Netki showcases enhanced biometric face matching technology

This week at the North American Bitcoin Conference Netki released an update of the biometric face matching technology for its OnboardID solution. The update increases ID validation through facial image scanning from multiple sources, the company announced.

“Our face-matching algorithm now outperforms industry-leading solutions by more than 60 percent,” said Steve Scott, Director of Software Engineering at Netki. “We’re especially proud of the algorithm’s ability to successfully match a wide variety of skin tones, from very light to very dark, as well as find and match faces in darker lighting conditions.”

Netki’s OnboardID is used by a number of financial institutions to validate new user or existing customer identity and prevent fraudulent account creation. The first step is to take a selfie and a photo of their ID, on which OnboardID will run its face-matching technology to confirm the person in the selfie and in the ID are one and the same.

The company claims recent product enhancements have led to a 62 percent improvement over other technologies on the market, reducing the need for manual inspection and cutting down costs.

“In the past, we licensed best-of-breed third-party algorithms inside of our face matching platform, but these solutions often were unable to successfully find and match faces in the wide variety of environments and lighting conditions end users experience in the wild,” said Justin Newton, CEO of Netki.

“Manual inspections are costly and time-consuming for customers. With the most recent update to our in-house technology, we have been able to reduce the number of cases requiring manual inspection by 83 percent!” said Newton. “It’s a dramatic improvement, which will reduce costs for our customers as well as speed their new account creation.”

The technology Netki develops is compatible with multiple skin tones and it will be implemented for all customers over the next weeks.

“We wanted to ensure that Netki’s algorithms were different than the others,” said Dawn Newton, COO of Netki. “That focus enabled us to develop our latest facial recognition algorithm, that recognizes faces from around the globe.”

A recent NIST study looking at the issue of bias in facial biometrics found a significant difference in the accuracy of some algorithms in matching women and people with darker skin.

Article Topics

accuracy  |  algorithms  |  biometric identification  |  biometric matching  |  biometrics  |  facial recognition  |  NIST