Dutch Firm Veridas Unveils AI Tools to Combat Identity Fraud
Amsterdam, Tuesday, 11 February 2025.
Veridas launches an AI-driven system on 9 February 2025, targeting identity fraud with advanced injection attack detection and liveness verification to counter synthetic identities in financial fraud.
Rising Synthetic Identity Threat
The financial sector faces an unprecedented challenge as synthetic identities now account for 85% of financial fraud cases [1][4]. Veridas, headquartered in Pamplona, Spain [1], has responded to this escalating threat by introducing a comprehensive security solution that combines injection attack detection with sophisticated biometric verification systems [1][4].
Advanced Detection Capabilities
The newly launched system employs multiple layers of security, integrating facial, voice, and document authentication with advanced injection attack detection [1][3]. This technology specifically targets sophisticated fraud attempts by identifying and blocking emulated environments, virtual machines, and unauthorized developer tools that attackers use to bypass traditional security measures [3].
International Impact
The solution has already gained significant traction, with financial institutions across Italy, Spain, the United States, and Mexico implementing the technology to uncover previously undetectable fraud attempts [4]. According to Javier San Agustín, CTO at Veridas, ‘Our technology is a game-changer for businesses facing the challenges of Gen AI fraud. By adopting Veridas’ injection fraud detection, companies can protect their operations, maintain customer trust, and confidently meet compliance requirements’ [4].
Real-Time Protection
The system’s real-time capability ensures legitimate users experience seamless verification while effectively blocking potential threats before they can impact business operations [3]. This approach represents a significant advancement in the fight against industrialized fraud, particularly as generative AI continues to enable increasingly sophisticated attack methods [1][3].