Should all Micro-Credit Banks Use Fingerprint Biometrics Banking Technology?

Perhaps foreshadowing a future shift for micro-credit banks across the globe to start using biometrics for customer identification, we distributed a News Release today announcing that ASMAB, a micro-credit bank in the country of Benin, has started to use fingerprint biometric banking technology for customer identification. The genesis for ASMAB’s decision to start using fingerprint biometrics was the widespread fraud and corruption that plagued their business, specifically customers falsifying their identities. These problems were undermining customer confidence in their process so ASMAB (with help from HPC Informatique, a technology solutions provider) decided to incorporate fingerprint biometrics to identify customers, eliminating fraud and corruption in their system and helping to secure consumer confidence.

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Iris Recognition vs. Retina Scanning – What are the Differences?

In biometrics, iris and retinal scanning are known as “ocular-based” identification technologies, meaning they rely on unique physiological characteristics of the eye to identify an individual. Even though they both share part of the eye for identification purposes, these biometric modalities are quite different in how they work. Let’s take a closer look at both and then explain the similarities and differences in detail: Retinal Scanning: The human retina is a thin tissue composed of neural cells that are located in the posterior portion of the eye. Because of the complex structure of the capillaries that supply the retina with blood, each person’s retina is unique. The network of blood vessels in the retina is so complex that even identical twins do not share a similar pattern. Although retinal patterns may be altered in cases of diabetes, glaucoma or retinal degenerative disorders, the retina typically remains unchanged from birth until death. (Source: Wikipedia) ...

False Rejection Rate – What Does It Mean And Why Should I Care?

False reject rate is a statistic used to measure biometric performance when operating in the verification task and it usually calculated as the percentage of times the system produces a false reject. A false reject occurs when an individual is not matched to their own existing biometric template. For example: John claims to be John, but the system incorrectly denies the verification. This can be particularly frustrating for an end user who knows that they are enrolled in the system and should be recognized and verified, but for some reason the system is incorrectly rejecting their scan. This can cause unnecessary logjams, affect service, frustrate staff and negatively impact productivity.

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