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How Better Data Can Reduce Chargebacks (Including Friendly Fraud) up to 86%

posted on: Thu Nov 02 2017

Chargebacks were first introduced over 40 years ago, long before eCommerce became the dominant force it is now. Today, with U.S. eCommerce retail sales projected to exceed $400 billion this year, chargebacks and card-not-present (CNP) fraud represent a huge expense for online merchants.

Fortunately, the right enterprise-class fraud prevention solution can take advantage of Big Data and the huge leaps we’ve seen in computing and data processing power to allow online businesses to detect and prevent online fraud better than ever before.

ChargebackBut even with world-class fraud prevention putting the brakes on criminal fraud, chargebacks can still be an issue. Recent research indicates that up to 86% of chargebacks may be cases of friendly fraud. Friendly fraud is when consumers wrongly or illegitimately dispute a transaction with their bank (the term originates from the expression “friendly fire”). The reasons behind friendly fraud chargebacks are numerous, including:

  • Merchant or shipper error. Nearly 40% of disputes are due to the retailer shipping the wrong product or the product never arriving. Instead of requesting a refund/exchange or reporting an insurance claim against the shipper, the cardholder files a chargeback.
  • Consumer behavior. The buyer receives the correct product, but it doesn’t meet expectations. Rather than requesting a refund or exchange, the buyer instead files a chargeback.
  • Outright theft. The cardholder engages in digital shoplifting by knowingly filing a false chargeback claim.
  • Simple misunderstanding. 49% of cardholders don’t realize they’re filing a chargeback.

For those instances when a consumer does file an illegitimate chargeback, the data that enterprise-class fraud prevention solutions like Kount Complete™ analyze for each transaction can be extremely valuable for proving that a charge is valid during representment. For example, a common claim made by consumers who commit friendly fraud is that they did not order an item. Kount Complete’s ability to show that the IP address and geolocation for the device that made the order corresponds to the billing and delivery address provides strong evidence that the consumer did in fact place the order.

The economic impact of successfully countering chargebacks can be startling. ClickBank—a Top 100 Internet Retailer specializing in digital product sales, such as eBooks, software, memberships, and digital subscriptions—capitalized on the power of Kount’s data and our partnership with Chargebacks911 to increase their representment win rate to 72%. This was responsible for adding $409,000 directly to their bottom line in just 60 days.

Other tips for reducing friendly fraud chargebacks include:

  1. BEST PRACTICES. Maintain delivery receipts that prove buyers received their goods. Make sure the charge description on the cardholder’s statement matches expectations. For example, if your website is called Julia’s Flowers, the charge should have that name associated with it and not the name of a parent company or other corporate division, which may confuse the cardholder. And clearly publish your cancellation and refund policies so consumers know their obligations and how to file for a refund or exchange.
  2. CUSTOMER SERVICE. Make it easy for customers to get in contact with you. Respond promptly to customer inquiries, monitor social media, and track all customer interactions.
  3. BE PREPARED. Use an enterprise-class fraud prevention solution like Kount to prevent criminal fraud and to win the fight against friendly fraud with representments supported by data.
  4. BOOST SALES. Make sure your fraud prevention system doesn’t add friction to checkout (Kount processes transactions in an average of 250-350 milliseconds) and doesn’t increase false positives that reduce revenue.

Want to do a better job of reducing chargebacks? Discover some of the best practices for fighting chargeback fraud in our new eBook “There's No Such Thing As Friendly Fraud".

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