iDenfy, a pioneer in the field of identity verification and fraud prevention, has introduced a new Age Estimation tool within its onboarding software.
This advancement allows users to manage age verification processes independently of the company's usual identity verification methods while maintaining high security standards. The innovative tool offers a non-document-based workflow that seeks to increase user conversions while adhering to age verification regulations.
Enhanced Age Verification Workflow
The Age Estimation process enables businesses to ascertain if a user fulfills minimum age criteria using either live selfies or uploaded images, crucial for sectors like iGaming and finance requiring compliance checks. Traditionally, iDenfy's platform necessitated uploading an ID photo for age verification. The new feature removes this step, relying solely on selfie biometrics to estimate age from facial characteristics.
iDenfy has transformed age estimation from a mere onboarding feature into a standalone function with independent permissions, billing, and API endpoints. This allows partners focusing solely on Age Estimation not to engage the full identity verification suite. Users can access comprehensive session lists, generate tokens, and view detailed sessions from a centralized platform utilizing customized settings and fully documented APIs.
Accurate Age Estimation and Compliance
iDenfy has transformed age estimation from a mere onboarding feature into a standalone function
In the age estimation flow, users capture a live selfie that is measured against age limits set by businesses, achieving up to 3-year gap accuracy. Users significantly above the threshold are swiftly verified, whereas those near the limit are directed to use a certified ID check, ensuring accuracy without over-reliance on estimate models. iDenfy notes that adults over the age of 25 are easily verified, while younger users can present challenges due to facial feature variances.
Domantas Ciulde, CEO of iDenfy, underlined that enabling partners to monitor what's happening within sessions is crucial, especially in age-restricted markets. He stated, "We improved our product against disguises such as makeup or a mustache to precisely estimate people’s age and brought it into the dashboard with its own sessions list and detail view." Verified age data minimizes the need to collect user information to secure compliance with various regulations, such as the UK Online Safety Act and GDPR, and new laws emerging in the US and Australia.
Simplifying Age Verification
By combining estimate data and document verification in one session, compliance reviews and audits are streamlined, eliminating the need for reconciling information from multiple systems.
Domantas Ciulde emphasized, "Centralizing session creation and results in one dashboard view might sound like a small operational detail, but for partners that run age checks at scale, it removes a lot of manual tracking that used to happen outside our platform." iDenfy's Age Estimation dashboard is now available for partners, integrating seamlessly with API or Dashboard solutions, backed by round-the-clock support to ensure efficient implementation without extra coding.
iDenfy, the global identity verification, compliance, and fraud prevention business, announced the launch of its Age Estimation tool integrated into its onboarding software dashboard.
This new Age Verification upgrade gives the ability to create, manage, and review age verification sessions on their own, separately from iDenfy’s standard identity verification flow metrics, while still relying on the same level of security. That means iDenfy’s users will now be able to choose an alternative, non-document-based Age Estimation workflow, designed to convert more users while still complying with age check requirements.
Age verification workflow
Age Estimation is a process that determines whether a user meets a minimum age requirement using a real-time selfie or via an uploaded document with the picture, if that requires a compliance policy, such as iGaming or financial industries.
It is also commonly used by platforms that must confirm age eligibility before granting access to certain products or content. Previously, iDenfy’s platform offered an age verification workflow that required the end-user to upload a photo of their government-issued ID document. Now, with the new add-on of Age Estimation, this step can be removed, and the user can only be asked to capture their selfie biometrics. The system then determines the person’s age based on their facial features.
Treating age estimation
Rather than treating age estimation as a feature bundled inside a broader onboarding flow, iDenfy has built it out with its own permission structure, billing model, and API endpoints, so its partners that only need Age Estimation checks are not required to adopt the full identity verification stack to access it.
As a result, iDenfy’s users can view a full sessions list, generate tokens, and open a detailed session page from a single, centralized view, all supported by their own custom settings, fully encoded verification URLs, and official API documentation.
Official API documentation
When a business enables the age estimation flow, the end user is asked to capture a live selfie, which is compared against a configurable age limit and buffer zone set by the business. It is worth mentioning that iDenfy’s age estimation tool can estimate people’s age within 3 years of gap accuracy, and control the age limit businesses want to provide access to their products. Users who are clearly above the age threshold pass in seconds using only a selfie. On the other hand, users whose estimated age falls near the legal limit are automatically routed to a certified ID document check within the same session, where the date of birth on the document, not the model’s estimate and make the final decision.
iDenfy claims that most young adults who are over 25 are considered easily verifiable. However, many companies have a hard time differentiating 18 to 24 age category. These users often still look young, and their facial features can be shaped by genetics or other external factors that potentially can mislead their verification systems.
Personal data businesses
According to Domantas Ciulde, the CEO of iDenfy, the update reflects a broader pattern the company has noticed among its partners that operate in age-restricted and regulated markets:
“Age estimation only works if the people using it can actually see what’s happening inside each session. We improved our product against disguises such as makeup or a mustache to precisely estimate people’s age and brought it into the dashboard with its own sessions list and detail view,” commented Domantas Ciulde.
Validated age data reduces the risk of underage access to restricted products, platforms, and content, while limiting how much of the personal data businesses need to collect in the process. Because most users pass on a selfie alone, companies avoid asking their entire user base to submit a government ID just to prove they are old enough. This supports compliance with regulations such as the UK Online Safety Act, the EU Digital Services Act’s age assurance guidance, and GDPR’s data minimisation principle, as well as emerging state-level age verification laws in the United States and Australia’s under-16 social media restrictions.
Small operational detail
Because the estimate and the document fallback now run inside the same session and the same dashboard, review and audit work move faster too. Compliance teams can see what was checked without needing to reconcile records across separate tools.
“Centralizing session creation and results in one dashboard view might sound like a small operational detail, but for partners that run age checks at scale, it removes a lot of manual tracking that used to happen outside our platform,” added Domantas Ciulde, the CEO of iDenfy. The Age Estimation dashboard module is available now to iDenfy partners, who can integrate through API or Dashboard, with 24/7 support available from iDenfy’s team to guarantee a smooth setup without any additional coding.
