Identity Verification: Best Practices Guide
The digital economy moves fast. Today, it’s often not enough to enter a simple password to gain online access. As sophisticated AI-driven fraud, such as deepfakes, is rising at an alarming rate, we need to verify who we are, especially when the content we’re trying to reach is of a sensitive, high risk or age-restricted nature.
That’s why Identity Verification (IDV) has become central to online business operations. Whether onboarding customers, preventing fraud, or meeting regulatory requirements, companies need identity verification flows that are both secure and frictionless. In this guide, we break down the 9 best IDV practices for identity verification to help you design a verification experience your users will actually complete.
Use the Risk-Based Identity Verification
Not every user or every action carries the same level of risk. Why treat every user like a high-stakes criminal? A static, uniform identity verification process adds unnecessary friction for the majority of your good customers. That’s why leading organizations are shifting from rigid, one-size-fits-all identity checks to dynamic, risk-based verification flows.
Did you know that, according to recent findings, 38% of customers abandon online applications because the digital identity verification process is too long or complex?
The Best Practice #1: Implement a risk-based approach where the verification flow dynamically adapts based on a real-time customer risk score. Opting for this approach minimizes the likelihood of onboarding process abandonment.
Here is what it looks like in practice:
- A Low Risk User: A user in a trusted region, signing up with an established device for a low-value service, like a free content subscription, might only require a basic document check, which makes the experience virtually frictionless.
- A High Risk User: A user attempting to open a high-limit bank account, using a brand-new device, from a region known for fraud, triggers a more intense “step-up” verification. This could involve biometric liveness checks and enhanced sanctions screening.
Example: A fintech app can allow returning users with a trusted device to skip document upload and use biometric face match only, while first-time high-value transactions require a full Know Your Customer (KYC) process.
Institutions can reduce onboarding costs by up to 90% and significantly cut fraud, including saving up to $1.6 trillion globally in reduced payroll fraud. Source
Keep Onboarding Simple and Reduce Friction
We’ve all been there: a dark, blurry photo upload, confusing instructions, and a forced retake cycle that makes you want to quit. In fact, 68% of consumers abandon digital onboarding due to such kind of friction. That’s why offering a smooth user experience is your best defense against drop-offs.
The Best Practice #2: Design a user experience that is intuitive, transparent, and forgiving.
To keep users moving forward:
- Explain why you need their data, such as “We need this to protect your account and meet banking regulations.”
- Give clear, human instructions, like “Take a photo in good light. Avoid glare. Place the document this way.”
- Provide instant feedback for blurry or incomplete images.
- Use minimal steps, don’t ask for more than necessary.
- Display progress indicators, so users know how long the process will take.
- Give frustration-free retakes, without forcing a full restart, like “The corner of your passport is cut off” instead of just “Error.”
In 2025, the average onboarding time for regulated industries was 35 minutes – nearly three times longer than what customers are willing to tolerate. Source
Offer Multiple Verification Methods
The global nature of digital business means you’ll encounter users with different ID types, device capabilities, and preferences. And some people don’t even have formal IDs: around 800 million people globally still lack official proof of identity, making it harder to access finance and essential services.
So, limiting yourself to one method of identifying a user’s identity will only limit your market.
The Best Practice #3: Provide a layered, adaptable set of identity verification methods.
Recommended methods include:
- Document verification: ID cards, driver’s license, passports, residence permits.
- Biometric face matching: Comparing a user’s selfie to their ID.
- NFC chip reading: Reading the cryptographically signed chip in e-Passports.
- Database or registry checks: Using credit bureaus or utility data as a contingency practice or for “light” verification.
- Fallback options, such as manual data entry.
81% of global consumers consider biometric verification to be more secure than traditional methods. Source
Implement Strong Liveness Detection
Presentation attacks during an identity verification process (holding up a photo) are old news. We are now facing the era of “sophisticated fraud” – AI-generated deepfakes and injection attacks that can fool standard cameras.
While overall identity fraud rates have stabilized, sophisticated fraud (including deepfakes) surged by 180% in the last year. It seems like attackers are moving from quantity to quality.
The Best Practice #4: Employ advanced, ISO-compliant liveness detection.
Effective facial recognition, powered by liveness detection, can spot printed photos, masks, and video replays, combat AI-generated face swaps and synthetic identities, use both active and passive checks, as well as provide real-time fraud scoring.
- Passive Liveness: The user simply looks at the camera. The system uses AI to analyze micro-reflections and skin texture to confirm a real human is present.
- Injection Attack Prevention: The system can detect when a video feed has been hijacked by software (a virtual camera) rather than coming from the physical camera lens.
Example: If a user uploads a high-quality deepfake video with perfectly stable lighting, passive liveness models analyze micro-expressions and texture anomalies that AI can’t replicate.
Strengthen Document Fraud Detection
Fraudsters are using increasingly sophisticated techniques such as digital alterations, template manipulation, and synthetic IDs. In other words, a user may present a real face, but the document they hold could be an expert forgery. Therefore, digital document analysis must be at a forensic level.
The Best Practice #5: Use AI to conduct rapid, multi-point document analysis.
- Tampering detection: Algorithms identify signs of digital alteration, like the use of Photoshop or physical tampering, like photo substitution.
- Data consistency: Cross-reference the Machine Readable Zone (MRZ) code against the visual text on the ID.
- Font and template analysis: Instantly confirm the document matches the exact font and layout specifications of the issuing authority.
- Barcode/QR code validation: comparing encoded data with the document.
- Expiry checks and comparison with global document templates.
Example: If a passport MRZ says the expiry date is 2030, but the visual zone says 2029, the system should flag it automatically.
Automate What You Can, Review Only Exceptions Manually
Manual review is slow, costly, and prone to human fatigue, while automation increases speed, reduces human error, and scales effortlessly. Leading IDV providers typically process verifications in about 5 to 12 seconds on average.
The Best Practice #6: Automate for speed and accuracy and reserve human expertise for high-risk “gray areas”.
- The “Fast Lane” – 90%+ of your verifications should be auto-approved in seconds by AI.
- The “Expert Lane” – Only cases flagged for ambiguity, like a damaged ID, are sent to a human specialist.
To sum up, use automation for data extraction (OCR), fraud scoring, liveness analysis, document classification, and duplicate checks. And reserve manual reviews for borderline or mismatched data, rare document types, complex fraud cases, high-risk regions, and VIP onboarding where human oversight adds value.
Limit Data Collection and Prioritize Privacy
Today’s consumers are increasingly sensitive about how their personal data is used, mainly for the fears of identity theft. Meanwhile, the identity verification process involves handling the most sensitive data a person owns. That’s why your commitment to privacy is the key trust signal.
The Best Practice #7: Adhere to the data minimization principle.
- Collect only what is absolutely necessary: Don’t ask for a utility bill if a passport scan satisfies the regulatory requirement.
- Secure storage: Apply end-to-end encryption.
- Use role-based access controls.
- Implement short data retention policies.
- Configure your system to automatically delete sensitive data after the retention period required by local laws, such as GDPR or CCPA, has expired.
- Support global and regional privacy regulations.
- Provide clear consent and opt-in flows.
Example: If your process only needs to verify age eligibility, don’t store the full passport details; instead, keep only the validated result.
Integrate Identity Verification with AML Controls
Identity verification becomes far more effective when it feeds directly into Anti-Money Laundering (AML) systems. Because a verified identity is useless if you don’t know that the person is on a terror watchlist.
The Best Practice #8: Ensure your IDV process triggers immediate AML screening.
Connecting IDV to AML helps ensure regulatory compliance, instant risk scoring, faster detection of suspicious behavior, and simplified audits.
An integrated IDV-AML system includes:
- Sanctions screening (OFAC, EU, UN lists, etc.)
- Politically Exposed Persons (PEP) and RCA (relatives and close associates) screening
- Adverse media monitoring
- Ongoing transaction monitoring
- Continuous Monitoring: Don’t just check once. Monitor the user daily for changes in their risk status.
2-5% of global GDP is laundered each year (up to around $2 trillion annually), which is why robust IDV and AML controls have to work together. Source
Continuously Test and Improve Your Verification Flow
Identity verification is never a “set it and forget it” process. Fraud tactics and regulatory requirements evolve constantly, and so do user expectations. That’s why your identity verification process should always be updated.
The Best Practice #9: Treat identity verification as an ongoing test.
Even small UX improvements can significantly boost onboarding conversions. Here are a few things you can test and measure:
- A/B testing: Test different UI flows, such as steps, instructions, layout, and camera guidance. Does asking for a selfie before the ID document improve completion rates, or is it better to do it after?
- Monitor core metrics: Track your completion (pass), drop-off, and time-to-verify rates, as well as false acceptance/false rejection rates.
- Analyze failures and device-specific performance: Look at why users fail. Is it poor lighting? Unclear instructions? fix the root cause.
Why Using an Identity Verification Platform Simplifies Everything
Building a system that handles global document checking, biometric liveness, deepfake detection, and AML screening, while staying compliant with ever-changing regulations, is a massive technical undertaking that requires a lot of resources. And maintaining it internally means constant updates, audits, optimizations, and monitoring.
What’s the solution? Having a dedicated IDV platform that can centralize everything into an automated, secure, and fully compliant workflow. Instead of cobbling together different vendors for OCR, biometrics, and database checks, a comprehensive solution can provide a single, all-in-one OS for identity and compliance.
And that’s exactly what Ondato does, helping you:
- Custom-build your flows using a drag-and-drop builder to suit different risk levels.
- Verify documents from virtually any country in seconds.
- Automate AML screening and lifecycle management are integrated directly into the onboarding flow.
Having this identity verification system at your disposal, your business can enjoy faster onboarding, reduced compliance burden, and increased conversion rates.
Looking to build a verification flow that is secure, scalable, and delightful for users? Explore how Ondato can help you verify identities with confidence.
Looking Ahead
The best identity verification practice is one that balances ironclad security with effortless user experience, such as invisible authentication, decentralized identity solutions, and AI that spots fraud before it happens.
Businesses that will thrive in the future are those that treat digital identity verification not just as a compliance checkbox, but rather a trust builder that welcomes good users in seconds while keeping bad actors out.
The best way to stay ahead is to combine risk-based verification, strong fraud prevention, smart automation, and privacy-first principles. So, don’t waste resources trying to build this internal infrastructure from scratch. Instead, partner with the experts, automate the complexity, and stay confidently ahead.
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