What is E-commerce Fraud?

Types of E-commerce Fraud

Payment Fraud

CNP (Card Not Present) fraud represents the largest e-commerce fraud category. Fraudsters use stolen credit card information to make purchases. Without physical cards, online merchants can't verify cardholder identity the way brick-and-mortar stores can. IP Risk Score helps merchants identify suspicious transactions by analyzing IP addresses, device characteristics, and behavioral patterns that indicate fraudulent activity.

Card testing operations validate stolen cards through small purchases before committing larger fraud. Fraudsters test thousands of stolen card numbers on your checkout to identify which cards still work. These rapid-fire small transactions generate fees and chargebacks while providing no revenue.

Account Takeover (ATO)

Account takeover attacks compromise legitimate customer accounts through credential stuffing, phishing, or social engineering. Fraudsters access accounts and use stored payment methods, steal loyalty points, or change account details to lock out real owners.

ATO is particularly damaging because fraudsters exploit established accounts with purchasing history, making fraud harder to detect. They also damage customer relationships when legitimate users discover unauthorized activity.

Refund and Return Fraud

Refund fraud exploits return policies. Fraudsters order products, claim they never arrived, and request refunds while keeping merchandise. They file false damage claims, return different or worthless items in place of originals, or abuse "wardrobing" by using products briefly then returning them.

Serial returners abuse generous return policies systematically. They buy products, use them, and return them before deadlines—treating stores like free rental services. Some buy multiple sizes intending to return most, inflating return costs.

Promotional Code Abuse

Promo code fraud exploits discount codes and promotional offers. Fraudsters share single-use codes widely, create fake accounts to claim multiple new-customer discounts, or manipulate code generation algorithms to create unauthorized discounts.

Some fraudsters resell promotional codes on gray market sites. Others use bots to rapidly claim limited-quantity promotions, preventing legitimate customers from accessing deals while profiting from reselling discounted merchandise.

Inventory Theft Through Fake Returns

Sophisticated fraudsters file fake return claims for expensive items they never purchased. They claim accounts were hacked and unauthorized purchases occurred. If merchants refund without proper verification, fraudsters keep both merchandise and refund money.

Detecting E-commerce Fraud

IP Address Analysis

IP Risk Score provides real-time fraud assessment for every transaction. High-risk indicators include data center or proxy connections, VPN usage, IP addresses from high-fraud countries, geographic mismatches between IP location and billing address, and IP addresses with fraud history.

Velocity Checks

Monitor transaction velocity across multiple dimensions. Unusual patterns include multiple purchases from the same IP in short periods, rapid sequential orders to different addresses, many different cards used from one IP, or sudden spikes in high-value orders.

Order Anomalies

Suspicious orders show recognizable patterns. First-time customers making large purchases, mismatches between billing and shipping addresses, orders shipping to freight forwarders or package forwarding services, rush shipping requests, or multiple orders for identical products.

Account Behavior

Compromised accounts exhibit suspicious behavior. Password changes followed immediately by purchases, shipping addresses changed then large orders placed, sudden interest in gift cards or easily resold products, or shopping patterns completely inconsistent with account history.

Device Fingerprinting

Device fingerprinting tracks unique device characteristics. Fraudsters often use new devices or clear data to avoid detection. Multiple accounts or transactions from the same device despite different stated identities indicates fraud.

Preventing E-commerce Fraud

Implement IP Risk Scoring

IP Risk Score evaluates every transaction in real-time. Block or challenge high-risk orders based on IP characteristics, location patterns, and fraud signals. Allow trusted customers to checkout smoothly while scrutinizing suspicious sources.

Use Address Verification (AVS)

Address Verification System compares billing addresses with card issuer records. Mismatches indicate potential fraud. Configure AVS to decline high-risk mismatches automatically while manually reviewing moderate risks.

Require CVV Codes

Always require CVV (Card Verification Value) codes. The three or four-digit security code proves someone has physical access to the card. Many stolen card databases lack CVV codes, making this simple check effective.

Implement 3D Secure

3D Secure (3DS) adds authentication before completing purchases. Cardholders verify identity through passwords, SMS codes, or biometrics. 3DS shifts liability from merchants to card issuers for authenticated transactions, providing both fraud protection and chargeback protection.

Monitor for Account Takeover

Track login patterns for anomalies. Failed login attempts followed by successful access, logins from unusual locations, or access from suspicious IP addresses all indicate potential account compromise. Require additional verification for suspicious logins.

Set Velocity Limits

Limit transactions per IP address, email, billing address, or shipping address. Flag multiple purchases in short timeframes. Monitor for rapid order submission. These velocity checks catch automation and high-volume fraud patterns.

Verify High-Value Orders

Manually review orders exceeding certain thresholds. Call customers to verify large or suspicious orders. This extra step catches fraud before shipping expensive merchandise. Balance fraud prevention with customer experience—don't over-verify low-risk orders.

Analyze Return Patterns

Track return rates by customer, product, and address. Serial returners show consistent patterns. Flag customers with abnormally high return rates for additional scrutiny. Some legitimate customers return frequently, but extreme patterns indicate abuse.

Protect Promotional Codes

Limit promo code redemption per customer, IP address, or device. Use unique single-use codes. Track code sharing to identify abuse. Monitor for bot activity attempting to harvest or brute-force promotional codes.

Business Impact

Direct Financial Losses

Fraud causes direct revenue loss from stolen merchandise, fraudulent refunds, and chargebacks. Each chargeback costs $20-$100 in fees plus the original transaction amount. High chargeback rates result in additional fines or losing merchant accounts entirely.

Operational Costs

Fighting fraud creates operational burden. Teams investigate suspicious orders, review flagged transactions, handle chargebacks, communicate with payment processors, and manage fraud prevention tools. These costs add up quickly.

Customer Experience Impact

Overly aggressive fraud prevention frustrates legitimate customers. Declined transactions, verification requirements, or delayed shipments for flagged orders hurt customer satisfaction. Some customers abandon purchases entirely when encountering friction.

Inventory and Shipping Costs

Fraudulent orders waste inventory and shipping costs. Products shipped to fraudsters represent lost merchandise. Return fraud depletes inventory through fake claims. Shipping costs for fraudulent orders provide no return.

Frequently Asked Questions