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Behavioral biometrics vs. behavioral analytics in fraud prevention

Author: Tiffany Staples


Biometrics, behavioral biometrics, behavioral analytics — while these words may spark visions of a futuristic fantasy movie, biometric technology has been a reality for years. What began in the 1960s with semi-automated facial recognition has evolved into a booming industry that delivers new technologies to fight fraud and improve identity verification across the digital universe. To find the best fraud prevention solution, you need to understand the differences between these options.

As technology continues to advance, businesses can struggle to decide on a fraud prevention solution. Aside from the different fraud types to account for (transactional, account takeover, identity theft, etc.), there seems to be a new fraud-fighting technology hitting the market every other day. Two technologies in particular — behavioral analytics and behavioral biometrics — have gained a lot of attention in the fraud prevention industry. But they’ve also stirred up a lot of confusion. Let's break it down:

Biometrics 101

Biometrics are physical characteristics used to identify a person. The most common types of biometric identifiers are voice, iris, fingerprint, facial profile, and palm/finger vein patterns.

From a technology perspective, biometric authentication is a security process that uses a person’s physical traits to verify their identity. Popular authentication methods include fingerprint scanners, iris scanners, and facial and voice recognition systems.

Biometric security is becoming common in everyday life — mobile phones unlock with the touch of a thumb, travelers scan their eyes and fingerprints to get through airport security, and certain devices can be triggered by a person’s voice. But when it comes to fraud prevention, biometric authentication faces many challenges. The rise in AI, digital voice cloning, and deepfake technology is making it easier for fraudsters to mimic and replicate real humans. Cybercriminals are also becoming better at stealing biometric data which, once stolen, is nearly impossible to change. If someone steals your fingerprint, you can’t simply go out and buy a new one. Biometric technology itself is also prone to data breaches. So, while biometrics are helpful in the fight against fraud, they’re not a perfect solution on their own.

Behavioral biometrics 101

Behavioral biometrics identifies measurable patterns in human activities. Instead of using a fingerprint, face, or iris (physical biometrics) to identify a person, behavioral biometrics looks at a person’s unique behaviors and actions across the digital landscape. Think of it as digital body language.

Types of behavioral biometrics include:

  • Mouse dynamics (right or left-handed, speed and accuracy, duration of movements)
  • Keystroke dynamics (speed, pressure, rhythm)
  • Voice and speech recognition (inflections, gender, cadence)
  • Gestures (pinches, swipes, zooms)
  • Eye tracking (uses cameras to track eye movement and where it focuses on screen)

In fraud prevention, behavioral biometrics are used to either confirm identity or detect anomalies in a user’s behavior. From a sudden change in typing speed to a shift in how a person uses their mouse, it uses multiple data points to spot patterns and distinguish between a legitimate user versus a fraudster or bot. Many companies rely on behavioral biometrics to verify the identity of visitors and customers, especially when they’re attempting to open a new account or change an existing profile.

Behavioral analytics 101

“Analytics” is a familiar word: it’s a field of computer science that turns raw data into insight so people can make better decisions. Behavioral analytics follows the same concept but focuses on revealing patterns in behavior. It’s the process of collecting and analyzing user data to understand and predict a person’s online behavior. Studying a user’s interactions on a website or app — what they click on, the time they spend on a page, how they search or filter, etc.— reveals insight into their interests. This information can then be used to predict trends, understand preferences, and improve the user experience. It can also be used to spot fraud.

Types of behavior that can be tracked with analytics include:

  • Page interactions
  • Site navigation
  • Search habits
  • Preferences
  • Purchase history

In fraud prevention, behavioral analytics are great for spotting transactional fraud. Machine learning and automation can analyze large sets of data quickly to reveal anomalies that deviate from normal user behavior. For example, credit card providers can establish a baseline behavior for a customer based on their habits like purchase and browsing history. When something unusual happens (the customer buys a cappuccino in Chicago and, 10 minutes later, fills up their gas tank in Paris), behavioral analytics can spot the fraudulent activity. The bank can then notify the customer of the suspicious activity, stop the transaction, or freeze the card.

Because it analyzes large sets of data, behavioral analytics can catch and flag questionable actions on a broad scale. It can also help to predict future actions.

What's the best fraud solution for your business?

Now that you understand the differences between the technologies, which solution will best meet your fraud prevention needs? The answer isn’t black and white — it depends on your use case and what you’re trying to accomplish. Here’s a quick summary:

Biometrics are specific, tangible characteristics used to validate a user’s identity. Fingerprints, facial features, and voice are the most common.

  • Benefits: Quick identity verification, two-factor authentication (2FA), ease of use.
  • Keep in mind: Biometrics data can be stolen or replicated, and it’s almost impossible to recover when that happens.

Behavioral biometrics uses specific behavioral traits to identify a person. From typing patterns to mouse movements, behavioral biometrics help to build a comprehensive identity profile that can be used to compare every interaction. It enables organizations to compare “me vs. me” for more accurate identity verification.

  • Benefits: Identifies and prevents all types of fraud, can't be replicated or stolen
  • Keep in mind: Behavioral biometrics focuses on unique behaviors that can’t be copied. It’s future-proof and can catch new types of fraud because it’s based on a behavioral profile instead of a finite set of attributes or transactions. Behavioral biometrics work hand-in-hand with other fraud solutions to elevate your fraud defense strategy.

Behavioral analytics examines behavior patterns. How consumers interact with a website creates a particular pattern of expected behavior. It connects a user’s behavior to their intention, not their identity. Behavioral analytics compare "me vs. fraudster" very effectively.

  • Benefits: Spots transactional fraud; complements behavioral biometrics
  • Keep in mind: Behavioral analytics relies on historical data to identify patterns. This means it typically can’t catch new types of fraud because a new threat won’t yet have a pattern. Incomplete or inaccurate data can also skew analytics and cause false positives, so a comprehensive data platform is essential to success.

When it comes to choosing the right fraud solution for your business, it’s important to remember that fraud and cyber-attacks are becoming more common, sophisticated, and expensive. While each of the technologies mentioned has specific strengths, leveraging all three in unison, with one end-to-end platform, is the most efficient way to fight all types of fraud.

The best approach to keeping fraudsters at bay is a multi-layered fraud defense solution that combines traditional identity verification methods with advanced fraud detection. Technology that leverages real-time data capture, behavioral biometrics, AND behavioral analytics is the best way to truly get ahead of evolving fraud.


Ready to beat creative fraudsters at their own game?

Digital fraudsters are an innovative bunch — they continuously adapt their techniques to outsmart current fraud technology. The key to winning the battle against creative fraudsters is to move from fraud detection to prevention.  

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