Mobile Device Fraud: Prevent the Headache

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Mobile Device Fraud: Prevent the Headache

By Aaron Kline - 02/21/2014
Last year might end up being remembered as the year that mobile commerce came of age with mobile devices becoming a suitable way to shop online. According to IBM, mobile traffic during the 2013 holiday season made up 48% of all online traffic, an increase of 28% from the prior year, while mobile sales made up 29% of overall online sales, a 40% improvement from 2012.
 
While mobile shopping is an increased convenience for customers, it can lead to greater fraud risk for online retailers as the proliferation of mobile devices also makes it easier for fraudsters to commit crimes. Fraudsters continue to target online retailers because they have access to customer credit card information that fraudsters seek; most mobile consumers store this information in online retail accounts, making it easier for fraudsters to steal.
 
As a result of this mobile device threat, online retailers are faced with the task of using advanced methods to minimize risk without hindering the customer experience. While many companies have focused on developing rules-based tools to fight fraud, it is only one piece to solving the fraud puzzle. In order to more effectively fight fraud, online retailers must look for other ways to authenticate consumers.
 
A powerful approach to authenticating consumers is to combine device authentication with the relevant personal identifiable information (name, phone number, IP address, e-mail). Applying predictive analytics to this information enables merchants to generate a greater level of insight into each customer. Device data can be collected during the online experience without the consumer having to enter information. Personally identifiable information is gathered through the checkout process. Armed with these two approaches, the merchant can create a safe, well-lit, friction-free online store. With the holistic approach at the point of a transaction, online retailers possess comprehensive information for each transaction and can receive real-time insights into transaction risk.
 
What can an online merchant do with these insights? It can take three courses of action:
  1. If it is considered low risk, it can automatically clear the transaction;
  2. If it is considered somewhat risky, the merchant can flag a transaction for a manual review;
  3. If it is considered high risk, it can manually review, contact the customer, or simply shut down the transaction.
With these predictive risk assessments, online retailers have accurate, real-time information on any transaction to help them more effectively determine fraud risk. They are also able to maximize sales conversion by reducing false positives generated by standard models. Best of all, this can all be accomplished while providing a friction-free mobile customer experience.
 
Aaron Kline is the director of eCommerce at ID Analytics, a provider of consumer risk management with patented analytics and real-time insight into consumer behavior.