Hedging Risk in Biometric Identification Management Deployments

As biometric identification management deployments continue to evolve around the world, the scope and complexity of administering these projects continue to grow as program administrators begin to expand the technology’s reach to more and more segments of society. A technology once used exclusively by government entities mostly in a military capacity has expanded to include virtually all classes and cultures thanks in large part to advances in system inefficiencies, lower costs and wider acceptance and understanding of the benefits by the public.

The intricacies and conditions of biometric identification deployments from initial set up to enrollment to identification/verification and the ever-present push to achieve near 100% identification accuracy has been a key motivator for biometric identification management vendors who design and build the software and hardware that power deployments. There is little doubt that biometric systems have become more user-friendly, customizable, ergonomic, and efficient, however, end users don’t assess the effectiveness or develop opinions on the use of biometrics based on these factors. They are much more in tune with the basic tenet of just about any piece of technology they come in contact with — does it work and do I trust it? Faith and trust in a biometric identification system are largely defined by the ability of the technology to accomplish what it promises and that is to accurately identify individuals, no matter what the conditions.

End users expectations are that biometric identity management systems will be able to identify them regardless of the condition of their own physiological attributes or the environment where the system is used. After all, the effectiveness and security of a biometric system hinges on its ability to enroll as many eligible end users as possible, and accurately identify them on subsequent use of the system. Unfortunately, limitations in the ability of certain biometric hardware modalities to effectively capture individual biometrics due to problems like skin integrity, or climate, as well as the use of unimodal (biometric systems that comprise one hardware modality) systems for larger scale deployments, raise the risk that the technology will not perform as expected.

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