Eliminating Friction Is Key; Customers No Longer Have to Trade Experience for Security
Just as the latest approaches to personalizing web content, offers, pricing, and promotions adapt to each customers’ unique preferences and buying history, account control and security must do the same. Customizing security for every online customer eliminates the friction of having the most loyal, VIP-level customers go through the same authentication steps as a new one. Instead of one-size-fits-all account verification, there needs to be a more adaptive approach to managing friction customers experience. And the best place to start is by expanding the dataset used for defining and personalizing adaptive friction approaches by customer, all in real-time. Knowing the user type, device specifics, IP risk, geolocation, custom data, and more can be taken together to define a microsegmentation-based strategy.
One of the more innovative approaches to solving this challenge uses AI and Machine Learning algorithms to customize every e-commerce consumers’ experiences, reducing friction by identifying and segmenting users based on common characteristics. It’s called Kount Control – Account Takeover Protection and what’s noteworthy about this approach is its ability to identify returning customers even if they are logging in from a new location or a new device. Rather than instantly blocking their access, e-commerce businesses can give their customers an appropriate login response, such as step-up authentication or frictionless experience.
Kount Control enables an e-commerce companies’ fraud agents to see the health of the logins and take a quick pulse of the number of blocks and challenges as well as the failed login attempts. They’re also able to see the normal ebbs and flows of a business, which can help analysts identify when something is amiss. The following dashboard is crucial for showing location patterns to analyze logins during specific periods, or even filter on a particular user to identify attempted fraud.
Knowing the patterns of failed login attempts helps identify and stop credential attacks, while also helping to improve user’s login and purchase experiences. What’s noteworthy about Kount’s approach to doing this is how they identify potentially risky IP addresses and feed those to Security Operations while also identifying potential users that are under attack so they can be contacted via customer service outreach. The following is an example of a Kount dashboard tracking and analyzing failed login attempts in real-time.
Millions of online customers changing their behavior at the same time to opt for more time saving and convenience puts a considerable strain on e-commerce and online retailers today. How they choose to react will define the future of e-commerce. Many are choosing to remove the friction that stands in the way of turning occasional customers into the most loyal. And they’re starting with securing online identities and protecting accounts from takeover control. Once state by state stay at home orders are lifted, e-commerce sales may stabilize at a lower growth rate than they are today. Yet, the behavioral changes are already in motion to completely change the retailing landscape and commerce overall for years to come.