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On this page
  • Real Fraud
  • Recognizing fraud indicators
  • Recommendations
  • Friendly Fraud
  • Recommendations

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  1. Payments
  2. Disputes
  3. Prevention

Fraudulent

Preventing "Fraudulent" disputes: In this article, Payrexx explains how it works.

Digital payment processing opens up opportunities not just for merchants and shoppers, but also for fraudsters. If fraudsters manage to access customer payment data, it can lead to contested payments and disputes. In this article, you'll find recommendations on how to prevent fraudulent activities.

Fraud cases are divided into two subcategories: real fraud and friendly fraud.

Real Fraud

Recognizing fraud indicators

One of the most critical steps is early detection of fraud indicators. For this purpose, use fraud detection software or ensure good and regular training for your staff to significantly increase the chances of recognizing fraudulent transactions. Below are some common patterns that may indicate fraud.

Suspicious address details

  • suspicious email addresses (e.g., abc-123@example.com)

  • suspicious phone numbers (e.g., sequences like +41 123 456 789 or area codes from a completely different country than the address)

  • Inconsistencies in customer data (e.g., multiple purchases with the same email address but differing address details)

  • different billing and shipping addresses

  • international shipping addresses or orders with foreign credit cards

  • a freight forwarding company as the delivery address

Suspicious messages

  • Review orders where the content of the comment field appears suspicious or pre-fabricated by searching it on Google or another search engine. If the comment field content appears with other merchants, it could indicate fraud.

Order behaviour

  • an order that deviates significantly from usual ordering patterns, such as:

    • unusually high total order value

    • unusually large number of ordered items

  • multiple declined payments with different credit cards within a short period (could indicate a fraudster testing stolen card numbers)

Suspicious payment behaviour

  • numerous payments made with:

    • the same card but different delivery addresses

    • the same card and IP address

    • same delivery address but multiple cards

    • the same name and e-mail address

    • similar or identical card numbers within a short period

Declined payments may not always indicate fraud, but it is advisable to regularly check declined payments for suspicious patterns.

Special requests

If a customer makes unusual requests regarding their order, this could also indicate fraud. The following customer requests are suspicious and should be carefully checked:

  • splitting a large order into partial payments with different cards

  • charging a card an amount higher than required and asking to pay a courier or other third party with a different payment method (overpayment fraud)

  • requesting a chargeback outside of the card network (e.g., via bank transfer or check) instead of using the card with which the purchase was made

  • having a payment manually processed by a third party (fraudsters may aim to have the payment executed from a different IP address)

  • changing the delivery address after placing the order (fraudsters might use a valid address for payment and then have the products delivered to a different address)

  • requesting orders to be delivered via express delivery

  • having orders delivered by a shipping company suggested by the customer

  • requesting a refund for part of a larger donation (e.g., fraudsters pay CHF 1,000.00, then claim a mistake and say they only intended to donate CHF 100.00, asking for the difference to be refunded)

Specific indicators for digital products

Fraudsters often use stolen credit cards for orders of digital products. Check such orders for the following indicators, as they may suggest fraud:

  • A customer purchases a digital product multiple times within a short period.

  • Different customers make purchases with the same credit card or with very similar email addresses.

  • A customer purchases an unusually large number of products or pays unusually high amounts.

Recommendations

  • Delay shipping of expensive orders by up to 48 hours.

  • Delay shipping to unverified delivery addresses by up to 48 hours.

  • Match verified postal codes with the postal code on the label of the shipping company (some fraudsters provide a valid postal code but make false statements about street, town, canton, or state. Automated systems then automatically correct the postal code, replacing the verified billing address postal code with that of the fraudster).

  • Inform yourself about delivery addresses (destinations) with increased risk.

  • Issue a chargeback in the case of a suspiciously high donation from an unknown individual.

Friendly Fraud

Unlike criminal fraud, no stolen card data is used in friendly fraud (Friendly Fraud). Instead, the payments are made by the legitimate cardholders.

Especially in families, but also among friends or in companies, it can happen that an authorized user of a credit card account makes a purchase that the cardholder is unaware of. When the cardholder notices the purchase, it often leads to a dispute of the transaction. However, the challenge can also be initiated by the same person.

Generally, two types of "friendly fraud" are distinguished:

No intent

In these cases, for example, a child makes a purchase, the parents notice it, and dispute the payment. It's simply a mistake that occurred—no malicious intent involved.

Conscious fraud

Especially with digital products like online services and subscriptions, it happens that the purchase is made consciously, and it is deliberately disputed much later. This way, the customer can use the acquired service for weeks or months—at no cost if they win the dispute.

Since such disputes are based on a subjective assertion by the cardholder, it is not easy to counter them. However, there are indeed effective precautions you can take.

Recommendations

  • clear return policies

  • high accessibility and excellent quality in customer service to resolve unintentional cases early

  • good empathy from support staff

Last updated 11 months ago

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