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When It Comes To Digital Body Language, Fraudulent Bluffs Fall Short

Poker has its “tells” — those tics and behavioral body language nuances that tip others at the table to the strength of a carefully observed player’s hand.

As for eCommerce? Well, online consumers also have their own forms of “digital body language,” Neuro-ID CEO Jack Alton told Karen Webster. Converting the taps, swipes and types as individuals navigate sites can be converted into data that helps merchants stop fraud, yes — but also can help them increase conversion rates, too. Leveraging behavioral analytics, he said, helps ID legitimate buyers at scale.

At a high level, it’s a matter of flipping the script — endeavoring to let the good guys in rather than just trying to catch and stop the bad guys.

Merchants could use the help, he said, as their eCommerce conversion rates have been stuck in single-digit percentages. Those rates are kept low by the fact that the fraud systems that businesses have in place, said Alton, are over-tooled and perhaps overly onerous. They rely on static, historical data to find red flags that signal bad actors are in the mix.

With the use of traditional models, he said, “the fear of fraud, and the inability to see the behaviors of genuine customers have left many firms to a ‘default position’ where they ‘ratchet down’ fraud and risk rules to stay within the chargeback ranges, or default ranges, that are consistent with where the business wants to go.”

The false-positive problem is a significant one in eCommerce, he told Webster. As many as 40 percent of the false positives (it’s an average, he said, culled from a range of 30 percent to as much as 50 percent) logged by firms seeking to combat fraud with outright declines, or as they step up verification and other challenges, are in fact, genuine customers.

The ripple effect is decidedly punishing. The conversion rates are low, as noted, but companies also lose future revenue contributions. The customers experiencing those false declines are more likely than ever to walk — as found in one recent PYMNTS tracker, one-third of consumers have said that they would take their business elsewhere after a single negative experience.

Read more: Deep Dive: How Behavioral Analytics Can Boost Conversion Rates By Reducing Customer Friction

Against that backdrop, maintained Alton, the same information and examination that is tied to Neuro-ID’s behavioral analytics offerings can use the tells tied to the hesitations and swipes to pinpoint just where the pain points lurk for the consumer as they choose to abandon their digital journeys out of frustration.

Alleviating those pain points, he said, represent “biggest opportunity we have to digitally transform,” commerce.

As he told Webster: It may be easy to fake facts — to leverage the personally identifiable information (PII) floating around on the web to fool traditional fraud-fighting systems. It’s much harder, well-nigh impossible, to fake behavior.

With a nod toward how the company’s Javascript, which sits behind online forms, operates, he said data is captured during the user session that is then delivered to the cloud. Attributes gleaned through the user’s interactions (without capturing PII) gives the enterprise actionable insight into their customer journeys.

In the bid to stop the fraudsters, the use of behavioral analytics to determine intent can separate the good customers from those who are pretending to be legitimate customers.

As Alton noted, the company examines how individuals online “interact” and input information spanning names and addresses — the key identifiers that would be so automatic they could be considered muscle memory. No one makes mistakes when inputting those details into a data field. Pauses here, repeated keystrokes, etc., raise alarms that actions being performed are inconsistent with genuine behavior.

“We watch the consumers,” he said “that have ‘genuine’ behaviors — as they interact with the data as though it really is ‘theirs’ coming from long term memory. And we look at others that are interacting with data that are not their own. Then we start to segment those customers into those who are genuine versus fraudulent.”

See more: Behavioral Analytics Pulls Double Duty On Fraud Prevention, Customer Conversion

Data gleaned from more than 200 million online customer interactions, he said, means that, in Alton’s words, “We’re comparing you versus you, you versus the crowd, and then you versus known bad actor —all simultaneously.” And proactively, as well, which means that companies are alerted as the fraud is being attempted, a marked advantage over trying to mitigate damage after it’s done.

Drilling down into what has been termed by Neuro-ID as “neuro attributes” can help battle the emerging waves, and changing profiles, of the fraudsters themselves. Alton noted that bot attacks are becoming more prevalent. He recounted how one Neuro-ID customer, a card issuer, was able to use the behavioral platform to stop 40,000 bot attacks in a single week.

Fixing The Customer Journey 

The behavior as a service platform also has the advantage of helping merchants and other corporates see where the confusion or frustration lies on the digital journey itself — right down into the data field level. It’s a way to use the digital interactions of online consumers, quantify them and, in a scientifically data-driven way, reduce the frictions on those consumers that the genuine customers so badly want to convert.

“It’s like a light turning on where they now see the root cause of abandonment, friction, or a positive customer journey,” he said.

That level of granular detail, he said, can steer firms to the insight that some of the things they are doing to improve conversions are actually causing issues that spur those same users to abandon sites and transactions. The pre-fills, the auto-fills may be designed to make things easier, but the “tells” that come across — as users, say, have to put a personal email where a business email is automatically being loaded — can steer firms toward what needs to be fixed for the individual user in an individual session.

A broad swath of executives, he said, “can see the core underlying behaviors and see what questions are necessary to ask.” Along the way, risk management makes the leap from being a cost center to a revenue driver as firms have the insight to pull back on friction.

As he noted to Webster, “We started with fraud and risk, but now we’ve definitely moved over to product and heads of digital experience. And we’re seeing massive traction there. With this data they can systematically reduce friction, which doubles or triples conversion.”

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