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Influencer Insights: High-risk Merchants Are at Risk of MATCHing

by Bradley
May 24, 2019
in Articles, Influencer Insights

multifacetedgirl / Pixabay

Visa shifts its risk monitoring programs by toughening the qualifying thresholds for the Visa Chargeback Monitoring (VCMP), and Visa Fraud Monitoring (VFMP) programs. It aims at the introduction of stricter thresholds to ensure that merchants’ sales tactics and transaction processing are ethical.

The industries that will be most impacted by Visa’s changes are the same verticals impacted in 2015: adult goods, online gaming and gambling, discount health and online pharmacies, e-cigarettes and drug paraphernalia, weapons, and many types of travel services, i.e. booking tickets, renting a car online. These industries share characteristics such as multi-currency payment options and reliance on recurring billing. However, along with the growth of e-commerce –  an increase of 150 billion dollars since 2015 in the US alone (SalesCycle) – the scale of the phenomenon might be significantly greater.

Merchants with fully implemented chargeback mitigation strategies are not the most vulnerable, although they may be under closer scrutiny. It’s the merchants who are currently dangerously close to the 1% threshold that may find themselves in danger of joining the “high-risk merchants” category and by extension getting forced into Visa’s chargeback monitoring program. Once in the program, merchants will be hit with much higher third-party processing fees.

The lowered threshold will cause merchants who unsuccessfully set their risk management strategies to receive an increased number of penalties from acquirers. Soon, the stricter Visa rules will also cause increased caution from acquirers who will let go of some merchants that don’t qualify for close monitoring.

If the merchant gets listed on MATCH (Member Alert to Control High-Risk Merchants), they will need to sign up for a new processor facing an extended settlement period, high set up fee, and the requirement to maintain the reserves. While this may not be a headache for large companies, smaller ones can quickly encounter problems with their resource liquidity.

In addition to taking care of customer satisfaction and frictionless selling/refund processes, merchants must be prepared for fraudulent activities. With the constant evolution of fraudsters and the dark web, it is necessary to secure payment providers with anti-fraud tools (like Straal secured by Nethone Guard) that can mitigate risk at all stages of the sale. Using the full potential of data, merchants can shed light on the whole purchasing process and make predictions about who is making purchases with fraudulent intentions. Opportunities to watch customers online is limited – most often, merchants know as much about their customers as they choose to tell them. Therefore, it is necessary to use services that reveal additional information about each user. This is most effectively done via a process of picking up data and discovering patterns between variables unrelated at first glance. Due to the volume and the complexity of data, Machine Learning is the most useful analytical method to accomplish that.

One of the key values for online merchants that Nethone provides is comprehensive KYU analytics (KYU). Besides profiling, it combines external merchant data to provide a real-time decision accurately and transparently to closely detect fraudsters who damage merchants’ reputation with chargebacks. And that’s exactly why we decided to create Nethone – to bring KYU analytics to online merchants.


Hubert Rachwalski, Nethone, CEO

Mr Rachwalski is a strategy and operational excellence fanatic with broad experience as a management consultant (BCG) and some M&A experience. Even before becoming an IT consultant (PWC) he was an AI enthusiast writing his MA thesis on implementing quant methods in stock portfolio optimisation. Hubert is a graduate from HEC Paris (Hautes Études Commerciales de Paris) in Management/Strategy and Warsaw School of Economics in Quantitative Methods in Economics.

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