Smarter Age Verification With the Highest Standard of Assurance
For too long, age verification has been treated as a compliance checkbox — a necessary step to satisfy regulation, but not much more. At Incode, we take a different approach. We believe age assurance should deliver the highest standard of protection for minors, while still making the process seamless for legitimate users.
Why Levels of Assurance Matter
Not all age verification is created equal. Different approaches rely on different data, and the level of protection varies widely. Some providers do the bare minimum, while others stop short of blocking more sophisticated fraud. To make sense of the differences, it helps to think in terms of levels of assurance.
The Four Levels of Age Assurance
| Level | What it Includes | Limitations | Assurance Strength |
|---|---|---|---|
| Level 1 Data-only checks | Verifies date of birth against telco, government, or credit bureau databases | Limited coverage, excludes minors without data sources, vulnerable to stolen or borrowed information | Low |
| Level 2 Selfie-based checks | Uses face biometrics to estimate or verify age with a selfie | No tie to a real ID, so there is no concept of identity; vulnerable to spoofing, deepfakes, or manipulated captures | Medium |
| Level 3 ID + Selfie Verification | Matches a live selfie with a government-issued ID; validates document authenticity and confirms ownership | Stronger identity assurance, but still vulnerable to advanced spoofing or deepfakes if additional signals are missing | High |
| Level 4 Deepsight-powered Age Assurance | Combines all of the above with multi-frame liveness, ID liveness, device and behavioral signals, network effects, and reusability | No limitations. Legitimate users pass seamlessly through guided capture flows, while synthetic IDs, injections, and deepfakes are stopped early | Highest |
Most vendors operate at Level 1 or 2, and a handful reach Level 3. Incode is unique in delivering Deepsight-Powered Age Assurance, where multiple verification methods are reinforced by contextual risk signals and reusability. This creates the highest level of assurance available today.
What is Deepsight?
Deepsight is Incode’s advanced fraud analytics layer. It goes beyond biometrics, analyzing behavioral patterns, device integrity, and network signals to detect anomalies before a user ever uploads an ID. By integrating these signals early in the process, DeepSight blocks sophisticated attacks like synthetic identities, replay attempts, and AI-generated deepfakes — without slowing down legitimate users.
The result is a system that feels fast and intuitive for real users but is uncompromising in protecting minors and stopping fraud.
Why the Highest Standard Matters
Deepsight-Powered Age Assurance brings all of this together:
- Legitimate users pass quickly through guided capture flows, with instant recognition on return sessions.
- Fraudsters are stopped early thanks to Deepsight’s multi-layer defenses against synthetic IDs, injection attempts, and deepfakes.
- Minors are protected through conservative thresholds and multiple lines of defense, validated by independent benchmarks.
- Global compliance is exceeded through NIST testing, regulator validation, and bias audits across demographics.
Backed by Data and Scale
We do not just claim the highest standard; we measure it.
- Ranked top 3 globally in NIST’s Challenge 25, the toughest test for child safety (ages 13–16).
- Achieved 2.7 mean absolute error (MAE) in Child Online Safety benchmarks, making our models among the most accurate at detecting minors.
- Processed over 80 million liveness checks in the past year, which translates to nearly 100 million age estimations.
- Delivered the fastest response time among leading IDV providers at 230 ms.
- Performed continuous bias audits across gender, ethnicity, and skin tone, ensuring fairness in every market.
- Achieved 99% accuracy in identifying minors (ages 6–17) in internal testing.
These results demonstrate that Incode operates at scale, but also at a proven level of accuracy and resilience.
How Incode Stacks Up
Here’s how our approach compares to traditional vendors:
| Capability | Incode | Typical Vendor |
|---|---|---|
| Signals Used | Multi-signal: device, behavioral, network, IP address, face, document | Primarily biometric (face match + basic liveness) |
| Age Estimation | AI-based, behavioral, bias-tested, NIST validated | Rarely offered, limited accuracy |
| Verification Options | Waterfall: estimation → doc/selfie → DOB data | One-size-fits-all (doc/selfie only) |
| Reusability | Yes – verified once, trusted across sessions & services | No – re-verification required every time |
| Fraud Protections | Deepsight (behavioral, device, ID liveness, spoof detection) | Limited to basic liveness |
| Conversion Impact | High – low friction for good users, minimal drop-off, early signals collected before ID step | Low – friction leads to abandonment |
| Compliance Assurance | Independently validated, regulator-trusted | Compliance-only focus |
| Privacy | Live Smart-data minimization (data redaction) for both user and clients | Falls short in data privacy and handling |
This is the difference between simply “doing age verification” and adopting the highest standard of age assurance.
The Business and Safety Impact
When businesses review the cost of age assurance, the question isn’t just “are we compliant?” — it’s “what measurable value are we getting?” . Deepsight-Powered Age Assurance, organizations get measurable outcomes:
- Safer environments for minors through multiple independent checks and conservative thresholds.
- Stronger fraud prevention by detecting synthetic IDs, injections, and deepfakes before they succeed.
- Higher trust and conversion as genuine users are guided through a seamless, fair process.
- Regulatory resilience with data-driven validation and audit-ready results.
Age verification should not be the lowest bar to clear. With Incode, it becomes the highest standard to subscribe to: protecting minors, building trust, and enabling growth.