False Reject Rate (FRR)

False Reject Rate (FRR) definition

Probability that the system fails to detect a match between the input fingerprint template and a matching template in the database. It measures the percent of valid inputs which are incorrectly rejected. It is sometimes denoted as False Non-Match Rate (FNMR).

What is False Reject Rate?

The False Reject Rate (FRR) is the ratio of the number of false rejections divided by the total number of transactions. FRR is calculated by dividing the number of false rejects by the total number of transactions. When you have a low FRR, it means that your biometric system is rejecting fewer people than it should be.

What is the difference between the False Reject Rate (FRR) and False Accept Rate (FAR)?

The false reject rate (FRR) measures how well your system can identify legitimate users. It is the percentage of times that a user is incorrectly rejected by your system. The false accept rate (FAR) measures how well your system can identify imposters. It is the percentage of times that an imposter is incorrectly accepted by your system.
The number of false acceptances (FAR) and the number of false rejections (FRR) are directly related. As one goes up, the other will go down. The point at which these two lines intersect is known as the Equal Error Rate (EER). This is where the percentage of false acceptances and false rejections is the same.

How do FAR and FRR affect security levels?

The false accept rate (FAR) and false reject rate (FRR) are two important metrics that can be used to evaluate the performance of a biometric system. These rates are typically configured in software by adjusting the system’s threshold value. As you can see, the FAR and FRR will affect the security level of a biometric system. This means that as you increase or decrease these rates, the amount of usable authentication attempts will decrease or increase respectively.
A high FAR means that the system is more likely to incorrectly accept an unauthorized user, which can compromise the security of the system. A high FRR means that the system is more likely to incorrectly reject an authorized user, which can cause frustration and lead to a drop in productivity.
A low FAR with a low FRR indicates a high-security level. When setting threshold values for a given system, it is important to find a balance between the false acceptance rate (FAR) and the false rejection rate (FRR). The compromise between security and usability should be reflected in the choice of threshold.

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KYC – Online Customer Onboarding and Identity Verification Use Case

eKYC

Online Customer Onboarding and Identity Verification