{"id":491,"date":"2026-06-03T08:34:00","date_gmt":"2026-06-02T22:34:00","guid":{"rendered":"https:\/\/nexiant.ai\/resources\/blogs\/?p=491"},"modified":"2026-06-09T15:47:31","modified_gmt":"2026-06-09T05:47:31","slug":"liveness-detection-digital-onboarding-deepfake-fraud","status":"publish","type":"post","link":"https:\/\/nexiant.ai\/resources\/blogs\/liveness-detection-digital-onboarding-deepfake-fraud\/","title":{"rendered":"Liveness Detection in Digital Onboarding"},"content":{"rendered":"\n<style>\n  .nx-blog * { box-sizing: border-box; margin: 0; padding: 0; }\n  .nx-blog { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; font-size: 16px; line-height: 1.75; color: #1a1a2e; max-width: 820px; margin: 0 auto; }\n  .nx-blog h2 { font-size: 1.55rem; font-weight: 700; color: #00184C; margin: 2.5rem 0 0.75rem; padding-bottom: 0.4rem; border-bottom: 3px solid #073EA1; }\n  .nx-blog h3 { font-size: 1.15rem; font-weight: 700; color: #073EA1; margin: 1.75rem 0 0.5rem; 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}\n  .nx-badge { display: inline-block; font-size: 0.73rem; font-weight: 600; padding: 2px 9px; border-radius: 20px; }\n  .nx-badge--red { background: #fde8e8; color: #A30000; }\n  .nx-badge--blue { background: #EEF2FF; color: #073EA1; }\n\n  .nx-inline-link { color: #073EA1; text-decoration: underline; font-weight: 600; }\n  .nx-inline-link:hover { color: #00184C; }\n\n  .nx-faq { margin: 1.25rem 0 1.75rem; }\n  .nx-faq-item { border: 1px solid #d0daf5; border-radius: 8px; margin-bottom: 8px; overflow: hidden; }\n  .nx-faq-q { width: 100%; background: #fff; border: none; text-align: left; padding: 1rem 1.25rem; font-size: 0.95rem; font-weight: 600; color: #00184C; cursor: pointer; display: flex; justify-content: space-between; align-items: center; gap: 1rem; }\n  .nx-faq-q:hover { background: #f5f8ff; }\n  .nx-faq-q .nx-chevron { flex-shrink: 0; width: 20px; height: 20px; border-radius: 50%; background: #EEF2FF; display: flex; align-items: center; justify-content: center; transition: transform 0.25s; }\n  .nx-faq-q .nx-chevron svg { width: 10px; height: 10px; stroke: #073EA1; fill: none; }\n  .nx-faq-q[aria-expanded=\"true\"] .nx-chevron { transform: rotate(180deg); background: #073EA1; }\n  .nx-faq-q[aria-expanded=\"true\"] .nx-chevron svg { stroke: #fff; }\n  .nx-faq-a { display: none; padding: 0 1.25rem 1rem; font-size: 0.92rem; color: #333; line-height: 1.7; background: #fff; }\n  .nx-faq-a.open { display: block; }\n\n  .nx-cta { background: linear-gradient(135deg, #00184C 0%, #073EA1 100%); border-radius: 12px; padding: 2rem; text-align: center; margin-top: 2.5rem; }\n  .nx-cta h3 { color: #fff; font-size: 1.3rem; font-weight: 700; margin-bottom: 0.5rem; }\n  .nx-cta p { color: #AEC9FF; font-size: 0.95rem; margin-bottom: 1.25rem; }\n  .nx-cta a { display: inline-block; background: #E11A1A; color: #fff; font-weight: 700; font-size: 0.95rem; padding: 0.7rem 1.8rem; border-radius: 6px; text-decoration: none; transition: background 0.2s; }\n  .nx-cta a:hover { background: #A30000; }\n  .nx-divider { border: none; border-top: 1px solid #e0e7f5; margin: 2rem 0; }\n  .nx-disclaimer { font-size: 0.8rem; color: #888; font-style: italic; text-align: center; margin-top: 1.5rem; }\n<\/style>\n\n<div class=\"nx-blog\">\n\n  <div class=\"nx-hero\">\n    <span class=\"nx-tag\">Fraud Prevention Guide &nbsp;\u00b7&nbsp; June 2026 &nbsp;\u00b7&nbsp; Global Focus<\/span>\n    <p class=\"nx-meta\">Liveness detection helps regulated businesses check whether a real person is present during digital onboarding. As identity fraud becomes more sophisticated, it is becoming a practical control for reducing remote onboarding risk.<\/p>\n  <\/div>\n\n  <p>Liveness detection is now an important part of digital onboarding. It helps businesses check whether the person completing an identity check is physically present, rather than using a photo, video, mask or manipulated media.<\/p>\n\n  <p>This matters because customer onboarding is no longer always face to face. Banks, fintechs, payment providers, marketplaces and regulated digital platforms often verify customers remotely. As a result, fraud teams need controls that can support speed, customer experience and stronger identity assurance at the same time.<\/p>\n\n  <p>Used well, liveness detection can strengthen <a href=\"\/solutions\/membercheck\/id-verification\/\" class=\"nx-inline-link\">digital ID verification<\/a>. It can also support wider <a href=\"\/solutions\/membercheck\/pep-sanctions-screening\/\" class=\"nx-inline-link\">PEP and sanctions screening<\/a>, adverse media checks, customer risk scoring and ongoing monitoring.<\/p>\n\n  <div class=\"nx-media\">\n    <img decoding=\"async\"\n      src=\"data:image\/svg+xml,%3Csvg xmlns='http:\/\/www.w3.org\/2000\/svg' width='820' height='460' viewBox='0 0 820 460'%3E%3Cdefs%3E%3ClinearGradient id='g' x1='0' y1='0' x2='1' y2='1'%3E%3Cstop offset='0' stop-color='%2300184C'\/%3E%3Cstop offset='1' stop-color='%23073EA1'\/%3E%3C\/linearGradient%3E%3C\/defs%3E%3Crect width='820' height='460' rx='22' fill='url(%23g)'\/%3E%3Ccircle cx='190' cy='210' r='64' fill='%23AEC9FF' opacity='0.22'\/%3E%3Ccircle cx='190' cy='188' r='28' fill='%23ffffff' opacity='0.9'\/%3E%3Cpath d='M135 285c12-44 98-44 110 0' fill='none' stroke='%23ffffff' stroke-width='14' stroke-linecap='round' opacity='0.9'\/%3E%3Crect x='340' y='128' width='300' height='56' rx='10' fill='%23ffffff' opacity='0.96'\/%3E%3Crect x='340' y='206' width='300' height='56' rx='10' fill='%23ffffff' opacity='0.86'\/%3E%3Crect x='340' y='284' width='300' height='56' rx='10' fill='%23ffffff' opacity='0.76'\/%3E%3Ccircle cx='370' cy='156' r='11' fill='%23073EA1'\/%3E%3Ccircle cx='370' cy='234' r='11' fill='%23073EA1'\/%3E%3Ccircle cx='370' cy='312' r='11' fill='%23073EA1'\/%3E%3Ctext x='400' y='162' font-family='Arial, sans-serif' font-size='22' font-weight='700' fill='%2300184C'%3EDocument verification%3C\/text%3E%3Ctext x='400' y='240' font-family='Arial, sans-serif' font-size='22' font-weight='700' fill='%2300184C'%3EBiometric matching%3C\/text%3E%3Ctext x='400' y='318' font-family='Arial, sans-serif' font-size='22' font-weight='700' fill='%2300184C'%3ELiveness detection%3C\/text%3E%3Ctext x='70' y='394' font-family='Arial, sans-serif' font-size='28' font-weight='700' fill='%23ffffff'%3EDigital onboarding identity checks%3C\/text%3E%3C\/svg%3E\"\n      alt=\"Liveness detection workflow for digital onboarding and identity verification\"\n      loading=\"lazy\"\n      width=\"820\"\n      height=\"460\"\n    >\n    <p class=\"nx-caption\">Liveness detection works best when it is connected with document verification, biometric matching and AML screening as part of a wider onboarding workflow.<\/p>\n  <\/div>\n\n  <div class=\"nx-callout\">\n    <div class=\"nx-callout-title\">Quick answer<\/div>\n    <p>Liveness detection helps confirm that a live person is present during identity verification. It is most effective when combined with document checks, biometric matching, AML screening and a clear risk based onboarding process.<\/p>\n  <\/div>\n\n  <h2 id=\"what-is-liveness-detection\"><span class=\"ez-toc-section\" id=\"What_is_Liveness_Detection\"><\/span>What is Liveness Detection?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n  <p>Liveness detection is a technology used during biometric verification. It checks whether the person interacting with the system is real and present at the time of the check.<\/p>\n\n  <p>In practice, this may involve facial movement, depth checks, texture analysis, device signals or other controls. The goal is to help detect presentation attacks and other attempts to fool the verification process.<\/p>\n\n  <p>NIST describes a presentation attack as the presentation of an artefact or human characteristic to a biometric capture system in a way that is intended to interfere with system policy. This can include impersonation or evasion attempts. <a href=\"https:\/\/pages.nist.gov\/frvt\/html\/frvt_pad.html\" class=\"nx-inline-link\">Read NIST&#8217;s overview of presentation attack detection<\/a>.<\/p>\n\n  <h2 id=\"why-liveness-detection-matters\"><span class=\"ez-toc-section\" id=\"Why_Liveness_Detection_Matters_for_Digital_Onboarding\"><\/span>Why Liveness Detection Matters for Digital Onboarding<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n  <p>Remote onboarding creates a simple challenge. The business needs to verify identity without seeing the customer in person. That gap can be exploited by fraudsters.<\/p>\n\n  <p>For example, a fraudster may use a stolen ID document and submit a photo that appears to match it. Another person may attempt to open mule accounts with synthetic identity details. In more complex cases, manipulated videos or deepfake style content may be used to bypass weak checks.<\/p>\n\n  <p>Therefore, a basic document upload is no longer enough for many regulated businesses. Identity checks need to test both the document and the person presenting it.<\/p>\n\n  <div class=\"nx-grid\">\n    <div class=\"nx-card\">\n      <div class=\"nx-card-icon\"><svg viewBox=\"0 0 20 20\"><path d=\"M4 2h12a1 1 0 011 1v14a1 1 0 01-1 1H4a1 1 0 01-1-1V3a1 1 0 011-1zm2 4h8V4H6v2zm0 4h8V8H6v2zm0 4h5v-2H6v2z\"\/><\/svg><\/div>\n      <h4>Document Fraud<\/h4>\n      <p>Fake, edited, stolen or expired documents may be submitted during onboarding.<\/p>\n    <\/div>\n    <div class=\"nx-card\">\n      <div class=\"nx-card-icon\"><svg viewBox=\"0 0 20 20\"><path d=\"M10 10a4 4 0 100-8 4 4 0 000 8zm0 2c-4 0-7 2-7 4.5V18h14v-1.5C17 14 14 12 10 12z\"\/><\/svg><\/div>\n      <h4>Impersonation<\/h4>\n      <p>A person may attempt to pass verification using another person&#8217;s identity details.<\/p>\n    <\/div>\n    <div class=\"nx-card\">\n      <div class=\"nx-card-icon\"><svg viewBox=\"0 0 20 20\"><path d=\"M10 1L3 5v6c0 4.25 3 8.22 7 9 4-.78 7-4.75 7-9V5l-7-4zm0 2.18l5 2.78V11c0 3.13-2.18 6.07-5 6.93C7.18 17.07 5 14.13 5 11V5.96l5-2.78z\"\/><\/svg><\/div>\n      <h4>Deepfake Risk<\/h4>\n      <p>Generated or manipulated media can increase the difficulty of remote identity checks.<\/p>\n    <\/div>\n    <div class=\"nx-card\">\n      <div class=\"nx-card-icon\"><svg viewBox=\"0 0 20 20\"><path d=\"M3 3h14v2H3zm0 4h14v2H3zm0 4h10v2H3zm0 4h7v2H3z\"\/><\/svg><\/div>\n      <h4>Weak Audit Trails<\/h4>\n      <p>Poorly recorded checks make it harder to explain why a customer was approved.<\/p>\n    <\/div>\n  <\/div>\n\n  <h2 id=\"liveness-detection-and-biometric-verification\"><span class=\"ez-toc-section\" id=\"Liveness_Detection_and_Biometric_Verification\"><\/span>Liveness Detection and Biometric Verification<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n  <p>Liveness detection is closely linked to biometric verification, but it is not the same thing.<\/p>\n\n  <p>Biometric verification usually compares a person against a reference image. In onboarding, that reference image may come from an identity document. Liveness detection adds another layer by checking whether the person is live at the point of capture.<\/p>\n\n  <p>Together, these controls help answer two separate questions:<\/p>\n\n  <div class=\"nx-table-wrap\">\n    <table class=\"nx-table\">\n      <thead>\n        <tr>\n          <th>Control<\/th>\n          <th>Question it helps answer<\/th>\n          <th>Why it matters<\/th>\n        <\/tr>\n      <\/thead>\n      <tbody>\n        <tr>\n          <td><strong>Document Verification<\/strong><\/td>\n          <td>Does the identity document appear valid?<\/td>\n          <td>Supports the first layer of identity assurance.<\/td>\n        <\/tr>\n        <tr>\n          <td><strong>Biometric Matching<\/strong><\/td>\n          <td>Does the person match the document image?<\/td>\n          <td>Helps detect basic impersonation risk.<\/td>\n        <\/tr>\n        <tr>\n          <td><strong>Liveness Detection<\/strong><\/td>\n          <td>Is a real person present during the check?<\/td>\n          <td>Helps reduce spoofing and remote attack risk.<\/td>\n        <\/tr>\n        <tr>\n          <td><strong>AML Screening<\/strong><\/td>\n          <td>Does the verified person create financial crime risk?<\/td>\n          <td>Connects identity assurance with compliance decisions.<\/td>\n        <\/tr>\n      <\/tbody>\n    <\/table>\n  <\/div>\n\n  <h2 id=\"common-attack-types\"><span class=\"ez-toc-section\" id=\"Common_Attack_Types_Liveness_Detection_Can_Help_Address\"><\/span>Common Attack Types Liveness Detection Can Help Address<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n  <p>Fraud methods vary by sector and market. However, several attack types appear across digital onboarding environments.<\/p>\n\n  <div class=\"nx-obligations\">\n    <div class=\"nx-obl-item\">\n      <h4>Photo and screen replay attacks<\/h4>\n      <p>A fraudster may hold up a printed photo, use an image on another screen or replay a video during the verification process.<\/p>\n    <\/div>\n    <div class=\"nx-obl-item\">\n      <h4>Mask and presentation attacks<\/h4>\n      <p>Physical artefacts may be used to imitate another person or bypass basic biometric checks.<\/p>\n    <\/div>\n    <div class=\"nx-obl-item\">\n      <h4>Manipulated or generated media<\/h4>\n      <p>AI generated images, edited videos and synthetic media can make remote identity checks harder to assess.<\/p>\n    <\/div>\n    <div class=\"nx-obl-item\">\n      <h4>Injection attacks<\/h4>\n      <p>Some attacks attempt to bypass the camera and inject images or video into the verification flow.<\/p>\n    <\/div>\n  <\/div>\n\n  <p>ENISA has also highlighted remote identity proofing risks and countermeasures, including threats linked to document capture, biometric checks and video based verification. <a href=\"https:\/\/www.enisa.europa.eu\/sites\/default\/files\/publications\/ENISA%20Report%20-%20Remote%20Identity%20Proofing%20-%20Attacks%20%26%20Countermeasures.pdf\" class=\"nx-inline-link\">Read ENISA&#8217;s remote identity proofing report<\/a>.<\/p>\n\n  <h2 id=\"where-liveness-fits-in-aml\"><span class=\"ez-toc-section\" id=\"Where_Liveness_Detection_Fits_in_AML_Compliance\"><\/span>Where Liveness Detection Fits in AML Compliance<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n  <p>Liveness detection is not an AML control on its own. Instead, it supports the identity verification stage of customer due diligence.<\/p>\n\n  <p>Once identity has been checked, regulated businesses still need to assess financial crime risk. That may include PEP and sanctions screening, <a href=\"\/solutions\/membercheck\/adverse-media-screening\/\" class=\"nx-inline-link\">adverse media screening<\/a>, <a href=\"\/solutions\/membercheck\/aml-risk-assessment\/\" class=\"nx-inline-link\">AML risk assessment<\/a>, beneficial ownership checks for businesses and ongoing monitoring.<\/p>\n\n  <p>FATF&#8217;s digital identity guidance notes that reliable digital ID can support customer due diligence and help financial institutions identify and verify individuals. <a href=\"https:\/\/www.fatf-gafi.org\/en\/publications\/Financialinclusionandnpoissues\/Digital-identity-guidance.html\" class=\"nx-inline-link\">Read FATF&#8217;s guidance on digital identity<\/a>.<\/p>\n\n  <div class=\"nx-callout nx-callout--warning\">\n    <div class=\"nx-callout-title\">Compliance note<\/div>\n    <p>Liveness detection should be part of a wider risk based process. It should not be treated as proof that a customer is low risk, legitimate or suitable for onboarding.<\/p>\n  <\/div>\n\n  <h2 id=\"what-to-look-for\"><span class=\"ez-toc-section\" id=\"What_to_Look_for_in_a_Liveness_Detection_Workflow\"><\/span>What to Look for in a Liveness Detection Workflow<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n  <p>Before selecting or reviewing a liveness detection workflow, decision makers should look beyond the user interface. A smooth customer experience is valuable, but the control must also be reliable, auditable and suitable for the business risk profile.<\/p>\n\n  <p>Important questions include:<\/p>\n\n  <ul>\n    <li>Does the workflow combine document checks, biometric matching and liveness detection?<\/li>\n    <li>Can the system detect common presentation attacks, such as photos and screen replays?<\/li>\n    <li>How does the solution address manipulated media and injection attack risk?<\/li>\n    <li>Can the results be reviewed by compliance or fraud teams when needed?<\/li>\n    <li>Are decisions recorded in a way that supports audit and investigation?<\/li>\n    <li>Can identity data flow into PEP, sanctions and adverse media screening?<\/li>\n    <li>Is the onboarding process configurable by customer, region or risk level?<\/li>\n  <\/ul>\n\n  <p>These questions help teams assess whether the process supports real risk control, rather than only adding a visible biometric step.<\/p>\n\n  <h2 id=\"how-nexiant-supports-idv\"><span class=\"ez-toc-section\" id=\"How_Nexiant_Supports_Identity_Verification_Workflows\"><\/span>How Nexiant Supports Identity Verification Workflows<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n  <p>Nexiant brings together fraud prevention and risk management capabilities that support digital onboarding. Through <a href=\"\/solutions\/membercheck\/id-verification\/\" class=\"nx-inline-link\">MemberCheck ID Verification<\/a>, businesses can verify identity documents, use biometric checks, assess liveness and connect identity verification with AML screening workflows.<\/p>\n\n  <p>This joined approach is important. In many businesses, identity verification, fraud review and compliance checks are handled across different systems. As a result, teams may lose context between onboarding and ongoing monitoring.<\/p>\n\n  <p>By connecting identity verification with screening and risk assessment, businesses can create a more consistent customer view from the first interaction. That helps reduce manual work, improve decision records and support stronger risk based onboarding.<\/p>\n\n  <hr class=\"nx-divider\">\n\n  <h2 id=\"frequently-asked-questions\"><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions\"><\/span>Frequently Asked Questions<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n  <div class=\"nx-faq\">\n    <div class=\"nx-faq-item\">\n      <button class=\"nx-faq-q\" aria-expanded=\"false\">What is liveness detection?<span class=\"nx-chevron\"><svg viewBox=\"0 0 10 6\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M1 1l4 4 4-4\"\/><\/svg><\/span><\/button>\n      <div class=\"nx-faq-a\">Liveness detection is a biometric control that checks whether a real person is present during identity verification. It helps detect attempts to use a photo, video, mask, screen replay or manipulated media instead of a live person.<\/div>\n    <\/div>\n    <div class=\"nx-faq-item\">\n      <button class=\"nx-faq-q\" aria-expanded=\"false\">How does liveness detection help reduce onboarding fraud?<span class=\"nx-chevron\"><svg viewBox=\"0 0 10 6\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M1 1l4 4 4-4\"\/><\/svg><\/span><\/button>\n      <div class=\"nx-faq-a\">Liveness detection can help reduce onboarding fraud by making it harder for fraudsters to pass checks using stolen documents, static photos, replayed videos or other spoofing methods. It is most effective when used with document verification and biometric matching.<\/div>\n    <\/div>\n    <div class=\"nx-faq-item\">\n      <button class=\"nx-faq-q\" aria-expanded=\"false\">Is liveness detection the same as biometric verification?<span class=\"nx-chevron\"><svg viewBox=\"0 0 10 6\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M1 1l4 4 4-4\"\/><\/svg><\/span><\/button>\n      <div class=\"nx-faq-a\">No. Biometric verification usually checks whether a person matches a reference image, such as a passport or driving licence photo. Liveness detection checks whether the person is live and present at the time of the verification.<\/div>\n    <\/div>\n    <div class=\"nx-faq-item\">\n      <button class=\"nx-faq-q\" aria-expanded=\"false\">Can liveness detection stop deepfake fraud?<span class=\"nx-chevron\"><svg viewBox=\"0 0 10 6\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M1 1l4 4 4-4\"\/><\/svg><\/span><\/button>\n      <div class=\"nx-faq-a\">Liveness detection can help reduce some forms of deepfake and manipulated media risk, but it should not be used alone. Businesses should combine it with document verification, biometric matching, device and behavioural controls, screening and manual review where risk is higher.<\/div>\n    <\/div>\n    <div class=\"nx-faq-item\">\n      <button class=\"nx-faq-q\" aria-expanded=\"false\">Why does liveness detection matter for AML compliance?<span class=\"nx-chevron\"><svg viewBox=\"0 0 10 6\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M1 1l4 4 4-4\"\/><\/svg><\/span><\/button>\n      <div class=\"nx-faq-a\">Liveness detection matters for AML compliance because it strengthens the identity verification stage of customer due diligence. However, AML compliance still requires wider risk checks, including PEP screening, sanctions screening, adverse media checks, risk assessment and ongoing monitoring.<\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"nx-cta\">\n    <h3>Strengthen identity checks across digital onboarding<\/h3>\n    <p>Nexiant helps regulated businesses connect liveness detection, digital ID verification, AML screening and customer risk assessment in a more consistent onboarding workflow.<\/p>\n    <a href=\"https:\/\/nexiant.ai\/contact-us\/\">Speak to our identity verification team<\/a>\n  <\/div>\n\n  <p class=\"nx-disclaimer\">This article was accurate at the time of publication in June 2026 and is intended for general informational purposes only. It does not constitute legal, regulatory or compliance advice. Organisations should seek qualified professional counsel in relation to their specific obligations.<\/p>\n\n<\/div>\n\n<script>\n  document.querySelectorAll('.nx-faq-q').forEach(function(btn) {\n    btn.addEventListener('click', function() {\n      var expanded = this.getAttribute('aria-expanded') === 'true';\n      this.setAttribute('aria-expanded', !expanded);\n      this.nextElementSibling.classList.toggle('open', !expanded);\n    });\n  });\n<\/script>\n\n<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What is liveness detection?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Liveness detection is a biometric control that checks whether a real person is present during identity verification. It helps detect attempts to use a photo, video, mask, screen replay or manipulated media instead of a live person.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"How does liveness detection help reduce onboarding fraud?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Liveness detection can help reduce onboarding fraud by making it harder for fraudsters to pass checks using stolen documents, static photos, replayed videos or other spoofing methods. It is most effective when used with document verification and biometric matching.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Is liveness detection the same as biometric verification?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"No. Biometric verification usually checks whether a person matches a reference image, such as a passport or driving licence photo. Liveness detection checks whether the person is live and present at the time of the verification.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can liveness detection stop deepfake fraud?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Liveness detection can help reduce some forms of deepfake and manipulated media risk, but it should not be used alone. Businesses should combine it with document verification, biometric matching, device and behavioural controls, screening and manual review where risk is higher.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Why does liveness detection matter for AML compliance?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Liveness detection matters for AML compliance because it strengthens the identity verification stage of customer due diligence. However, AML compliance still requires wider risk checks, including PEP screening, sanctions screening, adverse media checks, risk assessment and ongoing monitoring.\"\n      }\n    }\n  ]\n}\n<\/script>\n","protected":false},"excerpt":{"rendered":"<p>Fraud Prevention Guide &nbsp;\u00b7&nbsp; June 2026 &nbsp;\u00b7&nbsp; Global Focus Liveness detection helps regulated businesses check whether a real person is present during digital onboarding. As identity fraud becomes more sophisticated, it is becoming a practical control for reducing remote onboarding risk. Liveness detection is now an important part of digital onboarding. It helps businesses check [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":492,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[48,15],"tags":[],"class_list":["post-491","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-identity-verification","category-risk-management"],"blocksy_meta":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/nexiant.ai\/resources\/blogs\/wp-json\/wp\/v2\/posts\/491","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nexiant.ai\/resources\/blogs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/nexiant.ai\/resources\/blogs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/nexiant.ai\/resources\/blogs\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/nexiant.ai\/resources\/blogs\/wp-json\/wp\/v2\/comments?post=491"}],"version-history":[{"count":2,"href":"https:\/\/nexiant.ai\/resources\/blogs\/wp-json\/wp\/v2\/posts\/491\/revisions"}],"predecessor-version":[{"id":494,"href":"https:\/\/nexiant.ai\/resources\/blogs\/wp-json\/wp\/v2\/posts\/491\/revisions\/494"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/nexiant.ai\/resources\/blogs\/wp-json\/wp\/v2\/media\/492"}],"wp:attachment":[{"href":"https:\/\/nexiant.ai\/resources\/blogs\/wp-json\/wp\/v2\/media?parent=491"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/nexiant.ai\/resources\/blogs\/wp-json\/wp\/v2\/categories?post=491"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/nexiant.ai\/resources\/blogs\/wp-json\/wp\/v2\/tags?post=491"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}