In the rapidly evolving world of e-commerce, an increasing number of transactions are taking place online. This growth, while promoting global commerce and convenience, has inadvertently created opportunities for online scams. In particular, sophisticated merchants have learned to exploit the safeguards of dispute management programs put in place by payment service providers and acquiring banks.
To safeguard customers and maintain the integrity of their services, payment service providers and card networks like Visa and Mastercard have developed dispute and fraud card monitoring programs. These programs are designed to identify and manage accounts that have excessive levels of disputes (chargebacks) and fraudulent activities. Unfortunately, while these programs have been instrumental in mitigating many forms of fraud, they are not without their flaws.
Thresholds:
Visa chargebacks are calculated based on data collected from the first day of a given month to the first day of the following month.
Mastercard chargebacks are calculated based on data collected from a chosen date, to the same day of the following month.
The monitoring programs operated by Visa and Mastercard work by tracking the volume and rate of disputes related to a particular merchant account. Thresholds are set to trigger when disputes reach a certain volume or percentage of the total transaction. For example, in Visa's Dispute Monitoring Program (VDMP), an early warning is triggered at 75 disputes or a 0.65% dispute rate, and in Mastercard's Excessive Chargeback Program (ECP), the threshold begins at 100-299 disputes or a 1.5-2.99% chargeback rate.
The Loophole:
A potential loophole arises because these thresholds are set to consider only the absolute number of disputes, not necessarily the dispute rate. This means that if a merchant has a high dispute rate but doesn't meet the minimum number of disputes in a given month, the dispute management program won't be triggered.
Furthermore, some crafty merchants run their operations across multiple websites. By spreading out their transactions, they stay under the radar, with none of their sites reaching the dispute threshold, despite their collective operations harboring a high dispute rate. This dilution strategy makes it difficult for dispute management programs to detect fraudulent activity.
Moreover, some merchants employ a method of temporarily disconnecting their websites. By halting operations for a couple of months, they effectively reset their dispute count with many monitoring programs, which typically require consecutive months of high dispute activity to be triggered. When these merchants resume their scam activities, they do so with a clean slate, undetected by the monitoring programs.
From the perspective of an acquiring bank or a payment service provider, this presents a serious challenge. Undetected, these merchants could continue running scams, which could lead to substantial financial loss and damage to the reputation of the bank or provider. Furthermore, these illicit activities could undermine customer confidence, affecting the broader e-commerce ecosystem.
To tackle these challenges, financial institutions and payment service providers must take a more holistic and robust approach to fraud detection. This might involve considering the overall dispute rate even if the absolute dispute count is below the threshold, looking for patterns across multiple websites, and considering non-consecutive months of high dispute activity.
Advanced data analytics and machine learning techniques can also be employed to detect unusual patterns, correlate activities across different websites, and identify potential fraud before it reaches a significant level. Additionally, closer cooperation with regulatory bodies and other stakeholders in the e-commerce ecosystem could help improve the rules and practices of dispute management programs.
While the current dispute management programs play a significant role in fraud prevention, they are not perfect. As the online world continues to evolve, so too must our strategies to combat fraud. It is only through continuous learning, adaptation, and innovation that we can stay ahead of those looking to exploit the system.
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