Claims that cardholders make for a chargeback of a valid credit or debit card purchase of digital or physical goods can be tied to confusion, remorse or abuse. Whether inadvertent or deliberate, these claims are referred to as either first-party misuse or friendly fraud. Chargeback requests are a worsening problem for merchants, particularly when tied to high-value or low-margin purchases.

Visa and Mastercard network rules favor cardholders at the expense of merchants. They were created to build trust in the card payment system. However, in recent years, it can be said that an increasing number of cardholders lack trustworthiness. For instance, they return: goods because they had buyer’s remorse; items after the timeframe allotted by a return policy; empty boxes to warehouses (and keep the goods); goods other than what they had properly ordered; used goods, sometimes even when damaged or with missing pieces, which renders them unable to be resold. Commonly, they dispute recurring payments for subscriptions because they forgot to cancel within the allowed time.

First-party misuse plagues online merchants especially because there is no human interaction in ecommerce. At some merchants, friendly fraud losses, including expenses tied to compliance with card network regulations, are eating into net income. To claw back revenue lost to friendly fraud while complying with network regulations, merchants need documentation that substantiates sales as legitimate.

However, network rules get updated twice a year, and big overhauls of those rules occur every few years. Even merchants with high-functioning in-house fraud fighting teams have a difficult time keeping up.

Automating the chargeback retrieval process is the core business of several companies. Justt is one, and it claims that it has never lost a head-to-head comparison when tested against any merchant’s legacy chargeback retrieval system or that of its third-party provider.

Justt says its success is tied to a dynamic argument approach that uses AI to gather needed data from merchants, the processors they use and other third parties to provide very specific responses as rebuttal to an issuer’s request for a chargeback.

Justt technology can gather more than 500 data points to build dynamic arguments against a chargeback. An argument is specific to each case based on the number of data points available. The greater the number of data points, the greater the chance of winning a case against a chargeback.

The company has spent the last five years building and improving its technology, combining domain expertise with constant A/B testing of scenarios to generate arguments that are more likely to win cases.

As Justt’s models steadily improve, the company’s enterprise clients, which include Best Buy, Affirm, Melio and DoorDash, benefit.

Partners, including Worldpay, Forter, Riskified and Ravelin, integrate Justt technology into their fraud fighting technology stacks.

With most enterprise clients, Justt receives a percentage of the revenue that merchants recover in the chargeback. It also operates under other revenue models.

Prior issue: 1215