Company Provides Data, Best Practices for Retailers to Stay Fraud-Free This Holiday Season
Boise, Idaho – November 1, 2017 – Merchants everywhere are undergoing massive preparations in anticipation of a busy holiday retail season, with this year’s sales to increase 15.8 percent from last year. Unfortunately, retailers need to be just as prepared to combat the fraudulent transactions, and their nasty side effects, that come along with high volumes of holiday sales. In order to help merchants protect themselves and maximize gains from this season, Kount has put together the Merchant Holiday Retail Guide, which outlines what merchants need to watch out for, holiday pitfalls seen from the 2016 season, and what merchants can do now for a holly jolly retail season.
Kount analyzed millions of transactions from its network of thousands of merchants to provide insight into the percentages of attempted fraudulent or high-risk transactions throughout the year. During the 2016 holiday season, Kount found:
- Black Friday 2016 saw the biggest increase in sales at 189%
- Cyber Monday 2016 saw the biggest increase in fraud attacks at 134%
- Transactions via mobile browser saw significant growth at 221%
- Fraud attacks from mobile browser transactions also saw an increase during Black Friday, Cyber Monday, and Green Monday
- Overall, sales during the holiday season in 2016 increased 148%, with fraud attacks up 122%
Kount also found that desktop transactions appear to be most risky, with an average attack rate of 11.013 percent of orders in Q4 2016. And not all mobile orders assume the same amount of risk — mobile browser transactions are about twice as risky as transactions via mobile app:
- Transactions via Mobile Browser:
- Q4 2016 Average Attack Rate: 6.906% of orders
- Transactions via Mobile App
- Q4 2016 Average Attack Rate: 3.443% of orders
Retailers often see the largest effect on their transactions a while after the holidays during Q1, as chargebacks from heavy holiday sales in Q4 often don’t get reported until several months down the line. This delay affects a retailer’s bottom line, and causes financial reports to show a distorted picture of your company’s performance. Those great sales and high profits seen by merchants in December may actually turn out to be ugly losses in February, March, and April, throwing off a merchant’s entire year.
“Our data shows that chargebacks seen in Q1 are a huge problem for merchants, and one that will only to continue to grow if retailers don’t get a handle on their fraud problem,” said Don Bush, VP of Marketing, Kount. “Chargebacks reports are included in calculating our average fraud attacks, which spiked in Q1 2017 due to holiday fraud from the previous quarter. Q1 2017 reporting showed an increase in fraud among all device types over what was seen during 2016’s holiday retail quarter.”
- Transactions via Desktop
- Q1 2017 Average Attack Rate: 11.86% of orders
- Transactions via Mobile Browser
- Q1 2017 Average Attack Rate: 11.05% of orders
- Transactions via Mobile App
- Q1 2017 Average Attack Rate: 11.76% of orders
However, there is good news for merchants who are worried about the safety of their transactions this holiday season. And no, this does not include limiting payment methods or sales locations. Having a comprehensive fraud prevention system in place can not only help merchants prevent fraud, but also allow them to boost sales, increasing revenue and bottom line. Merchants should follow the below tips to keep their business and customers safe this holiday season.
- Identify type of mobile device being used. The first rule is the simplest, and one that all merchants should already be able to determine.iPhones, iPads, Android devices, etc. all have different fraud profiles. Knowing the type of device allows you to screen accordingly.
- Speed is king. Fraud systems need to react as quick as possible to limit delays for the customer. Kount’s solution provides an easy-to-use interface and is friction-free during the checkout process, reducing manual reviews and chargebacks all in less than 300ms.
- Maximize the use of AI. In order to truly capitalize on all that artificial intelligence (AI) and machine learning have to offer, fraud solutions must implement a combination of four pillars, which Kount has dubbed Real Intelligence: patented, proprietary technology, vast amounts of data, AI to make sense of all of that data and to identify anomalies, and finally, human intelligence. AI by itself is not enough – the key is the addition of the human element to calculate specific tolerance and risk levels for each specific business to provide real intelligence for retailers
- Reduce Manual Reviews. Manual review of orders should be a last line of defense when fighting online fraud. The process is slow, resource intensive, and not scalable for company growth. Plus, making your customer wait for approvals can cost you sales and brand reputation. Automating the transaction review process can eliminate costs and speed up order acceptance while maintaining a high-quality customer experience. With Kount, businesses can reduce the time for a manual review by 90 percent.
- Use Order Linking and Personas. Capabilities like Order Linking and Personas use hundreds of variables to construct a definitive link to online purchase behavior—either directly or indirectly—to help reveal fraudulent activity. How does it work? Kount’s patented technologies such as Dynamic Scoring™, Multi-Layer Device Fingerprinting™, and Proxy Piercer first assess over 200 variables and report in real-time on potential risks. When these variables are compiled and evaluated, a Persona is created. Examples of attributes that make up a Kount Persona are:
- The number of credit cards linked to the Persona. A single Persona may be associated with dozens of credit card numbers issued to different individuals that have been used to make purchases within a short time span.
- The number of email addresses associated with a Persona making a purchase.
- The actual location of the individual device making the purchase as determined through Proxy Piercer technology.
- Discrepancies in the customers self-divulged information and actual information as determined by Multi-Layer Device Fingerprinting information.
- Recognize if the phone number being used is a forwarded number. Fraudsters forward calls from a stolen or compromised account to their own phone.
- Optimize Rules. Every business is different and there is no universal setting for rules within your fraud platform. Using Kount, businesses can uncover hidden insights and optimize performance of your fraud platform. After reviewing specific business goals and objectives, merchants should make sure their fraud platform conducts an analysis of currently active rules and their overall effectiveness to best make recommendations, along with an assessment of future performance gains.