1. What kind of products do you sell?
Obviously, some product categories are at greater risk than others.
“If you sell white goods such as dishwashers or fridges you needn’t be as worried as if you sell Samsung or Apple smartphones,” says Luisa Stock, Manager for Fraud Detection at Klarna. “You need to be more vigilant when your products are in high demand on e-market platforms and are therefore easy and lucrative for criminals to resell”.
Examples of high-risk products are:
- Tickets for concerts
- Tickets for sport events
- Branded shoes
- Designer bags
- Tech products<
- Travel services
“You would think that industries like the groceries market would be safe, but no. Many grocery stores also sell electronics online,” says Luisa.
2. Does your system raise red flags for suspicious buying patterns?
Do you have a way to detect if…
… a person makes multiple orders within minutes?
… an order is placed from an IP address that just made 20 other purchases?
… the person placing the order is using a fake email address or an address from a suspicious domain?
… the same phone number has been used for multiple shipping addresses?
… someone has a history of changing the shipping address after orders have been sent out?
… your new customer has a track record of not paying bills?
… the email address given at the time of purchase has been used for multiple customers?
The list of suspicious buying patterns above is just the tip of the iceberg; there are many other things to look out for.
“These criminals have a lot of tactics to avoid being detected. If you sell shoes, for example, they might first try to order 5 or 10 pairs in different names and see what happens. If that goes well, they’ll try 20 next time, then 80, then 200,” explains Luisa.
Is it possible that organized criminals have been attacking your web store for months without you knowing?
3. How effectively do you review suspicious orders?
Let’s say you just identified a suspicious order. What do you do about it?
“Suspicious orders should be reviewed before you send out any products. Klarna uses a special tool to visualize transactions for review. Background algorithms analyze transaction data to flag up unusual patterns and any other suspicious behavior, making it much easier for the merchant to assess the transaction,” says Luisa.
“In many cases there is nothing to worry about. A red flag doesn’t necessarily mean you risk losing money, it just means you need to be more cautious.”
For example, when someone is asking for goods to be delivered to an address that’s been used for fraud in the past, would you let that pass or not?
“Upon investigation it may turn out that the new applicant has nothing to do with that previous fraud, and the transaction is safe to proceed. You don’t want to cancel orders unnecessarily”.
4. Do you keep up-to-date with criminal tactics?
Criminals are getting more sophisticated every day. In order to effectively defend your online store, you first need to be aware of the tactics they are using – and how to spot criminal activity.
“There are many variables to cross-check if you want to be successful in preventing fraud,” says Luisa. “That’s why we invest so much time, money and intelligence into our fraud pattern recognition systems. For example, we know that organized criminals follow certain trends in terms of the type of shoes they order, and at what price tag. These trends change all the time, but we keep on top of them and add the latest data into our fraud pattern recognition systems to protect our merchants”.
What does all this mean?
Let’s get back to the main question at hand: How easily can your products be stolen?
Well, if you are up-to-date and knowledgeable about the latest criminal fraud tactics, if you effectively review suspicious orders, and if you have ways of identifying suspicious orders in the first place, you don’t need to worry too much. However, if you’re not at this stage yet, it’s time to take this issue seriously – especially if your products are easy to resell.
Klarna detected and stopped fraudulent orders for 160 million SEK (about 18 million EUR) in 2017.