Biometric spoof attempts on the rise: Shufti Pro reports

A new white paper released by Shufti Pro suggests biometric fraud attempts are quickly rising during the holiday season, spurred by attackers exploiting the effects of the pandemic to their own advantage.
According to the report, overall identity fraud attempts increased by 3.36 percent in 2020, while 22.44 percent of all face verification attempts performed in 2020 using the Shufti Pro were identified as fraud through biometrics and blocked.
Digital replay attacks and various spoof attacks were the main biometric presentation attack techniques used by malicious actors, with the paper suggesting the same techniques may be employed this holiday season.
“Cybercrimes doubled in 2020 and without a sound approach to fight identity fraud, it is nearly impossible to combat perpetrators this holiday season,” explains Shufti Pro Victor Fredung.
The white paper shows that payment and commerce fraud attempts were higher from January through October 2020 than in the same months of 2019, but actually declined from the previous year last November and December, possibly as fraudsters shifted to targeting government pandemic benefits schemes.
“To secure businesses from million-dollar worth of identity and financial fraud, every sector is in dire need of AI-backed solutions,” Fredung adds.
According to the CEO, AI-driven identity verification services not only increase security drastically but also deliver improved customer experience.
“Shufti Pro’s state-of-the-art identity verification solutions allow businesses to verify clients in seconds and 98.67 percent accurate results make legit customer onboarding easier,” the white paper concludes.
The report comes days after Shufti Pro was selected by Russian SIM service provider Birka to provide biometric ID verification for customer registration.
Article Topics
biometric liveness detection | biometrics | digital identity | face biometrics | fraud prevention | identity verification | presentation attack detection | Shufti Pro | spoof detection | white paper
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