Given the nature of fraud that merchants are seeing, behavioral biometric security is receiving more attention. In the past few years, the types of fraud merchants saw were different from those they see today. Account takeover, bot activity, social engineering, and remote payment fraud are growing concerns for many merchants. Yet merchants also need to maintain high conversion rates—blocking fraudulent transactions without adversely affecting the customer experience is a difficult balancing act.
Behavioral biometrics offers a powerful solution for detecting payment fraud without disrupting legitimate customer activity. By focusing on the interaction a customer has with a device and the session they are performing, merchants can gain insight into customer behavior. This includes data such as typing behavior, swipe gestures, mouse movement, and device handling. By incorporating this data into the fraud detection and prevention process, merchants can shift focus from a product category to an additional risk signal.
What Behavioral Biometrics Means in Payments
The easiest way to think about behavioral biometrics is that it adds a form of identity to the payment risk decision. According to the FFIEC, behavioral biometrics software analyzes how a customer uses their phone or device to complete a transaction. The Federal Reserve takes a slightly different view of the technology, stating that the software analyzes a customer’s behavior throughout the transaction and compares it to the behavior profile obtained when the customer set up their digital banking and payment account. Since most payment fraud occurs at various stages of the transaction, being able to view the activity that occurs during the transaction is extremely useful.
Why Behavioral Biometrics Matters More for Payment Fraud
The fraud environment is increasingly automated and disguised. The Federal Reserve’s recent guidance on account takeover makes clear that automated tools are becoming easier to use, and AI is making social engineering attacks more convincing. These dynamics make it increasingly difficult for payments teams to use rules engines alone to combat fraud in card-not-present transactions.
In this environment, behavioral biometrics becomes even more important. Instead of trying to create rules engines that can identify fraudulent transactions, behavioral biometrics can answer a different question. Rather than asking whether a transaction looks okay on paper, behavioral biometrics can assess whether the behavior within the transaction aligns with what a human is expected to do. According to the Federal Reserve, behavioral biometrics is highly effective at detecting and preventing fraud and should be used within a broader authentication strategy.
Best Practices for Behavioral Biometrics in Payment Security
The most important best practice for behavioral biometrics in payment security is that it is just one layer of the overall control model. The National Institute of Standards and Technology (NIST) does not recognize biometrics as an authenticator on its own and specifically requires that they be used as part of a multi-factor authentication process that also includes a physical authenticator. While this speaks to biometrics in general, the concept remains applicable to payments.
The second-best practice is governance. The Federal Reserve outlines some concerns regarding privacy and compliance with behavioral analytics. The resulting false-positive rates can be significant if the systems do not properly distinguish between authorized and unauthorized activity.
What Leading Behavioral Biometrics Solutions for Fraud Prevention 2025 Had in Common
The phrase leading behavioral biometrics solutions for fraud prevention 2025 sounds like it should refer to a list of companies. What matters more is what the best solutions for merchants had in common. The answer is orchestration. Beyond simply monitoring a user’s taps and keystrokes, the best solutions combine a variety of data to help merchants make better decisions. This was clear from the guidance from the Federal Reserve, Visa, and Mastercard.
The other shared trait is intelligent friction. Mastercard says it wants to make it easy for genuine customers to get approved while adding friction to actions that pose a higher risk of fraud. For example, Visa says it wants to reduce the number of false positives in its fraud detection systems.
Where Behavioral Biometrics Actually Fits in the Payment Stack
At account creation
Behavioral biometrics can help to detect synthetic or otherwise suspicious account creation activity before the account is ever used. The FFIEC guidelines specifically state that using reliable means of verifying the identity of an account applicant can help to prevent fraudulent and synthetic identities from being created and used.
At login and account recovery
Because many forms of online account takeover attempt to take place during login and password recovery, this is one of the most natural places to implement controls for behavioral biometric online fraud. The Federal Reserve specifically states that incorporating device risk information as part of an account takeover prevention strategy is one of the most effective ways to reduce the risk of account takeover.
At checkout before authorization
Even prior to the authorization of the card, behavioral biometrics can be used to help decide whether a transaction should proceed as normal, be challenged, or sent to a stronger review process. The Federal Reserve notes that using behavioral biometrics can help to prevent bots from authorizing transactions, as well as provide enhanced controls prior to reaching the 3DS authorization step.
During authentication and step-up
Behavioral biometrics works best within a risk-based authentication framework. Both EMVCo and Mastercard note that incorporating behavioral biometrics into the authentication process allows the system to more seamlessly and effectively prevent fraud and handle higher risk scenarios.
After authorization, before fulfillment
Not all decisions related to fraud prevention occur at the time of the authorization. By observing the behavior after authorization, merchants are able to make decisions regarding the release of goods. This is especially useful for high-risk product categories including digital goods and gift cards.
On alternative rails and faster payments
The utility of behavioral biometrics is not limited to combating card fraud. The Federal Reserve specifically notes that incorporating behavioral biometrics as an additional signal to detect scams and fraud in digital payments will be especially important in the context of instant and faster payments. In a future with more account-to-account and real-time payments, behavioral biometrics and risk-based signals will be even more valuable to the payment ecosystem.
FAQs
Q: What is behavioral biometric security in payments?
A: This refers to the use of data from the interaction during a session to help determine whether the individual using the account is legitimate. This data is used as a signal to detect fraud in the payment process rather than as a replacement for the other security measures in place.
Q: Can behavioral biometrics stop behavioral biometric online fraud?
A: Unfortunately, no. While this is a helpful tool for detecting certain types of fraud, the Federal Reserve and NIST both suggest that behavioral biometrics should be used as part of a layered protection rather than as the only form of protection merchants use.
Q: What are the best practices for implementing and using behavioral biometrics in payment security?
A: The best practice would be to ensure that behavioral biometrics are used in conjunction with other security controls. They should be used throughout the customer’s payment session, not just at checkout. Additionally, merchants must also determine which decisions will use the behavioral biometric signals.
Q: What are the factors to consider when evaluating the leading behavioral biometrics solutions for fraud prevention in 2025 and beyond?
A: While the leading solutions may use different terminology, the best solutions will combine this technology with other signals to determine if there is fraudulent activity. Determining how this improves the outcome of fraud decisions is more important than the terminology used to describe the capability.
Conclusion
Behavioral biometrics will not replace the rest of your fraud prevention efforts in payments. Instead, it adds a new level of usefulness when evaluating whether a session is a real customer session. This is especially helpful for digital transactions, as the fraudsters can get the credentials and still pose as the customer in question.
For merchants, behavioral biometric security should be thought of operationally. It should build on the fraud prevention system you already have in place. The goal is not to create a more futuristic fraud prevention process, but to streamline and improve the current one.
Sources
- FFIEC. “Authentication and Access to Financial Institution Services and Systems.” Accessed March 2026.
- Federal Reserve Banks, FedPayments Improvement. “Authentication Fraud Mitigation Approaches, Key Findings and Recommendations.” Accessed March 2026.
- Federal Reserve Banks, FedPayments Improvement. “Digital Defenders: Leveraging Risk Signals to Help Combat Fraud and Scams.” Accessed March 2026.
- Federal Reserve Banks, FedPayments Improvement. “Online Authentication to Mitigate Fraud.” Accessed March 2026.
- Federal Reserve Banks, FedPayments Improvement. “Account Takeover Fraud: A Persistent Threat.” Accessed March 2026.
- Federal Reserve Banks, FedPayments Improvement. “Toolkit Module 3: Scam Prevention and Detection.” Accessed March 2026.
- NIST. “Digital Identity Guidelines: Authentication and Authenticator Management.” Accessed March 2026.
- EMVCo. “EMV 3-D Secure.” Accessed March 2026.
- Mastercard. “Mastercard Transforms the Fight Against Scams With Latest AI Tech.” Accessed March 2026.
