ID R&D passive liveness solution tackles biometric bias with new release
ID R&D says its new passive liveness detection product, IDLive Face 1.18, is built with algorithms that help close the gap on face biometrics bias across genders, ages and ethnicities.
The biometrics and liveness technology company said in an announcement that the release of the product, which is already being adopted by a growing number of customers in 38 countries, is part of its inclusive development policy which seeks to, among other things, address the issue of AI bias among demographic groups.
ID R&D said coming up with the new model for liveness detection with high accuracy required investing in unbiased biometric data collection and classification which will help it better tackle the industry’s AI bias problem.
The company also noted the exponential growth of its IDLive Face passive biometric liveness solution which, it said, now facilitates millions of passive liveness checks every month. ID R&D added that it was important its products are based on inclusive data sets so that they can prevent discrimination given that liveness detection is increasing become a part and parcel of identity verification, especially in the financial sector.
Alexey Khitrov, president of ID R&D, praised the solution, saying, “IDLive Face is a breakthrough product in that it provides proven accuracy in even the most demanding, regulated financial environments with use cases such as onboarding. However, unlike alternative liveness products, we have had a relentless focus on enabling a zero-friction user experience. Improving speed and increasing accuracy, including both false accepts and false rejects, for all types of users and across various devices is critical to successfully using face for identity verification and authentication.”
ID R&D added that its IDLive Face solution is the lone single image passive facial liveness detection product to achieve iBeta Level 2 presentation attack detection (PAD) compliance.
Article Topics
accuracy | algorithms | biometric-bias | biometrics | facial recognition | ID R&D | passive facial liveness | research and development
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