10 Tips to Reduce Card Not Present (CNP) Fraud

card not present fraud

As Card Not Present fraud continues to hurt merchants, issuers and acquirers, we look at actions your business can take to reduce it today.

The core of the problem with card not present fraud (CNP) can be explained in one simple question: how do you prove that cardholders are who they say they are?

It’s not an easy task, and it’s what makes them so risky. Sadly, card not present fraud continues to be an expensive affair, set to cost issuers, merchants and acquirers an estimated $34.66B by 2022

But luckily, it’s a plague everyone is working together to fight. And there’s actually a lot you could do, as an online business, to reduce CNP fraud yourself today. 

Here are ten tips I collected by gathering insights from industry specialists in fraud prevention.

#1 Collect All the Customer Info You Can 

Generally speaking, the more customer data you have, the better. This is true in the context of fraud protection, but also marketing and sales. Upselling, cross selling and good segmentation can be thanks to the same data that allows you to validate user IDs, or to dispute a chargeback.

As to the kind of data you should gather, the bare minimum would be:

  • Email address
  • Credit card info
  • Billing address
  • Information about the device used to log in
  • IP address
  • Phone number

Now you have three main touchpoints to gather that information: registration, login or at the point where you take credit card payments. 

And while it’s your duty to follow the best SCA practices, there’s a lot more info you can collect. User devices, phone numbers or email addresses can go a long way in filtering out bad agents – or at least prove they’re risky users, as we’ll see later.

  • Why it works: the more data you have about a user, the easier it can be to refuse suspicious payments that could be clear cases of card not present fraud.  
  • Main challenge: collecting data without creating too much friction for the user, which can hurt conversions and sales.

#2 Go the Extra Mile With Data Enrichment

If you read the first tip and wondered: how do I collect extra info without creating friction? The answer is data enrichment. It’s no wonder these tools are used by everyone from ecommerce to financial institutions these days.

Put simply, it is a process that takes single data points and uses them to aggregate data from external sources. For instance, an email address is analyzed, and found to be used for registration with social media profiles. Likewise, you take a phone number and see if it’s a landline or cell phone, and in which country.

All that info helps detect suspicious discrepancies. And best of all, it can be done pretty much instantly, and without asking the users for extra authentication steps if you use the right tools.

  • Why it works: data enrichment can be invisible to the user, which helps you reduce risk without creating too many obstacles for the right customers.
  • Main challenge: enriching data from sources that make sense, and from fresh, open source datasets. For instance, by linking an email address to the user’s connected social media accounts in use, which should be done by meeting GDPR requirements.

#3 Stick to the Best Data Protection Practices

Even though the customer isn’t standing in front of you, it’s still your job to protect their credit information. At least that’s what PCI Data Security Standard (PCI DSS) says, and it’s mostly to protect everyone from potential CNP fraud attempts.

In practice, that means using online security tools like SSL, especially on pages that collect sensitive information such as credit cards, social security numbers, or addresses. You should also encrypt data as efficiently as possible, whether it’s shared between your customers and website, or between staff members. 

  • Why it works: data that’s encrypted and safeguarded is less likely to fall into the wrong hands, which reduces CNP fraud as a whole.
  • Main challenge: managing backup copies and configuring data protection software and hardware can be costly due to rapid data growth. It’s the #1 most cited challenge by industry experts.

#4 Keep An Eye On Unusual Behaviour

Hopefully by now, you have enough data to start gathering insights about user behaviour. While what is considered fishy can differ from one business to the next, there are a few general red flags to keep an eye for, perfectly exemplified in the graphic below:

  • Why it works: Fraudsters often try to work fast, and use multiple stolen card details in a row to maximize how much they can extract. This means their behaviour follows certain patterns that point to CNP fraud.
  • Main challenge: Analyzing behaviour is very difficult to do without a proper fraud prevention solution in place as it needs to be done in real time.

#5 Look Out For Very Small Transactions

Not all the fraudulent payments made to your business will impact you directly. Sometimes, fraudsters will use you to “test a card”, usually by purchasing inexpensive items or services.

Of course, if the transaction goes through, fraudsters could very well use the same stolen card to purchase more expensive items, which will damage your business eventually. 

  • Why it works: identifying card testing as soon as possible can help prevent fraudsters from using stolen card details for larger transactions.
  • Main challenge: keeping an eye on small transactions that would otherwise go under the radar.

#6 And Gift Cards Too

Gift card fraud is often a problem that goes hand in hand with CNP fraud. Individuals looking to quickly turn stolen products into cash will often activate gift cards using stolen payment details, then sell these digitally delivered funds on an open marketplace within minutes.

If your company has a loyalty program or offers gift cards as a product (or payment method) it helps to be extra vigilant there.

  • Why it works: Adding an extra hurdle for fraudsters who want to perform gift card fraud can help reduce card not present fraud too. 
  • Main challenge: Offering enough payment channels and loyalty programmes without suffering from bonus abuse.

#7 Don’t Be Afraid to Ask For Extra Authentication

At this stage, you should have all the data and insights you need to segment users based on how risky they are. So it’s time to reduce the risk by asking for extra authentication details. 

At SEON, we like to call it light and heavy KYC. And our system is adept at only triggering the heavy authentication methods based on risk thresholds. That means that legitimate users will be able to purchase with as little friction as possible, while potential CNP fraudsters will have a harder time going through the hoops.

Each business needs to find the right balance between heavy and light KYC

In practice, you’ll be looking at first enabling light KYC tools like email analysis, IP analysis, or device fingerprinting, amongst others.

If you find enough red flags to be worried, you can then trigger additional authentication measures such as ID verification, 2FA or credit card preauthorization.

  • Why it works: You keep your customers happy, and discourage card not present fraudsters by letting them know they are suspicious.
  • Main challenge: Once again, it can be hard to automate adaptable KYC at scale without the right fraud prevention system.

#8 And Don’t Hesitate to Dispute Chargebacks

One aspect of card not present fraud we haven’t really covered yet is the problem of friendly fraud. As you may already know, there’s nothing friendly about it, and tends to occur when:

  • Customers change their mind about a purchase and claim it was fraudulent
  • Use their real card to try and scam the system by claiming a chargeback
  • Family members use the card without authorization

The takeaway here is that the chargeback is clearly the customer’s fault. And believe it or not, issuers and banks are actually quite good at siding with businesses, if you have all the right data to back up your claim (which goes back to my tip #1 and #2).

So what can you do armed with the right data and enriched data? Well, for instance one of our clients uses our social media analysis tool. They found that some customers claimed they’d never received the product, and discovered social media posts of them showing the very same product off online. Talk about getting caught red-handed.

  • Why it works: If you have the right data at hand, it can be easier than you think to win a chargeback dispute, which can be considered “friendly CNP fraud “.
  • Main challenge: Collecting the right data at the right time.

#9 Dig Into Velocity Rules

The last two tips are more technically advanced, and I don’t imagine you’d be able to do it without a complete fraud prevention solution. 

So if your system allows it, I would highly recommend looking at velocity rules. These are rules for calculating risk that look at connections and combinations of data points happening during a set timeframe, such as:

  • Shipping address connected to multiple different cards in a short period of time
  • High number of transactions on the same card
  • High order value and fastest shipping method
  • High priced items orders during the day…

So it is a kind of behavior profiling, and a highly efficient one at that. 

  • Why it works: Another way of profiling CNP fraudsters behaviour, without creating friction for legitimate users.
  • Main challenge: The number of combinations of velocity rules is virtually infinite, so you need to refine your search (or let an AI system help) to extract good parameters.

#10 Build Risk Scoreboards

Reducing CNP fraud is all about calculating risk and setting your thresholds. So sometimes you need to have enough data on fraudsters to be able to predict who will be a bad customer. One convenient way to do it is through risk scoreboards, which allow you to cluster users based on similar data, behaviour and risk score.

These scoreboards, which use statistical models, can vary greatly in complexity, so I won’t go into too much technical details here. But whether you do it manually or use an automated solution, scoreboards are a fantastic way to detect fraud, and therefore reduce CNP fraud damage. 

  • Why it works: Creating risk models helps extract insights about bad users and detect fraud before it can happen.
  • Main challenge: Risk scoreboards are complex statistical models that can be hard to create manually.

Key Takeaway

Like with many other types of fraud, the best defense against CNP fraud is to be prepared, well-equipped, and knowledgeable. This is true whether you use a full end-to-end fraud prevention system, or multiple layers of protection via different tools.

Simplifying data enrichment for small businesses is also something we’ve been thinking about a lot at SEON. This is why we even created a tool that gives you complete flexibility by working as a one-click data enrichment solution: our Extension for Google Chrome

It’s designed to speed up data enrichment based on email addresses, phone numbers or IP addresses, so you can start reducing CNP fraud in one click today. 

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