Unisys wins contract to provide biometric identity service with IDEMIA matching engine for Australian Home Affairs
Unisys has won an AUD $44.2 million (US$34 million) contract to provide the Australian Department of Home Affairs’ with a new Enterprise Biometric Identity Service (EBIS) to aid visa, border crossing, and citizenship applications, ARN reports.
Unisys is providing its Unisys Stealth(identity) biometric management and processing platform, along with the system integration.
IDEMIA has revealed that it will provide the biometric matching engine for the EBIS, and the scalability of IDEMIA’s MorphoBSS multi-biometric engine, combined with the scalability of Unisys Stealth(identity), will provide a flexible capability for seamless integration with Home Affairs’ wider ecosystem, according to the announcement.
Stealth(identity) supports facial, finger, iris, and voice recognition, and is capable of performing up to 100,000 daily transactions, matching against a database of more than 100 million records with operations across multiple devices.
IDEMIA’s global biometrics research capability and local personnel from IDEMIA and Unisys will be called on to deliver the high level of accuracy Home Affairs requires for the program. Australian border control has been using IDEMIA technology since the country implemented Smartgates in 2004.
“We are very proud to be providing this flagship biometric platform with our partner Unisys,” said Tim Ferris, Vice President for IDEMIA’s Public Security and Citizen Identity activities in APAC. “Our teams both locally and globally are excited by this major system which will form one of the keystones of the security of the Australian border.”
Australia is also in the process of expanding its use of biometrics for other identity applications, such as online ID.
IDEMIA announced earlier this month that it will provide enrollment in the TSA Precheck program at a retail location in Brooklyn’s Barclays Center, along with fast access to the venue. Unisys also recently announced the addition of a machine learning tool to its border control portfolio.