How AI is reshaping biometric ID verification
Keivan Bahmani, Ph.D
Lead CVML Engineer, Documents & Biometrics Engineering
In the past year, nearly 80% of fraud professionals have witnessed a sharp rise in the sophistication of fraud attempts. Even more concerning, 32% say these advanced tactics now pose a greater threat to their business than ever before. Our recent Global Fraud Report reveals a common thread behind this surge: the growing use of Generative AI (GenAI) by fraudsters.
But while GenAI is fuelling a new wave of identity fraud, it also holds the key to fighting back.
The dual nature of AI: threat and tool
AI is a double-edged sword. On one side, it enables fraudsters to scale attacks with unprecedented realism and speed. On the other, it empowers businesses to detect and prevent fraud with greater precision.
Compounding the issue is the scale and cost-efficiency of synthetic fraud. With Generative AI (GenAI) tools, fraudsters can now create and deploy synthetic identities at a fraction of the cost and time it once took. This allows fraudsters to launch widespread attacks with minimal resources.
Adding to the complexity, criminals often use AI based tools to recycle old scams. As companies adapt to new fraud vectors, attackers are exploiting blind spots by reviving familiar tactics in more convincing and technologically advanced ways. This blend of old and new makes it even more difficult for traditional systems to keep up.
To stay ahead, organisations must adopt layered, real-time identity verification strategies to protect against the next generation of fraud tactics.
“Legacy systems weren’t built for this level of sophistication. Businesses need real-time, explainable AI to keep up with today’s threats.”
How AI is disrupting biometric security
As fraud continues to evolve, with help from AI, it remains a significant challenge for businesses, especially in the face of high customer expectations. Specifically, there are vectors that seen a prominent uptick thanks to AI:
- Deepfakes: Hyper-realistic fake identities used in financial fraud and disinformation
- Tamper detect: AI-generated IDs now mimic authentic patterns so closely that traditional visual checks are no longer reliable
- Injection attacks: Synthetic data streams or virtual cameras that bypass biometric checks
Recent research outlines how traditional verification methods are being outpaced by these evolving threats. Traditional biometric systems are increasingly vulnerable to AI-fuelled threats.
Why traditional systems are falling short
Legacy identity verification systems are increasingly unable to keep pace with the evolving tactics of fraudsters. One of the most pressing challenges is their inability to detect high-quality synthetic identities. These identities, often generated using GenAI, are becoming more realistic and harder to distinguish from legitimate ones, making them a growing threat across industries.
This is impacting business across the globe. Although, U.S. respondents are twice as likely as their European counterparts to view GenAI-generated synthetic identities as the most threatening fraud vector (44% vs. 22%).
The identity fraud landscape is evolving rapidly, and organisations must remain vigilant. Legacy systems that rely on handcrafted rules are more suspectable to AI power trending fraud threats. In contrast, modern data-driven systems learn from vast datasets to detect subtle anomalies that static rules miss.
Human powered AI
The real power of AI lies in how it’s integrated into business workflows. That’s why we champion a human-in-the-loop model, where AI works alongside fraud analysts to:
- Detect novel fraud patterns
- Govern AI models to reduce bias
- Provide transparent, closed-loop data insights
Our analysts monitor transactional activity across our vast GBG Trust Network, giving businesses a real-time, cross-industry view of fraud trends.
With over 30 years of experience in identity verification, we understand that AI adoption is a journey and not a quick fix. Our layered approach to building secure onboarding journeys helps businesses stay secure while scaling confidently while building trust.
AI vs. AI: the future of identity fraud protection
As GenAI continues to evolve, so too will the tools to combat it. Smart identity proofing systems are already building multi-layered defense that combines advanced document and biometric solutions with human supervised AI based verification tools
Future-ready systems are integrating behavioral biometrics with explainable AI to create multi-layered defenses. These systems not only detect deepfakes with high accuracy but also comply with global regulatory standards. These systems can rapidly analyze massive data volumes to detect anomalies in identity documents and behaviors, empowering business to stay one step ahead of fraudsters.
An all-in-one platform that combines document and biometric authentication, real-time fraud detection and explainable AI offers the agility and depth required to counter increasingly sophisticated threats. By integrating these capabilities into a single system, organizations can streamline onboarding, enhance compliance and stay ahead of fraudsters who are leveraging generative AI to exploit outdated defenses. The future of identity verification lies in layered, human-supervised AI systems that adapt quickly and scale securely.
Read to connect safely with every genuine identity? Get a demo today.
Frequently Asked Questions
What is generative AI (GenAI) and how is it used in identity fraud?
Generative AI refers to AI models that can create realistic content such as images, voices, and videos. Fraudsters use GenAI to generate synthetic identities, deepfakes and voice clones that can bypass traditional identity verification systems, making fraud attempts more convincing and harder to detect.
Why are traditional identity verification systems no longer effective?
Traditional systems struggle to detect high-quality synthetic identities and are not equipped to handle the scale and sophistication of modern fraud tactics. They often rely on static data and manual reviews, which can be easily manipulated or overwhelmed by AI-driven attacks.
What are some of the most common AI-driven fraud tactics today?
Common tactics include deepfake-based attacks, voice cloning and injection attacks. These methods exploit vulnerabilities in biometric and identity verification systems, allowing fraudsters to impersonate real individuals or create entirely fake ones.
