What’s the cost of pulling off a successful presentation attack—say, opening a bank account or checking in for an event using an AI-generated ID and selfie? Are we talking hundreds of dollars, and how difficult is the process?
With the increase in technological advancement, generative AI now allows fraudsters to rapidly generate thousands of realistic online identities at very affordable amounts. For instance, various online AI-generating websites have emerged, allowing users to generate multiple fake IDs simultaneously by submitting data in bulk. Unfortunately, people don’t only leverage these realistic creations for fun purposes. For example, AI-generated images of IDs from platforms like OnlyFake enable users to generate multiple types of ID documents, such as passports and driver’s licenses, in bulk. This capability allows criminals to produce hundreds of fake IDs quickly, so much that synthetic identity fraud has been predicted to reach as high as $6 billion annually in the U.S. alone.
However, the chances of this may be low if there was a comprehensive KYC flow including a customer liveness detection, to match the individuals with the documents they are presenting to ensure that the ID belongs to them.
Here’s one of the importance of incorporating customer liveness checks into a business’s digital onboarding process. Let’s delve into the details.
The Impact of Deepfakes On KYC Procedure
When thinking about the importance of liveliness detection in any solution, we cannot neglect the reason why it comes first- the rise of deepfakes. The term deepfake originated in 2017 when a Reddit user, under the same name, began sharing manipulated videos using AI technology, specifically for creating pornographic content featuring celebrities. However, the underlying technology has roots that trace back to the 1990s, when researchers first experimented with computer-generated imagery (CGI) to create realistic human images.
The evolution of deepfakes accelerated in the 2010s, driven by the availability of large datasets, advancements in machine learning, and increased computational power. By 2018, concerns began to emerge regarding the implications of deepfake technology, prompting major tech platforms to implement policies aimed at moderating its use. As this technology continues to evolve, it poses significant challenges across various sectors, including business.
As deepfake technology becomes more sophisticated, businesses are increasingly investing in detection tools to identify manipulated media. Integrating technologies such as face liveliness checks into existing security and KYC processes is essential for protecting against rising potential threats posed by deepfakes.
What is Face liveliness detection?
Liveliness detection is a technology designed to verify whether a biometric sample, such as a facial image or video, comes from a real, live person rather than a spoofed representation like a photograph, video playback, or deepfake. This capability is crucial in preventing unauthorized access and ensuring the integrity of identity verification processes.
Facial Liveliness detection is a technology designed to verify whether a biometric sample, such as a facial image or video, comes from a real, live person rather than a spoofed representation like a photograph, video playback, or deepfake. This capability is crucial in preventing unauthorized access and ensuring the integrity of identity verification processes.
Why Face liveliness detection is key for biometric systems
There is a never-ending rivalry between online scammers and businesses Fraudsters are advancing their techniques while preparing new sophisticated attacks, eager to find neglected spots in the online identity verification flow.
The rise of generative AI tools also enables scammers big time. Now, they employ new-gen photo and video creators to make compelling synthetic identities and ID forgeries. Liveness detection is therefore essential in protecting businesses from deepfake attacks and identity fraud. By effectively distinguishing between real users and AI-generated fakes, it prevents unauthorized access to sensitive data and systems. This added security layer is particularly critical in industries like finance, healthcare, and e-commerce, where identity verification is crucial. Integrating liveness detection into biometric systems also mitigates the risk of presentation attacks, which can involve using high-quality images or videos to impersonate legitimate users.
Beyond security, liveliness detection fosters trust and compliance by helping businesses meet regulatory requirements related to data protection and identity verification. Modern systems are designed to be user-friendly, often employing passive detection methods that streamline the user experience without compromising safety. As a result, customers can securely engage with services while businesses uphold strong security standards and maintain confidence in digital interactions.
How does Prembly’s liveness detection work
Our facial recognition technology is well-known for its speed and accuracy. We ensure image quality by utilizing our proprietary face biometrics/recognition technology via our SDKs. Prembly’s facial recognition technology is an AI system designed to suit various use cases ranging from face match to liveness check.
With this feature, users can provide their facial features as input to the system, which will then perform a liveliness check to ensure that the user is present and not just a still image or pre-recorded video. This ensures the security and reliability of the authentication process, as it reduces the risk of unauthorized access by fraudulent means.
The feature is suited for businesses across the globe to confirm the identity of their users/customers by carrying out ID verification with face capture and liveliness checks via the Identitypass ID Checker Widget. The ID Checker Widget SDK typically allows businesses to capture your customers’ faces with a liveness check and compare them with the image attached to the provided government ID on your app/website.
While customers may occasionally attribute the failure of face match technology to the biometric engine, most of the time, these failures result from individuals failing to follow some best practices for obtaining accurate verification results. Here are some best practices your customers should prioritize to get the most out of Prembly’s facial recognition.
How To Get Started
In line with our commitment to staying ahead of trends to keep you up to date with progressive & innovative technology that serves you security-wise, we have added Biometrics Dynamism as an extra level of security to your checks; which is available via our Mobile SDKs and can be set up for verification with Identitypass or Identityradar.
For Prembly Customers:
- Login to your dashboard
- Go to the left sidebar and click “SDK Library.”
- Click “Create new SDK.”
- Name your SDK, select the Prembly product, and then select the countries and verification endpoints.
- Enable Biometric Dynamism on the biometrics screen and select a minimum of 3 prompts (e.g., Closed Fist, Open Palm).
- Save and test your SDK.
For Your Users:
- The app displays prompts requiring specific actions (e.g., blinking, head tilting, raising a finger).
- The system differentiates between a live person and a pre-recorded video.
- Successful completion of prompts confirms the user’s physical presence and awareness.
Whether onboarding new customers or safeguarding sensitive data, biometrics dynamism provides the tools needed to stay ahead of fraudsters, and combat deepfakes.
