False Acceptance Rate (FAR)

False Acceptance Rate (FAR) measures how often a verification system incorrectly approves the wrong person. 

In identity verification, FAR is used as a biometric performance measure to evaluate how accurately a system distinguishes between genuine users and incorrect matches. It is commonly used when assessing biometric technologies such as face verification, fingerprint recognition, and other authentication methods. 

A lower FAR means that a system is less likely to approve an incorrect identity match. However, achieving a lower FAR usually requires stricter matching criteria, which can increase the chances of rejecting genuine users. 

How Is False Acceptance Rate Calculated?

FAR is calculated by dividing the number of incorrect approvals by the total number of attempts made by users who should not have been accepted. 

The formula is:

FAR = (Number of False Acceptances ÷ Total Number of Impostor Attempts) × 100

For example, if a biometric verification system incorrectly accepts 8 attempts out of 200,000 verification attempts made by unauthorized users: 

FAR = (8 ÷ 200,000) × 100 = 0.004%

Biometric testing standards use performance measures such as FAR and FRR to assess how accurately a system performs during verification.

False Acceptance Rate (FAR) vs False Rejection Rate (FRR)

The biometric systems can make two types of verification errors. FAR and FRR measure different outcomes. 

For example, If a biometric system incorrectly matches one person’s facial features with another person’s identity and approves the verification, it contributes to a False Acceptance Rate.  If a genuine customer is rejected despite providing valid biometric information then it contributes to FRR.

Both measures are used together when assessing biometric system performance. 

What Is Considered a Good False Acceptance Rate?

There is no universal FAR value that works for every biometric application.

The appropriate FAR depends on factors such as:

• Required security level
• Industry risk exposure
• Type of biometric technology
• User experience expectations

For example, a high-risk identity verification process may prioritize reducing incorrect approvals while other applications may place more emphasis on faster user access. FAR should be reviewed alongside other performance indicators including FRR, because biometric accuracy depends on the overall balance between security and usability. However, specific FIDO biometric certification levels use a FAR below 1 in 10,000 with an FRR below 5%.

FAR Threshold and Biometric Accuracy

A FAR threshold is the matching setting a biometric system uses to decide whether a verification attempt should be accepted as a match. The threshold determines how similar two biometric samples must be before the system considers them a valid match.

A stricter threshold can reduce the chance of accepting an incorrect match, but it may also cause genuine users to be rejected if their biometric information does not meet the required matching criteria. The right threshold depends on the purpose of the biometric system, security requirements, and the level of assurance needed. (NIST Face Recognition Technology Evaluation)

Examples of False Acceptance Rate

A false acceptance can happen when a biometric system approves an identity that should have been rejected. 

Here are some scenarios: 

• A person’s facial biometric data is incorrectly matched with another individual’s enrolled identity, and the system approves the verification. 
• Two individuals have similar biometric characteristics, and the system incorrectly identifies them as the same person.
• The matching settings allow a biometric comparison that should not have passed. 

During digital onboarding, a false acceptance could occur when the wrong person is incorrectly approved during biometric verification.

Why FAR Matters in Identity Verification?

FAR helps businesses understand how effectively a biometric verification system prevents incorrect identity approvals.

It is particularly important for businesses and any organizations using biometric checks for:

• Digital onboarding
• Account access
• Financial services
• Fraud prevention

By reviewing FAR alongside other biometric performance measures helps businesses understand whether their verification process provides the right balance between preventing fraud and allowing genuine users to complete verification successfully.