Is AI the Biggest Threat or Most Significant Ally in Identity Verification?
For identity verification, business risk mitigation, and customer protection, the answer is both.
Rise of the AI ID
In 2025, most fake IDs look genuine to the human eye. Recognizing the threats they face, leaders in all manner of industries, from retail and financial institutions to car dealerships and casinos, are seeking methods to combat this issue. In the US, organizations are deploying digital and physical ID verification methods to stop fraudsters using fake IDs.
- As fraud methods evolve, verification solutions must be up to the challenge. Outdated systems can and will be fooled by new methods, harming the business reputation and impacting customer safety and spending habits.
- The accessibility of fraudulent identities is rising, with the darkweb becoming more and more prominent. Our recent exploration into these markets saw AI-generated ID images readily available for as little as $5.
- Consumers are fearful of new fraud methodologies, chiefly related to rising confusion around AI. Recent IDScan research from 2024 highlighted that 78% of consumers pointed to the misuse of AI as their core fear around identity protection. Equally, 55% believe current technology isn’t enough to protect our identities. Businesses cannot sit idle while AI damages consumer trust, as impacts to bottom lines will swiftly follow.
State of the AI ID
The reality of using AI to generate fake IDs is rather basic – at least compared to what most businesses envision when they think of AI and identity fraudsters joining forces. Darkweb suppliers rely on PDF417 and ID image generators, using varying degrees of automation to match data inputs onto a contextual background. Easy-to-use tools such as Thispersondoesnotexist make it simple for even low-skilled fraudsters to combine a quality fake ID image with a synthetic identity.
However, businesses must acknowledge consumer fears and adapt their security processes not for where AI-IDs are right now but how they will rapidly evolve in the future. By demonstrating that existing solutions are up to the challenge, businesses can put customers at ease and protect their bottom lines.
So How Effective are AI IDs at Committing Fraud?
Catch rates for non-AI generated IDs processed through IDScan.net’s proprietary and third-party checks average 95%. In our study, we caught 99.6% of AI-generated fake IDs.
Our analysis revealed the AI being used to create these fraudulent IDs is not yet able to compete with the sophistication of our identity verification systems. Simply, AI-IDs have trouble with finer details that systems specifically look for, including differing templates and data syntax across states. The scale of fake ID user requirements weigh on AI-ID efforts; each state’s ID has its own system for encoding personal data into the barcode, and even the slightest discrepancy in this is enough for ID verification systems to identify them.
Where are Identity Solutions Winning?
Across our study, we found 24% of AI IDs showed evidence of photo tampering. While not always immediately obvious to the human eye, verification systems identified the smallest discrepancies in document tampering. While this is encouraging for businesses that have implemented a document tampering solution, it’s evidence that barcode and OCR validation alone may not be enough to identify evidence of tampering. Here, we must stress the importance of not relying on a single system to quash the diversified threat of identity fraud.
State by State
The diversification of identity documents throughout the US creates an ever-changing cycle of new IDs, introducing risk to businesses that may lack the knowledge or software applications to assess at a nationwide level.
Our study revealed that the quality of fake IDs, analyzed through various physical and software-based fraud prevention tools, varied state by state. While states such as New York, Texas, and Arizona see the most frequent use of fake IDs, according to IDScan.net’s 2023 and 2024 Annual Fake ID Reports, they were also the easiest to catch. We caught 100% of the fakes from these high-volume states.
AI IDs in the Future
From our study, the immediate horizon for businesses concerned about the rise of fake AI-IDs seems bright. On one hand, current systems are good enough to catch the large majority, on the other, organisations already exploring mitigation strategies for the rising threat of AI-IDs are one step ahead, and will stay diligent around the battle between fraudsters and the solutions in place to stop them.
However, we must temper optimism: AI IDs will improve at a faster rate and we must not be complacent. To mitigate the risk of ever-improving AI fraud, businesses must have AI-ready methods of their own, by way of best-in-class identity solutions.
Conclusion
In conclusion, while AI-IDs pose a significant threat to businesses, our study suggests that current identity verification solutions are effective in detecting and preventing fraudulent activities. However, it is crucial for businesses to stay ahead of the evolving threat landscape and adapt their security processes to keep pace with the development of AI-IDs.
FAQs
- What is the impact of ID fraud on businesses?
- The true cost of ID fraud is likely much larger than currently reported, with Javelin research suggesting the figure is upwards of $50 billion per year for US businesses.
- How effective are AI IDs at committing fraud?
- Catch rates for non-AI generated IDs processed through IDScan.net’s proprietary and third-party checks average 95%. In our study, we caught 99.6% of AI-generated fake IDs.
- What are the key problem areas in ID verification?
- As fraud methods evolve, verification solutions must be up to the challenge. Outdated systems can and will be fooled by new methods, harming the business reputation and impacting customer safety and spending habits.
- The accessibility of fraudulent identities is rising, with the darkweb becoming more and more prominent.
- Consumers are fearful of new fraud methodologies, chiefly related to rising confusion around AI.
