In biometrics, one of the first questions that comes up is about accuracy. It's a complicated issue because a biometric match is never a sure thing - it is a matter of probability. When a phone owner unlocks their phone with a fingerprint, the phone is not 100% sure that the fingerprints match. And this a problem because we want important things to be 100% true. It's just not possible in biometrics (blame math).
There are two types of errors a biometric system can make. A system can erroneously match someone it shouldn’t. This type of error is called a false match. The second type of error is when the system does not match someone who should match, called a false non-match. To understand the accuracy of a biometric system, it is important to understand both of these probabilities. Consider a typical biometric system used to control access to a facility. A false match means allowing someone in when that individual shouldn't be allowed. A false non-match means blocking someone who should be allowed. False non-matches are annoying; false matches are dangerous. Biometric systems can be tuned to optimize one factor over another, but it is a trade-off. If false matches are decreased, false non-matches automatically increases and vice-versa.