TL;DR
Behavioral biometrics use invisible, passive signals — like how you type, scroll, or hold your phone — to continuously verify your identity without adding friction. Unlike passwords or one-time codes, these patterns are extremely difficult to steal or replicate, making them a powerful tool for banks, retailers, and digital platforms to prevent fraud, stop account takeovers, and meet anti-money laundering compliance requirements.
How behavioral biometrics help prevent fraud
Behavioral biometrics analyze behaviors and physical activities to help prevent and identify fraud.
Behavioral biometrics can recognize how a person acts online, how a user interacts physically with their computer or smartphone (e.g., how the phone is held or keystroke patterns), and help determine that a person really is who they say they are. These biometrics can help to prevent identity theft, as they can tell the difference between an imposter and a real user.
What are behavioral biometrics and how do they work?
Every user has a unique way of accessing and interacting with a computer, both cognitively and physically. Behavioral biometrics analyzes these patterns to determine what a user's online and digital profile looks like. Behavioral biometrics can use the following:
- Keystroke uses and patterns
- Pressure or location touched on a touchscreen
- How a user holds and moves their smartphone
- Scrolling behavior
- Mouse movement patterns and speed of use
Every user interacts with a computer in specific ways. Behavioral biometrics can work in the background to pick up on these patterns and determine that a user is who they say they are.
How can biometrics prevent identity theft?
The Federal Trade Commission (FTC) reports that there were well over 2 million reports of fraud from consumers, with imposter scams and online shopping fraud topping the list of fraudulent activities. The use of biometrics can secure online transactions and help to prevent identity theft.
A signature can be forged, and passwords and login credentials can be stolen. But it is much more difficult to mimic a user's direct actions and biometric patterns. Programs scanning for behavioral biometrics are often unobtrusive and unnoticed by the end user. They are running in the background to provide a host of data to help identify a user.
Much of the security software being used by retailers and banks today has behavioral biometrics built in to protect against fraud and identity theft.
Why are behavioral biometrics more effective than standard security measures?
Systems that use behavioral biometrics do not require any extra steps for users, and can be harder to get around than standard security measures.
| Security Measure | Vulnerability | Behavioral Biometrics Advantage |
|---|---|---|
| Username & Password | Can be stolen via malware or identity theft | Behavioral patterns are unique and cannot be easily replicated |
| Multi-Factor Authentication (MFA) via SMS | Phone numbers can be hacked or SIM-swapped | Adds a passive layer of security even if credentials and phone are compromised |
| Standard login screen checks | Only verifies identity at login | Continuously monitors behavior throughout the entire digital session |
Why standard MFA alone isn't enough
Standard security measures often use a multi-factor authentication (MFA) process, for instance. Banks require users to log in with a username and password, and then receive a text to fully access the account. But both phone numbers and login credentials can be hacked and stolen through malware and identity theft.
On top of this, many users do not want to go through extra steps to access their account. With behavioral biometrics, even if the user's login information and phone number have been breached, there is still an extra layer of security. A cybercriminal is much less likely to know exactly how a user interacts with their smartphone or computer.
How behavioral biometrics catches impostors
Behavioral biometrics can help to identify when someone who is not the user is trying to gain access to these accounts. Behavioral biometrics is extremely accurate in identifying individuals specifically.
How do behavioral biometrics support anti-money laundering (AML) compliance in banking?
Financial firms and banks are required to comply with anti-money laundering (AML) rules and regulations under the Bank Secrecy Act. This means that they must work to ensure that users are legitimate and the money is authentic and not gained through suspicious activity or fraud.
How mobile banking growth increases fraud risk
Behavioral biometrics can help banking companies to be compliant while also adding an extra layer of security for consumers. Digital banking and the use of mobile banking apps have exploded due to the COVID-19 pandemic and overall convenience.
The Federal Bureau of Investigation (FBI) warns that this also increases the risk for cybercrimes and exploitation via these platforms. Banks and financial institutions are increasingly recognizing that spending money on AML compliance and fraud defense mechanisms is necessary.
Where are behavioral biometrics used in practice?
There are three main instances where behavioral biometrics can protect individuals and companies.
- Protection during account opening: Even if a user is not already a customer with a specific firm or banking institution, behavioral biometrics can still help to determine if a user is legitimate. Companies employing behavioral biometrics can help to decipher criminal and fraudulent activity by recognizing "bad" behaviors.
When a legitimate user is filling out information in credit card application forms, for example, they already know their information and can input it with a certain amount of speed. Cybercriminals must often find or look up this information, which can cause a lag in the input time. Behavioral biometrics can pick up on this time difference and help to spot criminals attempting to open fraudulent accounts.
- Protecting against account takeovers: Behavioral biometrics go beyond just the login screen and can continue to protect a user during the entire time they are logged in or inside of a digital session. Through behavioral and cognitive biometrics, any fraudulent or suspicious activity can be flagged and recognized before the cybercriminal can access or transfer funds, for instance.
Users tend to stick to predictable patterns. Behavioral biometrics can determine when something is different, which sends up a red flag. For example, if a user always scrolls with a mouse a certain way or accesses their account via a specific platform, but then changes it up by using a touchscreen or different method, behavioral biometrics can spot this and ask for additional verification.
- Detecting social engineering scams: Social engineering scams are very common, and they use various methods to entice sensitive information from users. Phishing scams often encourage a user to click on links containing malware or provide login credentials and passwords through what seem to be legitimate and reputable sites.
Behavioral biometrics can help to recognize that a user's pattern and digital access methods are different. This can stop some of these scams before they really get started.
With more and more sensitive and financial information being stored and accessed online, it is increasingly important to take steps to protect both users and institutions against fraud and cybercrime. Okta employs some of the latest evolving technology to ensure privacy and security.
Frequently asked questions
What types of behaviors do behavioral biometrics actually measure?
Behavioral biometrics capture a range of passive signals, including keystroke patterns, how a user holds and moves their smartphone, touchscreen pressure and tap location, scrolling behavior, and mouse movement speed and patterns. Together, these signals build a unique digital profile for each user.
How are behavioral biometrics different from multi-factor authentication (MFA)?
Standard MFA typically requires an extra step — such as entering a code sent via text message — which can be inconvenient and is still vulnerable to SIM-swapping or credential theft. Behavioral biometrics work passively in the background throughout an entire session, adding a layer of security that doesn't require any action from the user and is far harder for a cybercriminal to replicate.
Can behavioral biometrics detect fraud during account opening, not just after login?
Yes. Even for new customers, behavioral biometrics can flag suspicious activity during account creation. For example, a legitimate user filling out a credit card application typically inputs their own information quickly, while a fraudster who has to look up stolen details will show a noticeable lag — a pattern that behavioral systems can detect.
How do behavioral biometrics help banks meet anti-money laundering (AML) requirements?
Financial institutions are required under the Bank Secrecy Act to verify that users and transactions are legitimate. Behavioral biometrics help banks satisfy these AML obligations by continuously authenticating users and flagging anomalous behavior, reducing the risk of fraudulent or money-laundering activity slipping through.
What happens if a legitimate user changes how they interact with their device?
Behavioral biometrics systems are designed to detect deviations from a user's established patterns. If a genuine user switches from a mouse to a touchscreen or accesses their account from an unusual platform, the system may flag this change and prompt additional verification — helping to distinguish between a real user adapting their behavior and a potential account takeover.
Are behavioral biometrics systems noticeable to the end user?
Generally, no. These programs run silently in the background and are designed to be unobtrusive. The end user typically does not notice them operating, which is one of their key advantages over traditional security measures that require active participation, such as entering one-time passwords.
References
New Data Shows FTC Received 2.2 Million Fraud Reports From Consumers in 2020. (February 2021). Federal Trade Commission (FTC).
Banks and Retailers Are Tracking How You Type, Swipe and Tap. (August 2018). The New York Times.
Behavioral Biometrics is the Future of User Authentication. (May 2019). Forbes.
Anti-Money Laundering (AML). (2021). FINRA.
Does the Combination of AI. Biometrics Hold the Key to Stopping Identity Theft (and Money Laundering)? (August 2020). TechWire Asia.
