Identity verification 101
If you’re new to identity verification, the identity space uses several closely related terms that are often used interchangeably even if they don’t always mean the same thing.
Outside of these core three verification methods, many other types of verifications are possible, like document verification and phone/email ownership verification. When and how you introduce these methods depends heavily on your use case, applicable regulations, and industry.
Consider identity verification for a gig economy marketplace
Until recently, most marketplaces only verified workers once at onboarding. Today, the typical marketplace verifies more types of users at different times for different reasons:
Workers for regulatory compliance
Buyers for fraud prevention
To protect their insurance policies and prevent fraudulent refunds, many platforms now verify buyers before processing claims over a certain threshold.
Workers for high-risk transactions
When a worker changes their bank account, requests a large payout, or gets flagged for suspicious activity, the platform needs to reverify identity quickly to stop fraud without blocking legitimate users.
Candidates and employees for security
With the rise of generative AI, fraudsters increasingly impersonate legitimate employees to access internal data and systems. Workforce identity verification is becoming table stakes, particularly for gig platforms that hire quickly and don’t meet workers in person.
Workers for regulatory compliance
Buyers for fraud prevention
To protect their insurance policies and prevent fraudulent refunds, many platforms now verify buyers before processing claims over a certain threshold.
Workers for high-risk transactions
When a worker changes their bank account, requests a large payout, or gets flagged for suspicious activity, the platform needs to reverify identity quickly to stop fraud without blocking legitimate users.
Candidates and employees for security
With the rise of generative AI, fraudsters increasingly impersonate legitimate employees to access internal data and systems. Workforce identity verification is becoming table stakes, particularly for gig platforms that hire quickly and don’t meet workers in person.
Chances are, your organization is facing IDV demands it never had to meet before. At the same time, you’ve got to navigate a regulatory gauntlet that changes constantly.
To keep up, you need an adaptive identity verification strategy.
Adaptive identity verification
Adaptive identity verification moves beyond one-time checkpoints and binary decisions. It treats risk as a spectrum and adjusts verification dynamically based on real-time signals.
Instead of asking
Did we verify this person?
Ask
Are we applying the right level of verification for this user at this moment, given what we know?
Example 1
If the majority of your users present low-risk signals, they’ll experience minimal verification friction, making it easier for them to convert.
Example 2
If a minority of users present suspicious signals, they’ll have to pass additional verifications with stronger fraud controls.
Why adaptive IDV doesn’t mean “fraud prevention”
One of the most common misconceptions about IDV is that there's a single "fraud prevention" button you can turn on to catch bad actors.
In reality, every verification method triggers a series of individual checks that run behind the scenes. Each of these checks helps detect different fraud patterns or validates different aspects of identity.
To illustrate how it works, let’s take a look at two of the most common verification methods: government ID and selfie verification.
Government ID verification
Document authenticity analysis to look for signs of tampering or forgery
Data extraction and validation to confirm the information is internally consistent
Expiration checks
Template matching — verifying the ID format matches the issuing authority's standards
Cross-reference against databases like AAMVA for driver's licenses to increase assurance
Selfie verification
Liveness detection to distinguish a live person from a deepfake, photo, or mask
Device intelligence to verify the person is taking a live selfie rather than injecting a recorded video or deepfake
Facial recognition to compare the selfie to a reference image, like a photo ID
Adaptive IDV impacts how you build your identity verification program.
The upside is configurability: You choose which checks run in the background. You can dial them up or down to match your risk tolerance, compliance requirements, and user experience goals.
Example 1
Example 2
Example 1
Example 2
The downside is complexity: there's no single, straightforward answer to "fraud prevention." Instead, you must make dozens of micro-decisions about how strict each individual check should be, which checks to run for which users, and when to escalate to manual review.
This configurability is what makes adaptive IDV powerful, but it also means you need a clear understanding of your risk surface, your user population, and your tolerance for false positives versus false negatives.