer accounts
- Friendly fraud: Legitimate purchases disputed as unauthorized
- Triangulation fraud: Fraudster acts as middleman between victim and merchant
- Refund fraud: Fake returns or claims of non-delivery
How Fraud Prevention Works
Rule-based systems: Flag orders matching specific patterns (high value, new customer, shipping/billing mismatch).
Machine learning: Analyze hundreds of signals to predict fraud probability.
Velocity checks: Monitor for unusual patterns (multiple orders from same IP, rapid card testing).
Device fingerprinting: Identify returning devices regardless of account.
(AVS): Match with card issuer records.
CVV verification: Require card security code for all transactions.
Balancing Security and Experience
The fraud prevention dilemma: Every fraud prevention measure adds friction. Too much friction loses legitimate sales.
False positives: Legitimate orders incorrectly flagged as fraud. These cost revenue and damage customer relationships.
False negatives: Fraudulent orders that slip through. These cost the order value plus chargeback fees.
Finding balance: Most merchants accept some fraud to avoid losing good customers. A 0% fraud rate usually means too many legitimate orders are blocked.
Common Fraud Signals
High-risk indicators:
- Billing and mismatch
- New customer with high-value order
- Multiple orders from same IP address
- Expedited shipping on first order
- Failed payment attempts before success
- Gift card purchases with new accounts
Not always fraud: These signals correlate with fraud but also occur in legitimate orders. Use them as inputs, not automatic blocks.
Best Practices
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Layer your defenses. Combine multiple fraud prevention methods.
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Review manually when uncertain. Don't auto-decline borderline cases.
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Track your false positive rate. Know how many good orders you're rejecting.
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Adjust for your business. A $10 item has different risk tolerance than $1,000.
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Keep data for disputes. IP addresses, device info, and delivery confirmation help fight chargebacks.
