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The Road To Overcoming Data Overload

You don’t need to be an actuary to notice the correlation between the growth of ecommerce and the evolution of online merchant-based payment fraud. This is due two main factors: The first is the proliferation of Do It Yourself websites. These let merchants get their websites looking professional and legitimate in just a few clicks. All they have to do is follow a template, add a shopping cart and a cashier/checkout page. The other factor is the large choice of payment service providers and facilitators, particularly in the ecommerce domain — PayPal, Google Wallet, etc. These have given birth to an increasing number of marketplaces and micromerchants.

According to Worldpay, an Atlanta-based payments company with global reach, the global ecommerce market will be worth $2.4 trillion by 2019. That means plenty of opportunity for legitimate profits, and plenty of opportunity for criminals.

As I described in Transaction Laundering: Unreported Ecommerce on the Rise, one of the types of ecommerce crime is a sophisticated form known as Transaction Laundering (TL). This is when emerchants hide illegal activity or transactions on behalf of another merchant, knowingly or unknowingly, through a legitimate website. This year, VISA reported that 75% of all fraud related fines were related to transaction laundering.

Few in the payment industry can turn a blind eye to this phenomenon. In fact, Worldpay’s ‘Fraud Trends 2016 Latest perspectives on international eCommerce’, reinforces what I’ve been seeing for quite some time in my encounters with Merchant Service Providers (MSPs).

What is the true nature of these transactions?­

Due to the overwhelming number of emerchants and data associated with these merchants, MSPs are faced with data overload. Collecting data on merchants is not enough. They do not know what to do with it. Out of Worldpay’s 200 respondents, 58% of Worldpay’s said that they collect information that they do not use and 85% expressed that they required greater insight to fight fraud.

Then there’s the data that may not be collected at all — mobile transaction data or mcommerce data, for example. Since consumers are making more and more payments using their mobile devices, MSPs are even more vulnerable. For example, transaction laundering criminals can use mobile apps to reroute payment information to their partners, as these devices are less secure than desktop based purchases.

Although 59% of respondents said that they fully understand the increased risk relating to transactions made on a mobile device, most merchants are treating mobile transactions as ‘just another channel’. But not all solutions have the technology to collect and monitor data on mobile. When transaction launderers use mobile apps to process payments for illicit purposes through legitimate merchant accounts, it’s almost impossible for the payment industry to detect. When fraudulent transactions go undetected, banks can end up paying heavy fines, face legal action and damage their overall reputation.

Worldpay’s report goes on to say that in regards to mobile, ‘time will be the test’. I disagree. MSPs cannot stand by and wait. The future to combating online fraud includes a solution to detect and prevent transaction laundering activities from entering the payment ecosystem today rather than letting the fraudsters flee. MSPs need a system that reveals related and unreported mobile applications, URLs, and payment environments.

Using cyber intelligence to automate the data collection, combined with human intelligence is the ideal solution to combat online fraud —today, and on an ongoing basis. Cyber intelligence automates data analysis to uncover patterns that may suggest transactional laundering violations. It can reveal things merchants would not have thought to query, as they have been masked behind seemingly legitimate transactions on legitimate websites. Cyber intelligence doesn’t just collect the puzzle pieces. It assembles them together and creates a clear picture of what is actually going on. The combined approach allows MSPs to collect very large amounts of data and derive insights regarding transaction laundering which they find to be relevant and actionable.



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