In recent years, cybercrime has continued to increase at an alarming rate, moving banks, e-retailers, credit bureaus and other financial institutions to look beyond traditional, static authentication and fraud prevention techniques to more robust and dynamic solutions. Behavioral biometrics has therefore emerged as a breakthrough technology that analyzes an array of human interactions between a device and an application, to prevent identity theft and fraud. As a new technology, there are many questions on how to get started with behavioral biometrics. Here are 3 things you need to know:

1. “Behavioral What?”

“Behavioral biometrics” sounds like “Behavioral analytics”, but they are not the same. Behavioral analytics typically look at past patterns of a user within a website or from a transactional perspective – where do they go on a network, what do they buy, what do they click on. On the other hand, behavioral biometrics is looking at HOW a user does certain things with a device or on an application in ways to detect anomalies and prevent fraud in real-time. Behavioral biometrics is used to prevent new account fraud and account takeovers, while behavioral analytics are traditionally used for marketing but can provide insights to network activity for security purposes.

2. One Size Does Not Fit All

Like other technologies, behavioral biometrics are not a one size fits all. One of the key aspects that distinguishes BioCatch as the market leader in behavioral biometrics is its patented “Invisible Challenges™. Invisible Challenges refer to tests that are invoked into an online session without the user’s knowledge, but that elicit subconscious responses that can be used to distinguish a fraudster from a legitimate user. This powerful mechanism represents the latest generation of fraud prevention tools, that addresses the weakness of traditional approaches that rely on malware libraries, two-factor authentication, device ID and other means that the sophisticated fraudsters of today have figured out how to circumvent.

3. Lab Tests are No Substitute for Real-World Experience

There are not many players today with real-world, highly scalable experience and combining that with a deep understanding the way fraudsters behave is key to creating automated, machine learning approaches to fraud detection and prevention. BioCatch’s data science and machine learning teams have created powerful tools to detect fraudulent activity, even for first-time users. Recent success stories include: (1) Preventing a vishing attack where the fraudster pretended to be a bank representative, calling a customer which he knows all the details about, and trying to deceive him into making transaction; (2) Thwarting an attack by fraudsters who tricked a victim into entering his credentials, login to the system, and willingly hand over the session through remote access. To learn more about how behavioral biometrics are used to prevent fraud, download our white paper.

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