{"id":14467,"date":"2026-10-14T10:57:19","date_gmt":"2026-10-14T00:57:19","guid":{"rendered":"https:\/\/namescan.io\/insights\/?p=14467"},"modified":"2026-10-14T10:57:19","modified_gmt":"2026-10-14T00:57:19","slug":"ai-sanctions-pep-screening","status":"publish","type":"post","link":"https:\/\/namescan.io\/insights\/ai-sanctions-pep-screening\/","title":{"rendered":"A Name Match Is Not a Risk Decision: The Future of Compliance Screening"},"content":{"rendered":"\r\n<style>\r\n#ns-wave1.ns-blog p,#ns-wave1.ns-blog li,#ns-wave1.ns-blog td,#ns-wave1.ns-blog th{font-family:inherit;color:#2E2E2E;letter-spacing:normal;text-transform:none}\r\n#ns-wave1.ns-blog p,#ns-wave1.ns-blog li{font-size:17px;line-height:1.75;font-weight:400}\r\n#ns-wave1.ns-blog strong,#ns-wave1.ns-blog b{font-weight:700}\r\n#ns-wave1.ns-blog,#ns-wave1.ns-blog p,#ns-wave1.ns-blog li,#ns-wave1.ns-blog h2,#ns-wave1.ns-blog h3,#ns-wave1.ns-blog h4,#ns-wave1.ns-blog td,#ns-wave1.ns-blog th,#ns-wave1.ns-blog 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.ns-d{display:none}#ns-wave1 .ns-fig .ns-m{display:block}#ns-wave1 .ns-cta{padding:25.6px 20.8px}}\r\n#ns-wave1 .ns-card{text-align:center;border-radius:16px}\r\n#ns-wave1 .ns-pill{border-radius:30px;padding:9.6px 12.8px;font-weight:700;color:#fff;border:1.5px dashed #A9E3E1}\r\n#ns-wave1 .ns-pill.ok{background:#46C1BE;color:#0B1F3A;border:0}\r\n#ns-wave1 .ns-ne{font-size:30.4px;font-weight:800;color:#46C1BE;line-height:1;margin:5.6px 0}\r\n#ns-wave1 .ns-card small{text-align:left}\r\n<\/style>\r\n<div id=\"ns-wave1\" class=\"ns-blog\"><div class=\"ns-wrap\">\r\n<div class=\"ns-hero\"><div><span class=\"ns-tag\">Thought leadership&nbsp;\u00b7&nbsp;Decision AI&nbsp;\u00b7&nbsp;PEP &amp; sanctions screening<\/span><p class=\"ns-sub\">Learn why PEP and sanctions screening requires more than matching names, and how contextual Decision AI could support more confident review decisions.<\/p><\/div><div class=\"ns-card\" aria-label=\"Name matching versus identity confirmation\"><div class=\"ns-card-h\">The screening distinction<\/div><div class=\"ns-pill\">Potential name match<\/div><div class=\"ns-ne\" aria-label=\"does not necessarily equal\">\u2260<\/div><div class=\"ns-pill ok\">Confirmed identity match<\/div><small>Name similarity is a lead. Identity assessment requires corroborating evidence and review.<\/small><\/div><\/div>\r\n <p class=\"ns-lead\"><strong>A sanctions or PEP name match is a potential lead, not proof that your customer is the person on a watchlist.<\/strong> Effective screening finds relevant records and then establishes whether the records really refer to the person or organisation being checked. The next opportunity for Decision AI is to help assess that second question using more context than name similarity alone.<\/p> <p>This matters to businesses screening a handful of customers and to teams processing thousands of onboarding checks. An unnecessary escalation costs time. An incorrectly dismissed potential match may expose the business to significant risk. The objective is not to eliminate review; it is to make review more relevant and evidence-led.<\/p> <h2 id=\"what-does-an-aml-screening-check-actually-do\">What does an AML screening check actually do?<\/h2> <p>NameScan provides <a href=\"https:\/\/namescan.io\/pricing\">pay-as-you-go checks<\/a> for politically exposed persons (PEPs), sanctions and <a href=\"https:\/\/namescan.io\/adversemedia\">adverse media<\/a>, with separate identity verification and business verification services available. A user can enter details, search relevant data sources and review possible records. The result helps inform customer due diligence; it does not by itself establish legal sanctions status, customer suitability or the appropriate level of due diligence.<\/p> <p>For example, suppose your customer is named <strong>Alex Morgan<\/strong>. A screening result returns a public record for a person with the same name. That is a reason to compare details, not automatically a reason to reject the customer. Conversely, a slightly different spelling may still refer to the same individual when aliases or transliterations are considered.<\/p> <p>An effective screening workflow must therefore distinguish between <strong>record retrieval<\/strong> and <strong>identity resolution<\/strong>.<\/p> <figure aria-label=\"A SCREENING HIT IS THE START OF A MATCH ASSESSMENT. Proposed contextual matching support, not autonomous sanctions determination\" class=\"ns-fig\" role=\"group\"><div aria-label=\"A SCREENING HIT IS THE START OF A MATCH ASSESSMENT. Proposed contextual matching support, not autonomous sanctions determination\" class=\"ns-d\" role=\"img\"><svg baseprofile=\"full\" height=\"460px\" version=\"1.1\" viewbox=\"0 0 1200 460\" width=\"1200px\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" xmlns:ev=\"http:\/\/www.w3.org\/2001\/xml-events\" xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\"> <defs> <marker id=\"ns_match_workflow_desk_arrow\" markerheight=\"10\" markerunits=\"userSpaceOnUse\" markerwidth=\"10\" orient=\"auto\" refx=\"9\" refy=\"5\"> <path d=\"M0,0 L10,5 L0,10 Z\" fill=\"#A1B0C3\"><\/path> <\/marker> <\/defs> <rect fill=\"white\" height=\"460\" width=\"1200\" x=\"0\" y=\"0\"><\/rect> <title>A SCREENING HIT IS THE START OF A MATCH ASSESSMENT<\/title> <desc>Proposed contextual matching support, not autonomous sanctions determination; An AI output cannot establish whether a person is formally listed or replace authoritative data.<\/desc> <rect fill=\"#46C1BE\" height=\"8\" width=\"1200\" x=\"0\" y=\"0\"><\/rect> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"25\" font-weight=\"bold\" x=\"30\" y=\"50\">A SCREENING HIT IS THE START OF A MATCH ASSESSMENT<\/text> <text fill=\"#455B70\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"15\" font-weight=\"normal\" x=\"30\" y=\"83\">Proposed contextual matching support, not autonomous sanctions determination<\/text> <rect fill=\"#F8FAFD\" height=\"218\" rx=\"15\" stroke=\"#C9D5E1\" stroke-width=\"2.2\" width=\"262.75\" x=\"31.0\" y=\"150\"><\/rect> <rect fill=\"#D5DEE8\" height=\"216\" rx=\"3\" width=\"6\" x=\"32.0\" y=\"151\"><\/rect> <circle cx=\"66.0\" cy=\"190\" fill=\"white\" r=\"26\" stroke=\"#D5DEE8\" stroke-width=\"1.3\"><\/circle> <g fill=\"none\" stroke=\"#0B1F3A\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2.9\"> <circle cx=\"63.0\" cy=\"185\" r=\"12\"><\/circle> <line x1=\"72.0\" x2=\"83.0\" y1=\"194\" y2=\"206\"><\/line> <\/g> <circle cx=\"264.75\" cy=\"181\" fill=\"#0B1F3A\" r=\"14\"><\/circle> <text fill=\"white\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"bold\" text-anchor=\"middle\" x=\"264.75\" y=\"187\">1<\/text> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"bold\" x=\"48.0\" y=\"239\">Screening<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"normal\" x=\"48.0\" y=\"274\">Check a person or entity<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"normal\" x=\"48.0\" y=\"297\">against PEP, sanctions<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"normal\" x=\"48.0\" y=\"320\">and adverse-media sources<\/text> <line marker-end=\"url(#ns_match_workflow_desk_arrow)\" stroke=\"#A1B0C3\" stroke-width=\"3.4\" x1=\"298.75\" x2=\"313.75\" y1=\"259.0\" y2=\"259.0\"><\/line> <rect fill=\"#F8FAFD\" height=\"218\" rx=\"15\" stroke=\"#C9D5E1\" stroke-width=\"2.2\" width=\"262.75\" x=\"322.75\" y=\"150\"><\/rect> <rect fill=\"#D5DEE8\" height=\"216\" rx=\"3\" width=\"6\" x=\"323.75\" y=\"151\"><\/rect> <circle cx=\"357.75\" cy=\"190\" fill=\"white\" r=\"26\" stroke=\"#D5DEE8\" stroke-width=\"1.3\"><\/circle> <g fill=\"none\" stroke=\"#0B1F3A\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2.9\"> <path d=\"M345.75 173 h18 l8 8 v24 h-26 Z M363.75 173 v8 h8 M350.75 193 h14 M350.75 199 h12\"><\/path> <\/g> <circle cx=\"556.5\" cy=\"181\" fill=\"#0B1F3A\" r=\"14\"><\/circle> <text fill=\"white\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"bold\" text-anchor=\"middle\" x=\"556.5\" y=\"187\">2<\/text> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"bold\" x=\"339.75\" y=\"239\">Candidate record<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" 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Helvetica, sans-serif\" font-size=\"17\" font-weight=\"bold\" text-anchor=\"middle\" x=\"848.25\" y=\"187\">3<\/text> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"bold\" x=\"631.5\" y=\"239\">Identity context<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"normal\" x=\"631.5\" y=\"274\">Proposed System 1-style<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"normal\" x=\"631.5\" y=\"297\">evaluation of corroborating<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"normal\" x=\"631.5\" y=\"320\">and conflicting attributes<\/text> <line marker-end=\"url(#ns_match_workflow_desk_arrow)\" stroke=\"#A1B0C3\" stroke-width=\"3.4\" x1=\"882.25\" x2=\"897.25\" y1=\"259.0\" y2=\"259.0\"><\/line> <rect fill=\"#F8FAFD\" height=\"218\" rx=\"15\" stroke=\"#C9D5E1\" stroke-width=\"2.2\" width=\"262.75\" x=\"906.25\" y=\"150\"><\/rect> <rect fill=\"#D5DEE8\" height=\"216\" rx=\"3\" width=\"6\" x=\"907.25\" y=\"151\"><\/rect> <circle cx=\"941.25\" cy=\"190\" fill=\"white\" r=\"26\" stroke=\"#D5DEE8\" stroke-width=\"1.3\"><\/circle> <g fill=\"none\" stroke=\"#0B1F3A\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2.9\"> <circle cx=\"941.25\" cy=\"182\" r=\"7\"><\/circle> <path d=\"M925.25 205 c0 -17 32 -17 32 0\"><\/path> <\/g> <circle cx=\"1140.0\" cy=\"181\" fill=\"#0B1F3A\" r=\"14\"><\/circle> <text fill=\"white\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"bold\" text-anchor=\"middle\" x=\"1140.0\" y=\"187\">4<\/text> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"bold\" x=\"923.25\" y=\"239\">Evidence-led review<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"normal\" x=\"923.25\" y=\"274\">Apply thresholds and source<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"normal\" x=\"923.25\" y=\"297\">checks; review, document<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"normal\" x=\"923.25\" y=\"320\">and escalate as appropriate<\/text> <line stroke=\"#DDE5EE\" stroke-width=\"1.3\" x1=\"28\" x2=\"1172\" y1=\"408\" y2=\"408\"><\/line> <text fill=\"#455B70\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"15\" font-weight=\"normal\" x=\"28\" y=\"435\">An AI output cannot establish whether a person is formally listed or replace authoritative data.<\/text> <\/svg><\/div><div aria-label=\"A SCREENING HIT IS THE START OF A MATCH ASSESSMENT. Proposed contextual matching support, not autonomous sanctions determination\" class=\"ns-m\" role=\"img\"><svg baseprofile=\"full\" height=\"1147px\" version=\"1.1\" viewbox=\"0 0 620 1147\" width=\"620px\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" xmlns:ev=\"http:\/\/www.w3.org\/2001\/xml-events\" xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\"> <defs> <marker id=\"ns_match_workflow_mob_arrow\" markerheight=\"10\" markerunits=\"userSpaceOnUse\" markerwidth=\"10\" orient=\"auto\" refx=\"9\" refy=\"5\"> <path d=\"M0,0 L10,5 L0,10 Z\" fill=\"#A1B0C3\"><\/path> <\/marker> <\/defs> <rect fill=\"white\" height=\"1147\" width=\"620\" x=\"0\" y=\"0\"><\/rect> <title>A SCREENING HIT IS THE START OF A MATCH ASSESSMENT<\/title> <desc>Proposed contextual matching support, not autonomous sanctions determination; An AI output cannot establish whether a person is formally listed or replace authoritative data.<\/desc> <rect fill=\"#46C1BE\" height=\"8\" width=\"620\" x=\"0\" y=\"0\"><\/rect> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"21\" font-weight=\"bold\" x=\"30\" y=\"49\">A SCREENING HIT IS THE START OF A MATCH<\/text> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"21\" font-weight=\"bold\" x=\"30\" y=\"76\">ASSESSMENT<\/text> <text fill=\"#455B70\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"14\" font-weight=\"normal\" x=\"30\" y=\"110\">Proposed contextual matching support, not autonomous sanctions<\/text> <text fill=\"#455B70\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"14\" font-weight=\"normal\" x=\"30\" y=\"128\">determination<\/text> <rect fill=\"#F8FAFD\" height=\"196\" rx=\"15\" stroke=\"#C9D5E1\" stroke-width=\"2.2\" width=\"562\" x=\"29\" y=\"167\"><\/rect> <rect fill=\"#D5DEE8\" height=\"194\" rx=\"3\" width=\"6\" x=\"30\" y=\"168\"><\/rect> <circle cx=\"64\" cy=\"207\" fill=\"white\" r=\"26\" stroke=\"#D5DEE8\" stroke-width=\"1.3\"><\/circle> <g fill=\"none\" stroke=\"#0B1F3A\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2.9\"> <circle cx=\"61\" cy=\"202\" r=\"12\"><\/circle> <line x1=\"70\" x2=\"81\" y1=\"211\" y2=\"223\"><\/line> <\/g> <circle cx=\"562\" cy=\"198\" fill=\"#0B1F3A\" r=\"14\"><\/circle> <text fill=\"white\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"bold\" text-anchor=\"middle\" x=\"562\" y=\"204\">1<\/text> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"23\" font-weight=\"bold\" x=\"46\" y=\"256\">Screening<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"293\">Check a person or entity<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"318\">against PEP, sanctions<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"343\">and adverse-media sources<\/text> <line marker-end=\"url(#ns_match_workflow_mob_arrow)\" stroke=\"#A1B0C3\" stroke-width=\"3.8\" x1=\"310.0\" x2=\"310.0\" y1=\"371\" y2=\"388\"><\/line> <rect fill=\"#F8FAFD\" height=\"196\" rx=\"15\" stroke=\"#C9D5E1\" stroke-width=\"2.2\" width=\"562\" x=\"29\" y=\"404\"><\/rect> <rect fill=\"#D5DEE8\" height=\"194\" rx=\"3\" width=\"6\" x=\"30\" y=\"405\"><\/rect> <circle cx=\"64\" cy=\"444\" fill=\"white\" r=\"26\" stroke=\"#D5DEE8\" stroke-width=\"1.3\"><\/circle> <g fill=\"none\" stroke=\"#0B1F3A\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2.9\"> <path d=\"M52 427 h18 l8 8 v24 h-26 Z M70 427 v8 h8 M57 447 h14 M57 453 h12\"><\/path> <\/g> <circle cx=\"562\" cy=\"435\" fill=\"#0B1F3A\" r=\"14\"><\/circle> <text fill=\"white\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"bold\" text-anchor=\"middle\" x=\"562\" y=\"441\">2<\/text> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"23\" font-weight=\"bold\" x=\"46\" y=\"493\">Candidate record<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"530\">A similar name or related<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"555\">record is returned for<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"580\">identity assessment<\/text> <line marker-end=\"url(#ns_match_workflow_mob_arrow)\" stroke=\"#A1B0C3\" stroke-width=\"3.8\" x1=\"310.0\" x2=\"310.0\" y1=\"608\" y2=\"625\"><\/line> <rect fill=\"#EAF8F7\" height=\"196\" rx=\"15\" stroke=\"#46C1BE\" stroke-width=\"2.2\" width=\"562\" x=\"29\" y=\"641\"><\/rect> <rect fill=\"#46C1BE\" height=\"194\" rx=\"3\" width=\"6\" x=\"30\" y=\"642\"><\/rect> <circle cx=\"64\" cy=\"681\" fill=\"white\" r=\"26\" stroke=\"#46C1BE\" stroke-width=\"1.3\"><\/circle> <g fill=\"none\" stroke=\"#46C1BE\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2.9\"> <rect height=\"24\" rx=\"5\" width=\"24\" x=\"52\" y=\"668\"><\/rect> <circle cx=\"64\" cy=\"680\" r=\"4\"><\/circle> <line x1=\"56\" x2=\"56\" y1=\"663\" y2=\"668\"><\/line> <line x1=\"56\" x2=\"56\" y1=\"692\" y2=\"697\"><\/line> <line x1=\"64\" x2=\"64\" y1=\"663\" y2=\"668\"><\/line> <line x1=\"64\" x2=\"64\" y1=\"692\" y2=\"697\"><\/line> <line x1=\"72\" x2=\"72\" y1=\"663\" y2=\"668\"><\/line> <line x1=\"72\" x2=\"72\" y1=\"692\" y2=\"697\"><\/line> <line x1=\"47\" x2=\"52\" y1=\"672\" y2=\"672\"><\/line> <line x1=\"76\" x2=\"81\" y1=\"672\" y2=\"672\"><\/line> <line x1=\"47\" x2=\"52\" y1=\"680\" y2=\"680\"><\/line> <line x1=\"76\" x2=\"81\" y1=\"680\" y2=\"680\"><\/line> <line x1=\"47\" x2=\"52\" y1=\"688\" y2=\"688\"><\/line> <line x1=\"76\" x2=\"81\" y1=\"688\" y2=\"688\"><\/line> <\/g> <circle cx=\"562\" cy=\"672\" fill=\"#0B1F3A\" r=\"14\"><\/circle> <text fill=\"white\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"bold\" text-anchor=\"middle\" x=\"562\" y=\"678\">3<\/text> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"23\" font-weight=\"bold\" x=\"46\" y=\"730\">Identity context<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"767\">Proposed System 1-style<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"792\">evaluation of corroborating<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"817\">and conflicting attributes<\/text> <line marker-end=\"url(#ns_match_workflow_mob_arrow)\" stroke=\"#A1B0C3\" stroke-width=\"3.8\" x1=\"310.0\" x2=\"310.0\" y1=\"845\" y2=\"862\"><\/line> <rect fill=\"#F8FAFD\" height=\"196\" rx=\"15\" stroke=\"#C9D5E1\" stroke-width=\"2.2\" width=\"562\" x=\"29\" y=\"878\"><\/rect> <rect fill=\"#D5DEE8\" height=\"194\" rx=\"3\" width=\"6\" x=\"30\" y=\"879\"><\/rect> <circle cx=\"64\" cy=\"918\" fill=\"white\" r=\"26\" stroke=\"#D5DEE8\" stroke-width=\"1.3\"><\/circle> <g fill=\"none\" stroke=\"#0B1F3A\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2.9\"> <circle cx=\"64\" cy=\"910\" r=\"7\"><\/circle> <path d=\"M48 933 c0 -17 32 -17 32 0\"><\/path> <\/g> <circle cx=\"562\" cy=\"909\" fill=\"#0B1F3A\" r=\"14\"><\/circle> <text fill=\"white\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"bold\" text-anchor=\"middle\" x=\"562\" y=\"915\">4<\/text> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"23\" font-weight=\"bold\" x=\"46\" y=\"967\">Evidence-led review<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"1004\">Apply thresholds and source<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"1029\">checks; review, document<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"18\" font-weight=\"normal\" x=\"46\" y=\"1054\">and escalate as appropriate<\/text> <\/svg><\/div><figcaption>A potential watchlist or adverse-media match requires evidence-based identity assessment before a screening disposition is recorded.<em>Figure 1. Conceptual workflow. The System 1-style contextual layer is a prospective application, not a claimed live NameScan feature.<\/em><\/figcaption><\/figure>  <h2 id=\"why-exact-and-fuzzy-matching-are-only-part-of-the-answer\">Why exact and fuzzy matching are only part of the answer<\/h2> <p>Exact matching is useful when records share the same spelling. Fuzzy matching can surface alternate spellings, transcription differences and typographical variation. Both are useful screening techniques, but neither alone answers the full identity question.<\/p> <p>Consider the information that might be available:<\/p> <div class=\"ns-table\"><table>  <thead> <tr> <th>Signal<\/th> <th>What it can help establish<\/th> <th>Important limitation<\/th> <\/tr> <\/thead> <tbody> <tr> <td>Name and aliases<\/td> <td>Similarity across spelling and known variants<\/td> <td>Common names can yield many candidates<\/td> <\/tr> <tr> <td>Date of birth<\/td> <td>Whether identity records align<\/td> <td>Records may be incomplete or approximate<\/td> <\/tr> <tr> <td>Nationality \/ geography<\/td> <td>Whether jurisdictional context is consistent<\/td> <td>People relocate; nationality is not unique<\/td> <\/tr> <tr> <td>Associated entities<\/td> <td>Whether relevant organisations or relationships match<\/td> <td>Relationships can be outdated<\/td> <\/tr> <tr> <td>Adverse-media context<\/td> <td>Whether a report relates to the screened subject<\/td> <td>Media reports may be ambiguous or inaccurate<\/td> <\/tr> <\/tbody> <\/table><\/div> <p>The challenge is contextual. One mismatch may be decisive when the evidence is reliable; another may simply reflect incomplete public data. This is why a screening decision should be supported by the actual available identifiers and a review process, rather than a similarity percentage alone.<\/p> <h2 id=\"where-could-system-1-style-decision-ai-help\">Where could System 1-style Decision AI help?<\/h2> <p>A System 1-style decision model can be asked to select from a small, defined set of outcomes using the context supplied to it. For a potential screening hit, examples of narrow questions include:<\/p> <ul> <li><strong>Identity consistency:<\/strong> Do the available identifiers support treating these two records as the same person?<\/li> <li><strong>Evidence sufficiency:<\/strong> Is there enough reliable information for a preliminary match assessment?<\/li> <li><strong>Classification:<\/strong> Does the case appear to be an unlikely match, a possible match or a potentially strong match requiring review?<\/li> <li><strong>Review routing:<\/strong> Should the result be reviewed by a human because key identifiers conflict or are missing?<\/li> <\/ul> <p>This may create a more structured triage process than an unrestricted AI summary. It does not give the model authority to change a sanctions list, determine the legal effect of a designation or certify that a customer is safe.<\/p> <p>TypeSafe\u2019s Jev model, introduced in September 2026, is an example of this emerging class of typed, probabilistic decision technology. A product implementation would still need controlled inputs, validation on real screening cases, local policies, audit trails and human escalation.<\/p> <h2 id=\"two-customers-can-have-the-same-name-but-very-different-evidence\">Two customers can have the same name but very different evidence<\/h2> <p>Imagine two illustrative screening cases involving the same common name.<\/p> <div class=\"ns-grid\"><div class=\"ns-item\"><h4>Case A<\/h4><p>The name matches, but the date of birth differs substantially and the public profile relates to an individual in a different location with a distinct employment history. The review process may have grounds to treat the hit as an unlikely match, subject to data quality and policy.<\/p><\/div><div class=\"ns-item\"><h4>Case B<\/h4><p>The name matches, several aliases align and the date of birth and associated company details are consistent. This is a much stronger potential match and merits closer investigation before any disposition.<\/p><\/div><\/div>  <p>Neither conclusion follows from the name alone. Even a strong identity match should be assessed against the underlying authoritative record, its date, the relevant legal requirements and the organisation\u2019s risk appetite.<\/p> <figure aria-label=\"IDENTICAL NAMES CAN SUPPORT DIFFERENT ASSESSMENTS. Illustrative examples only \u2014 attributes and source reliability both matter\" class=\"ns-fig\" role=\"group\"><div aria-label=\"IDENTICAL NAMES CAN SUPPORT DIFFERENT ASSESSMENTS. Illustrative examples only \u2014 attributes and source reliability both matter\" class=\"ns-d\" role=\"img\"><svg baseprofile=\"full\" height=\"560px\" version=\"1.1\" viewbox=\"0 0 1200 560\" width=\"1200px\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" xmlns:ev=\"http:\/\/www.w3.org\/2001\/xml-events\" xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\"> <defs> <marker id=\"ns_two_cases_desk_arrow\" markerheight=\"10\" markerunits=\"userSpaceOnUse\" markerwidth=\"10\" orient=\"auto\" refx=\"9\" refy=\"5\"> <path d=\"M0,0 L10,5 L0,10 Z\" fill=\"#A1B0C3\"><\/path> <\/marker> <\/defs> <rect fill=\"white\" height=\"560\" width=\"1200\" x=\"0\" y=\"0\"><\/rect> <title>IDENTICAL NAMES CAN SUPPORT DIFFERENT ASSESSMENTS<\/title> <desc>Illustrative examples only \u2014 attributes and source reliability both matter; Neither case is a final compliance determination. Human review follows applicable policy.<\/desc> <rect fill=\"#46C1BE\" height=\"8\" width=\"1200\" x=\"0\" y=\"0\"><\/rect> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"25\" font-weight=\"bold\" x=\"30\" y=\"50\">IDENTICAL NAMES CAN SUPPORT DIFFERENT ASSESSMENTS<\/text> <text fill=\"#455B70\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"15\" font-weight=\"normal\" x=\"30\" y=\"83\">Illustrative examples only \u2014 attributes and source reliability both matter<\/text> <rect fill=\"#F8FAFD\" height=\"142\" rx=\"15\" stroke=\"#C9D5E1\" stroke-width=\"2\" width=\"540\" x=\"30\" y=\"142\"><\/rect> <g fill=\"none\" stroke=\"#0B1F3A\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2.9\"> <circle cx=\"69\" cy=\"181\" r=\"12\"><\/circle> <line x1=\"78\" x2=\"89\" y1=\"190\" y2=\"202\"><\/line> <\/g> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"22\" font-weight=\"bold\" x=\"111\" y=\"190\">CASE A<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"normal\" x=\"57\" y=\"234\">Same name<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"normal\" x=\"57\" y=\"262\">DOB and other attributes conflict<\/text> <line marker-end=\"url(#ns_two_cases_desk_arrow)\" stroke=\"#A1B0C3\" stroke-width=\"3.6\" x1=\"300.0\" x2=\"300.0\" y1=\"291\" y2=\"328\"><\/line> <rect fill=\"#EAF8F7\" height=\"149\" rx=\"15\" stroke=\"#46C1BE\" stroke-width=\"2\" width=\"540\" x=\"30\" y=\"340\"><\/rect> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"19\" font-weight=\"bold\" x=\"54\" y=\"385\">WEAKER EVIDENCE OF A MATCH<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"16\" font-weight=\"normal\" x=\"54\" y=\"422\">Conflicts require source verification.<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"16\" font-weight=\"normal\" x=\"54\" y=\"459\">Do not treat as an automatic clearance.<\/text> <rect fill=\"#F8FAFD\" height=\"142\" rx=\"15\" stroke=\"#C9D5E1\" stroke-width=\"2\" width=\"540\" x=\"630\" y=\"142\"><\/rect> <g fill=\"none\" stroke=\"#0B1F3A\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2.9\"> <circle cx=\"669\" cy=\"181\" r=\"12\"><\/circle> <line x1=\"678\" x2=\"689\" y1=\"190\" y2=\"202\"><\/line> <\/g> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"22\" font-weight=\"bold\" x=\"711\" y=\"190\">CASE B<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"normal\" x=\"657\" y=\"234\">Same name<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"normal\" x=\"657\" y=\"262\">DOB and aliases corroborate<\/text> <line marker-end=\"url(#ns_two_cases_desk_arrow)\" stroke=\"#A1B0C3\" stroke-width=\"3.6\" x1=\"900.0\" x2=\"900.0\" y1=\"291\" y2=\"328\"><\/line> <rect fill=\"#EAF8F7\" height=\"149\" rx=\"15\" stroke=\"#46C1BE\" stroke-width=\"2\" width=\"540\" x=\"630\" y=\"340\"><\/rect> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"19\" font-weight=\"bold\" x=\"654\" y=\"385\">STRONGER EVIDENCE OF A MATCH<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"16\" font-weight=\"normal\" x=\"654\" y=\"422\">Prioritise verification against source records.<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"16\" font-weight=\"normal\" x=\"654\" y=\"459\">Do not treat as an automatic finding.<\/text> <line stroke=\"#DDE5EE\" stroke-width=\"1.3\" x1=\"28\" x2=\"1172\" y1=\"508\" y2=\"508\"><\/line> <text fill=\"#455B70\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"15\" font-weight=\"normal\" x=\"28\" y=\"535\">Neither case is a final compliance determination. Human review follows applicable policy.<\/text> <\/svg><\/div><div aria-label=\"IDENTICAL NAMES CAN SUPPORT DIFFERENT ASSESSMENTS. Illustrative examples only \u2014 attributes and source reliability both matter\" class=\"ns-m\" role=\"img\"><svg baseprofile=\"full\" height=\"1010px\" version=\"1.1\" viewbox=\"0 0 620 1010\" width=\"620px\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" xmlns:ev=\"http:\/\/www.w3.org\/2001\/xml-events\" xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\"> <defs> <marker id=\"ns_two_cases_mob_arrow\" markerheight=\"10\" markerunits=\"userSpaceOnUse\" markerwidth=\"10\" orient=\"auto\" refx=\"9\" refy=\"5\"> <path d=\"M0,0 L10,5 L0,10 Z\" fill=\"#A1B0C3\"><\/path> <\/marker> <\/defs> <rect fill=\"white\" height=\"1010\" width=\"620\" x=\"0\" y=\"0\"><\/rect> <title>IDENTICAL NAMES CAN SUPPORT DIFFERENT ASSESSMENTS<\/title> <desc>Illustrative examples only \u2014 attributes and source reliability both matter; Neither case is a final compliance determination. Human review follows applicable policy.<\/desc> <rect fill=\"#46C1BE\" height=\"8\" width=\"620\" x=\"0\" y=\"0\"><\/rect> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"21\" font-weight=\"bold\" x=\"30\" y=\"49\">IDENTICAL NAMES CAN SUPPORT DIFFERENT<\/text> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"21\" font-weight=\"bold\" x=\"30\" y=\"76\">ASSESSMENTS<\/text> <text fill=\"#455B70\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"14\" font-weight=\"normal\" x=\"30\" y=\"110\">Illustrative examples only \u2014 attributes and source reliability both matter<\/text> <rect fill=\"#F8FAFD\" height=\"142\" rx=\"15\" stroke=\"#C9D5E1\" stroke-width=\"2\" width=\"560\" x=\"30\" y=\"165\"><\/rect> <g fill=\"none\" stroke=\"#0B1F3A\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2.9\"> <circle cx=\"69\" cy=\"204\" r=\"12\"><\/circle> <line x1=\"78\" x2=\"89\" y1=\"213\" y2=\"225\"><\/line> <\/g> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"22\" font-weight=\"bold\" x=\"111\" y=\"213\">CASE A<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"normal\" x=\"57\" y=\"257\">Same name<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"normal\" x=\"57\" y=\"285\">DOB and other attributes conflict<\/text> <line marker-end=\"url(#ns_two_cases_mob_arrow)\" stroke=\"#A1B0C3\" stroke-width=\"3.6\" x1=\"310.0\" x2=\"310.0\" y1=\"314\" y2=\"328\"><\/line> <rect fill=\"#EAF8F7\" height=\"160\" rx=\"15\" stroke=\"#46C1BE\" stroke-width=\"2\" width=\"560\" x=\"30\" y=\"340\"><\/rect> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"19\" font-weight=\"bold\" x=\"54\" y=\"385\">WEAKER EVIDENCE OF A MATCH<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"16\" font-weight=\"normal\" x=\"54\" y=\"422\">Conflicts require source verification.<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"16\" font-weight=\"normal\" x=\"54\" y=\"459\">Do not treat as an automatic clearance.<\/text> <rect fill=\"#F8FAFD\" height=\"142\" rx=\"15\" stroke=\"#C9D5E1\" stroke-width=\"2\" width=\"560\" x=\"30\" y=\"571\"><\/rect> <g fill=\"none\" stroke=\"#0B1F3A\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2.9\"> <circle cx=\"69\" cy=\"610\" r=\"12\"><\/circle> <line x1=\"78\" x2=\"89\" y1=\"619\" y2=\"631\"><\/line> <\/g> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"22\" font-weight=\"bold\" x=\"111\" y=\"619\">CASE B<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"normal\" x=\"57\" y=\"663\">Same name<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"20\" font-weight=\"normal\" x=\"57\" y=\"691\">DOB and aliases corroborate<\/text> <line marker-end=\"url(#ns_two_cases_mob_arrow)\" stroke=\"#A1B0C3\" stroke-width=\"3.6\" x1=\"310.0\" x2=\"310.0\" y1=\"720\" y2=\"734\"><\/line> <rect fill=\"#EAF8F7\" height=\"160\" rx=\"15\" stroke=\"#46C1BE\" stroke-width=\"2\" width=\"560\" x=\"30\" y=\"746\"><\/rect> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"19\" font-weight=\"bold\" x=\"54\" y=\"791\">STRONGER EVIDENCE OF A MATCH<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"16\" font-weight=\"normal\" x=\"54\" y=\"828\">Prioritise verification against source records.<\/text> <text fill=\"#1E2E40\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"16\" font-weight=\"normal\" x=\"54\" y=\"865\">Do not treat as an automatic finding.<\/text> <text fill=\"#0B1F3A\" font-family=\"Arial, Helvetica, sans-serif\" font-size=\"17\" font-weight=\"bold\" x=\"30\" y=\"943\">Neither case is a final compliance determination.<\/text> <\/svg><\/div><figcaption>Contradictory or corroborating identity evidence changes review priority but cannot prove a match or non-match by itself.<em>Figure 2. A simplified teaching example. Categories and thresholds are illustrative, not actual NameScan scoring logic.<\/em><\/figcaption><\/figure>  <h2 id=\"what-would-better-decisions-mean-for-screening-teams\">What would \u201cbetter decisions\u201d mean for screening teams?<\/h2> <p><strong>Better decisions<\/strong> means more relevant match assessments, with the evidence and uncertainty visible to the reviewer. That is the first of four potential benefits for embedded Decision AI.<\/p> <div class=\"ns-grid ns-g3\"><div class=\"ns-item\"><h4>Controlled decisions<\/h4><p>The organisation defines the permitted match categories, routing rules and conditions for manual review. A model output should be treated as evidence for a workflow decision, not a new source of sanctions authority.<\/p><\/div><div class=\"ns-item\"><h4>Faster decisions<\/h4><p>A well-designed workflow may reduce time spent comparing obviously unrelated records. This requires measurement of time to disposition, missed true matches and review quality before claiming an improvement.<\/p><\/div><div class=\"ns-item\"><h4>Decisions at scale<\/h4><p>Structured match assessment could be applied consistently across larger screening volumes, but different names, languages and populations demand careful testing for performance disparities.<\/p><\/div><\/div>   <p>A screening provider should evaluate false positives <em>and<\/em> false negatives. Removing noise is not a success if relevant records are being missed or the system is overconfident about incomplete evidence.<\/p> <h2 id=\"where-ai-must-remain-accountable-to-source-data\">Where AI must remain accountable to source data<\/h2> <p>Screening involves distinct facts and judgements. An official sanctions authority publishes designations; the platform retrieves records; a comparison process assesses whether the search subject corresponds to the record; the business then determines its obligations and actions under relevant law and policy.<\/p> <p>It is risky to compress these into a single statement such as \u201cAI cleared this customer\u201d. An auditable workflow should retain the original search terms, data source, timestamp, compared attributes, match recommendation, decision confidence where used, reviewer notes and final disposition.<\/p> <p>Privacy matters too. Screening records may contain sensitive personal information. Any external decision model would require review of processing location, retention, access control, contractual arrangements and whether only the necessary fields are transmitted.<\/p> <h2 id=\"how-namescan-fits-into-this-approach\">How NameScan fits into this approach<\/h2> <p>NameScan\u2019s core proposition remains straightforward: accessible screening for PEP, sanctions and adverse-media risks without requiring an enterprise software contract. That is the present-day screening service. The future Decision AI opportunity is more targeted: <strong>helping the screening workflow distinguish possible matches from meaningful identity evidence in a controlled way<\/strong>.<\/p> <p>This is why the right question is not \u201cCan AI screen someone?\u201d but rather <strong>\u201cCan an AI-assisted workflow help us assess a potential match more carefully?\u201d<\/strong> The distinction protects decision quality and gives users a more useful understanding of what their screening result means.<\/p> <h2 id=\"frequently-asked-questions\">Frequently asked questions<\/h2><div class=\"ns-faq\"><details><summary><h3 id=\"does-a-pep-or-sanctions-screening-match-mean-my-customer-is-listed\">Does a PEP or sanctions screening match mean my customer is listed?<\/h3><\/summary><div class=\"ns-ans\"><p>Not necessarily. Screening returns candidate records. You must establish whether the customer is the same person or organisation and assess what the relevant source and law require.<\/p><\/div><\/details><details><summary><h3 id=\"what-is-the-difference-between-fuzzy-matching-and-decision-ai\">What is the difference between fuzzy matching and Decision AI?<\/h3><\/summary><div class=\"ns-ans\"><p>Fuzzy matching measures or retrieves textual similarity. Decision AI could assess a bounded match judgement using additional evidence such as date of birth, aliases, geography and source quality. Both may be useful within the same workflow.<\/p><\/div><\/details><details><summary><h3 id=\"can-a-confidence-score-automatically-clear-a-screening-hit\">Can a confidence score automatically clear a screening hit?<\/h3><\/summary><div class=\"ns-ans\"><p>Only where a validated system and organisational policy permit an automated disposition. Uncertain, incomplete or legally consequential cases may need human review. Confidence alone is not proof of identity.<\/p><\/div><\/details><details><summary><h3 id=\"can-ai-determine-whether-someone-is-legally-sanctioned\">Can AI determine whether someone is legally sanctioned?<\/h3><\/summary><div class=\"ns-ans\"><p>AI is not the authoritative source of legal designation. Official sanctions sources, applicable laws and appropriate compliance procedures establish the relevant obligations.<\/p><\/div><\/details><\/div>            <div class=\"ns-cta\"><h2 id=\"screen-with-context-not-just-a-name\">Screen with context, not just a name<\/h2><p>A useful compliance check begins with comprehensive screening data and ends with a documented, proportionate assessment. NameScan helps businesses access PEP, sanctions and adverse-media screening through a pay-as-you-go service. As contextual decision technology develops, the opportunity is to make match evaluation clearer and more relevant, without confusing a possible name match with a final risk decision.<\/p><p><a class=\"ns-btn\" href=\"https:\/\/namescan.io\/pricing\">View NameScan screening options<\/a><\/p><\/div>  \r\n<\/div><\/div>\r\n","protected":false},"excerpt":{"rendered":"<p>Thought leadership&nbsp;\u00b7&nbsp;Decision AI&nbsp;\u00b7&nbsp;PEP &amp; sanctions screening Learn why PEP and sanctions screening requires more than matching names, and how contextual Decision AI could support more confident review decisions. The screening distinction Potential name match \u2260 Confirmed identity match Name similarity is a lead. Identity assessment requires corroborating evidence and review. A sanctions or PEP name [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":14470,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"image","meta":{"_yoast_wpseo_focuskw":"Sanctions screening","_yoast_wpseo_title":"Sanctions & PEP Screening: Where AI Fits | NameScan","_yoast_wpseo_metadesc":"Explore how contextual Decision AI could improve sanctions and PEP screening, assess potential name matches and support confidence-aware reviews.","footnotes":""},"categories":[85],"tags":[100,87,256],"class_list":["post-14467","post","type-post","status-publish","format-image","has-post-thumbnail","hentry","category-blog-post","tag-ai","tag-aml","tag-decision-ai","post_format-post-format-image"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Sanctions &amp; PEP Screening: Where AI Fits | NameScan<\/title>\n<meta name=\"description\" content=\"Explore how contextual 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