The digital economy moves fast. Today, it\u2019s 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\u2019re trying to reach is of a sensitive, high risk or age-restricted nature. <\/p>\n\n\n\n
That\u2019s why Identity Verification (IDV)<\/strong> 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 <\/strong>for identity verification to help you design a verification experience your users will actually complete.<\/p>\n\n\n\n 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\u2019s why leading organizations are shifting from rigid, one-size-fits-all identity checks to dynamic, risk-based verification flows.<\/p>\n\n\n\n Did you know that, according to recent findings<\/a>, 38% <\/strong>of customers abandon online applications because the digital identity verification process is too long or complex?<\/p>\n\n\n\n The Best Practice #1:<\/strong> 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. <\/p>\n\n\n\n Here is what it looks like in practice:<\/p>\n\n\n\n Example:<\/strong> 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<\/a>) process.<\/p>\n\n\n\n Institutions can reduce onboarding costs by up to <\/em>90% <\/em><\/strong>and significantly cut fraud, including saving up to <\/em>$1.6 trillion <\/em><\/strong>globally in reduced payroll fraud. <\/em>Source<\/em><\/a><\/p>\n<\/blockquote>\n\n\n\n We\u2019ve 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<\/a> abandon digital onboarding due to such kind of friction. That\u2019s why offering a smooth user experience is your best defense against drop-offs.<\/p>\n\n\n\n The Best Practice #2:<\/strong> Design a user experience that is intuitive, transparent, and forgiving.<\/p>\n\n\n\n To keep users moving forward:<\/p>\n\n\n\n In 2025, the average onboarding time for regulated industries was <\/em>35 minutes<\/em><\/strong> \u2013 nearly three times longer than what customers are willing to tolerate. <\/em>Source<\/em><\/a><\/p>\n<\/blockquote>\n\n\n\n The global nature of digital business means you\u2019ll encounter users with different ID types, device capabilities, and preferences. And some people don\u2019t even have formal IDs: around 800 million people globally<\/a> still lack official proof of identity, making it harder to access finance and essential services.<\/p>\n\n\n\n So, limiting yourself to one method of identifying a user’s identity will only limit your market.<\/p>\n\n\n\n The Best Practice #3:<\/strong> Provide a layered, adaptable set of identity verification<\/a> methods.<\/p>\n\n\n\n Recommended methods include:<\/p>\n\n\n\n 81%<\/em><\/strong> of global consumers consider biometric verification to be more secure than traditional methods. <\/em>Source<\/em><\/a><\/p>\n<\/blockquote>\n\n\n\n Presentation attacks during an identity verification process (holding up a photo) are old news. We are now facing the era of „sophisticated fraud” \u2013 AI-generated deepfakes and injection attacks that can fool standard cameras.<\/p>\n\n\n\n While overall identity fraud rates have stabilized, sophisticated fraud (including deepfakes) surged by 180% in the last year<\/a>. It seems like attackers are moving from quantity to quality.<\/p>\n\n\n\n The Best Practice #4:<\/strong> Employ advanced, ISO-compliant liveness detection<\/a>.<\/p>\n\n\n\n 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.<\/p>\n\n\n\n Example:<\/strong> 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\u2019t replicate.<\/p>\n\n\n\n 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.<\/p>\n\n\n\n The Best Practice #5:<\/strong> Use AI to conduct rapid, multi-point document analysis.<\/p>\n\n\n\n Example:<\/strong> If a passport MRZ says the expiry date is 2030, but the visual zone says 2029, the system should flag it automatically.<\/p>\n\n\n\n Manual review is slow, costly, and prone to human fatigue, while automation increases speed, reduces human error, and scales effortlessly. Leading IDV providers<\/a> typically process verifications in about 5 to 12 seconds on average.<\/p>\n\n\n\n The Best Practice #6:<\/strong> Automate for speed and accuracy and reserve human expertise for high-risk \u201cgray areas\u201d.<\/p>\n\n\n\n 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.<\/p>\n\n\n\n Today\u2019s 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\u2019s why your commitment to privacy is the key trust signal.<\/p>\n\n\n\n The Best Practice #7:<\/strong> Adhere to the data minimization principle.<\/p>\n\n\n\n Example:<\/strong> If your process only needs to verify age eligibility, don\u2019t store the full passport details; instead, keep only the validated result.<\/p>\n\n\n\n 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\u2019t know that the person is on a terror watchlist.<\/p>\n\n\n\n The Best Practice #8:<\/strong> Ensure your IDV process triggers immediate AML screening.<\/p>\n\n\n\n Connecting IDV to AML helps ensure regulatory compliance, instant risk scoring, faster detection of suspicious behavior, and simplified audits.<\/p>\n\n\n\n An integrated IDV-AML system includes:<\/p>\n\n\n\n 2-5% of global GDP<\/em><\/strong> is laundered each year (up to around <\/em>$2 trillion<\/em><\/strong> annually), which is why robust IDV and AML controls have to work together. <\/em>Source<\/em><\/a><\/p>\n<\/blockquote>\n\n\n\n Identity verification is never a \u201cset it and forget it\u201d process. Fraud tactics and regulatory requirements evolve constantly, and so do user expectations. That\u2019s why your identity verification process should always be updated.<\/p>\n\n\n\n The Best Practice #9:<\/strong> Treat identity verification as an ongoing test.<\/p>\n\n\n\n Even small UX improvements can significantly boost onboarding conversions. Here are a few things you can test and measure:<\/p>\n\n\n\n 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.<\/p>\n\n\n\n What\u2019s 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.<\/p>\n\n\n\n And that\u2019s exactly what Ondato<\/a> does, helping you:<\/p>\n\n\n\nUse the Risk-Based Identity Verification<\/strong><\/h2>\n\n\n\n
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Keep Onboarding Simple and Reduce Friction<\/strong><\/h2>\n\n\n\n
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Offer Multiple Verification Methods<\/strong><\/h2>\n\n\n\n
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Implement Strong Liveness Detection<\/strong><\/h2>\n\n\n\n
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Strengthen Document Fraud Detection<\/strong><\/h2>\n\n\n\n
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Automate What You Can, Review Only Exceptions Manually<\/strong><\/h2>\n\n\n\n
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Limit Data Collection and Prioritize Privacy<\/strong><\/h2>\n\n\n\n
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Integrate Identity Verification with AML Controls<\/strong><\/h2>\n\n\n\n
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Continuously Test and Improve Your Verification Flow<\/strong><\/h2>\n\n\n\n
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Why Using an Identity Verification Platform Simplifies Everything<\/strong><\/h2>\n\n\n\n