[{"data":1,"prerenderedAt":631},["ShallowReactive",2],{"uc-patient-previsit-education-avatar":3,"uc-regulations":408},{"useCase":4,"evidence":189,"blitsAiDeployments":283,"benchmarks":284,"indicative":293,"related":296,"indexability":406,"includeUnpublished":195},{"title":5,"shortTitle":6,"seoTitle":5,"metaDescription":7,"status":8,"definition":9,"aliases":10,"industries":15,"functions":17,"patterns":20,"channels":25,"audience":27,"autonomy":28,"adoptionStage":29,"problem":30,"problemStats":31,"howItWorks":32,"valueDrivers":33,"kpis":37,"indicativeValue":42,"macroEstimates":78,"feasibility":79,"implementation":94,"risk":137,"blitsAi":165,"faq":167,"related":180,"datePublished":184,"dateModified":184,"lastVerified":184,"changelog":185,"slug":188},"AI avatar for pre visit patient education","Pre visit patient avatar","An AI avatar prepares patients before a visit by explaining their condition and options. ChristianaCare reports less stress and better understanding.","published","A pre visit patient education avatar is an AI character that explains a condition and treatment options to patients before their appointment. It is often a digital version of the treating clinician, speaks from content the care team approved, and leaves diagnosis and decisions to the clinician.",[11,12,13,14],"AI physician avatar","pre consultation AI avatar","pre admission digital teammate","AI patient preparation avatar",[16],"healthcare",[18,19],"customer-service","knowledge-management",[21,22,23,24],"digital-human","content-generation","conversational-agent","rag-knowledge-assistant",[21,26],"web-chat","customer-facing","assist","emerging","A first consultation for a serious condition carries more information than a patient can take in\nduring the visit. ChristianaCare describes cancer patients arriving anxious and emotionally\ndrained, facing complex information in a single conversation, which makes it harder to ask\nquestions and understand treatment. At The Ottawa Hospital, patients scheduled for surgery had one\nPre-Admission Unit appointment two to six weeks beforehand, which Deloitte calls an unrealized\nopportunity to give patients continuous access to information.\n\nClinicians feel the same gap from the other side. The urologic oncologist who built the Vanderbilt pilot describes\ngiving \"the same spiel over and over\" about common conditions in visits limited to a few minutes\nby volume. An avatar that explains the basics at home, in the patient's own time, and answers\nfollow up questions moves that repetition out of the visit and leaves the appointment for the\npatient's goals and preferences.",[],"1. **The care team chooses the content.** A department picks the condition or procedure and writes\n   or approves the material: scripted education, or a curated question and answer document. At\n   Vanderbilt the avatar was trained only on a document chosen by the clinicians.\n2. **An avatar represents the clinician, or a neutral guide.** ChristianaCare built an avatar for\n   each radiation oncology physician with a cloned voice, so patients met a face and voice they\n   would see in the clinic. The Ottawa Hospital used a lifelike avatar named Digital Teammate.\n3. **The patient receives it before the visit.** The patient opens a link at home on a phone,\n   tablet or computer, and can use it at any hour.\n4. **The avatar teaches or answers.** In ChristianaCare's design it delivers personalized\n   educational videos and then runs teach back quizzes. In the Vanderbilt and Ottawa pilots it holds\n   a conversation and answers from approved content; the Vanderbilt avatar was told to refuse\n   prescribing.\n5. **The clinician takes over.** The patient arrives better prepared, and the visit covers\n   decisions and values. Teams in these pilots plan to extend the avatar to history taking and to\n   questions after the visit.",[34,35,36],"customer-experience","employee-productivity","inclusion-and-access",[38,39,40,41],"users-served","customer-satisfaction","time-saved-per-task","accuracy",{"referenceOrg":43,"inputs":44,"formula":73,"currency":74,"period":75,"resultLabel":76,"caveat":77},"A cancer center with 3,000 new patient consultations a year",[45,52,59,66],{"key":46,"label":47,"low":48,"high":49,"unit":50,"note":51},"newPatients","New patient consultations per year",2000,4000,"consultations","Reference size for a mid sized cancer center. Replace with your own volume.",{"key":53,"label":54,"low":55,"high":56,"unit":57,"note":58},"useShare","Share of new patients who complete the avatar education before the visit",0.4,0.7,"fraction of patients","Editorial assumption. ChristianaCare's study had 958 patients view the avatar videos but does not publish a completion rate for the invited patients (HospiMedica quotes the chair saying all the patients completed the quiz, but not how many were invited).",{"key":60,"label":61,"low":62,"high":63,"unit":64,"note":65},"minutesSaved","Clinician minutes saved per patient who completes it",5,10,"minutes","Editorial assumption. ChristianaCare plans to evaluate consultation efficiency and has not published a result, so measure this in your own pilot.",{"key":67,"label":68,"low":69,"high":70,"unit":71,"note":72},"clinicianCost","Fully loaded cost of one clinician hour",150,250,"USD per hour","Editorial assumption, replace with your own payroll data.","newPatients * useShare * minutesSaved \u002F 60 * clinicianCost","USD","per year","Annual clinician time released in consultations","Counts only clinician minutes released in the visit. It leaves out production and review time for the content, the cost of the platform, any effect on no shows, anxiety, understanding or outcomes, and the accessibility gain for patients who need another language or a slower pace. Most evidence so far concerns understanding and stress, not time, so the saving is an assumption to test.",[],{"complexity":80,"complexityNote":81,"dataPrerequisites":82,"integrations":88},"medium","The build is mostly clinical content and consent. Each condition needs approved scripts or a question and answer document with a named clinical owner and review date, voice and likeness consent from every physician who is cloned, and a secure way to reach the patient before the visit. Linking the avatar to the electronic record for personalization adds identity checks and privacy review.",[83,84,85,86,87],"Approved patient education content per condition or procedure, with a clinical owner and review date","Written consent for voice and likeness from every clinician who is represented","Practical local information such as location, parking, what to bring and how to reach the clinic","A list of questions the avatar must refuse, such as prescribing, diagnosis and dosing","Languages and reading levels the patient population needs",[89,90,91,92,93],"Appointment scheduling, to send the link and know the visit date","Patient portal or secure messaging for delivery and follow up","Electronic health record, only if personalization or history taking is added","Quiz and analytics store for teach back results and usage","Clinic phone or secure message queue for handover",{"steps":95,"guardrails":111,"humanInTheLoop":117,"kpisToInstrument":118,"failureModes":124},[96,99,102,105,108],{"title":97,"detail":98},"Start with one condition and one clinic","Choose a visit where the same explanation is repeated every day, such as first radiation oncology consultations or a pre admission appointment. A narrow scope makes the content reviewable and gives a clean comparison group.",{"title":100,"detail":101},"Get the content and consent signed off first","Clinical leads approve every script or question and answer document, and every represented clinician signs a consent for voice and likeness. Write down what the avatar must refuse, and put the refusals in the test set.",{"title":103,"detail":104},"Compare against the current material","ChristianaCare compared avatar videos with a standard educational video and measured understanding with a quiz, engagement in decisions, stress and satisfaction. Use the same design so the avatar has to beat what you send today.",{"title":106,"detail":107},"Test the conversation with patients, not staff","Run a small pilot, as Vanderbilt did with ten patients, and ask about format, tone and gaps. Patients there liked video, which argues for an avatar over text.",{"title":109,"detail":110},"Add the follow up questions and history taking last","Questions after the visit and structured history are the next steps teams name. Add them once the pre visit use has a measured effect and a clinician owns the review of what the avatar collects.",[112,113,114,115,116],"Answers only from clinically approved content, with a plain statement when the content is silent","The avatar does not diagnose, prescribe, change doses or triage symptoms, and refers urgent symptoms to the clinic or emergency services","Disclosure that the avatar is AI generated, including when it copies a real clinician's face and voice","Consent and a stop rule for every cloned voice or likeness, including what happens when the clinician leaves","Minimal personal data in the conversation, masked in logs, with retention limits","Clinical leads own the content and review a sample of conversations and quiz results every month. Anything the patient says that suggests a symptom, a safety concern or distress goes to a nurse or the clinic line, and the clinician sees what the patient learned before the visit starts.",[119,120,121,122,123],"Share of invited patients who complete the education before the visit","Teach back quiz scores against the standard material","Stress and confidence scores before the visit, using the same survey as the comparison group","Clinician time per new consultation and number of repeat questions asked in the visit","Questions the avatar declined or could not answer, grouped by topic",[125,128,131,134],{"title":126,"detail":127},"A confident wrong answer about treatment","The avatar states a risk or option that the clinician would not. Restrict it to approved text, test refusals, and have clinical leads read samples every month.",{"title":129,"detail":130},"Patients assume the avatar knows their case","A patient may expect an avatar that looks like their clinician to know their chart. Say plainly that it teaches general content and does not know the patient's case, unless it is linked to the record.",{"title":132,"detail":133},"A clinician's likeness is used beyond what was agreed","Voice and image clones outlive a job or a project. Record scope and end date in the consent, and delete the model when it ends.",{"title":135,"detail":136},"Education replaces the conversation","Patients arrive informed but the visit still runs short. Track whether visits spend more time on values and decisions, and cut repeated explanation from the visit script.",{"euAiAct":138,"regulations":141,"guidance":145,"controls":158,"incidents":164},{"tier":139,"basis":140},"context-dependent","Education from approved content is a limited risk system with transparency duties (Article 50), and an avatar that copies a real clinician's face and voice is synthetic content that must be disclosed as artificially generated. If the avatar assessed symptoms, triaged patients or advised on treatment it could be medical device software under the Medical Device Regulation. That makes it high risk under Article 6(1) and Annex I of the AI Act when the device needs a third party conformity assessment, and brings medical device conformity rules.",[142,143,144],"eu-ai-act","gdpr","hipaa",[146,152],{"title":147,"issuer":148,"region":149,"url":150,"note":151},"Article 50, transparency obligations for providers and deployers of certain AI systems","European Union","europe","https:\u002F\u002Fartificialintelligenceact.eu\u002Farticle\u002F50\u002F","People must be told when they interact with an AI system, and deployers must disclose AI generated image or audio that resembles real people.",{"title":153,"issuer":154,"region":155,"url":156,"note":157},"HIPAA Privacy Rule","US Department of Health and Human Services","north-america","https:\u002F\u002Fwww.hhs.gov\u002Fhipaa\u002Ffor-professionals\u002Fprivacy\u002Findex.html","Sets the rules for protected health information that an avatar may collect or show, including minimum necessary use and patient access.",[159,160,161,162,163],"AI disclosure at the start of every session and on every video","Clinical owner and review date for every script or question and answer document","Written voice and likeness consent per clinician, with scope and end date","Refusal tests for prescribing, diagnosis and urgent symptoms, rerun on every content or model change","Privacy impact assessment and masked, time limited logs",[],{"howToBuild":166},"On Blits.ai the patient guide is an **AI agent** with a **knowledge base** built from the care\nteam's approved patient education documents, retrieved with **hybrid search**, plus **custom\nfunctions** that call the scheduling system for the visit date and clinic details. The agent\nruns as a photorealistic **digital human** with lip synced speech, and the same agent is\navailable in **web chat** so a patient can use whichever format they prefer.\n\n**Guardrails** keep answers inside the approved content and block advice on diagnosis, dosing or\nprescribing, **PII masking** removes personal details from logs, and **human handover** passes\na patient with a concern to the clinic with the transcript. **Multi language** support lets one\nagent teach in several languages, **test suites** replay the refusal and accuracy questions\nbefore each change, **analytics** show usage and unanswered questions, and the platform is\n**model agnostic** with EU or UAE data residency.",[168,171,174,177],{"question":169,"answer":170},"Does a clinician's AI avatar replace the consultation?","No. ChristianaCare's radiation oncology chair says of the avatar, \"This is not about replacing the physician in any way.\" The avatar prepares patients so they arrive calmer and better informed, and the visit still holds the conversation about the patient's own case and decisions.",{"question":172,"answer":173},"What results have hospitals reported?","ChristianaCare compared avatar videos with a standard video in a study of 1,464 patients and reports better understanding, more engagement in care decisions, lower stress and higher satisfaction, without publishing effect sizes. Vanderbilt ran a pilot with 10 patients, who liked the video format, according to a clinician who built it. For The Ottawa Hospital, NVIDIA reports that a majority of user acceptance testers found the answers clear and relevant, with no percentage given. That is a vendor claim.",{"question":175,"answer":176},"Can the avatar answer open questions or only play scripted videos?","Both designs exist. ChristianaCare's avatars deliver personalized scripted videos followed by teach back quizzes. Vanderbilt and The Ottawa Hospital use a conversational avatar that answers from approved content. The Vanderbilt avatar was told to refuse prescribing, and the Ottawa sources do not describe what it declines.",{"question":178,"answer":179},"Is a patient education avatar high risk under the EU AI Act?","Not when it only explains approved content: it carries transparency duties, including disclosure of the synthetic clinician. It can become high risk if it triages symptoms or advises on treatment, because it may then count as a medical device.",[181,182,183],"patient-appointment-scheduling-and-reminders-agent","patient-portal-message-reply-drafting","ai-visitor-and-tour-guide","2026-10-14",[186],{"date":184,"note":187},"First published","patient-previsit-education-avatar",[190,228,251],{"title":191,"useCases":192,"organization":193,"vendors":197,"summary":198,"stage":199,"year":200,"channels":201,"languages":202,"metrics":204,"outcomeDisclosed":212,"sources":213,"verification":223,"grade":225,"id":226,"organizationSlug":227},"ChristianaCare: AI physician avatars before radiation oncology visits",[188],{"name":194,"anonymized":195,"country":196,"region":155,"industry":16},"ChristianaCare",false,"US",[],"ChristianaCare, working with an unnamed digital technology company, created an AI avatar for each physician in its radiation oncology department. Using cloned voices, the avatars delivered personalized educational videos to patients at home before the first in person consultation, followed by teach back quizzes. In a study of 1,464 patients, one group watched a standard educational video and another watched the avatar videos with personalized scripts and illustrations. The health system reports better understanding, greater engagement in care decisions, lower stress and higher satisfaction for the avatar group, and plans to extend the model to surgical oncology.","pilot",2026,[21],[203],"en",[205],{"kpi":38,"value":206,"unit":207,"qualifier":208,"claimant":209,"quote":210,"sourceUrl":211},958,"count","exact","organization","The other 958 patients (65.4%) viewed an avatar-based video tailored with personalized scripts and explanatory illustrations.","https:\u002F\u002Fwww.hospimedica.com\u002Fpatient-care\u002Farticles\u002F294810646\u002Fai-avatar-doctor-improves-patient-understanding-before-radiotherapy.html",true,[214,219],{"url":215,"title":216,"publisher":217,"date":218},"https:\u002F\u002Fnews.christianacare.org\u002F2026\u002F06\u002Fchristianacare-study-first-to-show-ai-avatar-can-help-cancer-patients-feel-less-anxious-before-radiation-visits\u002F","ChristianaCare Study First to Show AI Avatar Can Help Cancer Patients Feel Less Anxious Before Radiation Visits","ChristianaCare News","2026-06-24",{"url":211,"title":220,"publisher":221,"date":222},"AI Avatar Doctor Improves Patient Understanding Before Radiotherapy","HospiMedica","2026-05-20",{"level":224,"checkedAt":184},"source-verified","B","christianacare-radiation-oncology-ai-physician-avatars",null,{"title":229,"useCases":230,"organization":231,"vendors":234,"summary":235,"stage":199,"year":236,"channels":237,"languages":238,"metrics":239,"outcomeDisclosed":212,"sources":243,"verification":248,"grade":249,"id":250,"organizationSlug":227},"Vanderbilt University Medical Center: AI avatar for pre visit counseling in urology",[188],{"name":232,"anonymized":195,"country":196,"region":155,"industry":16,"wikidata":233},"Vanderbilt University Medical Center","Q7914455",[],"Urologic oncologists at Vanderbilt ran a pilot in which patients talked with an AI avatar of their clinician before a clinic visit. The avatar looks and sounds like the physician and answers questions about prostate cancer and its treatment options from a curated question and answer document chosen by the clinicians. It declines to prescribe, and it also answers local questions such as where to park. Ten patients took part, liked the video format and gave feedback on improvements. The team plans to add medical history taking and post visit questions.",2025,[21],[203],[240],{"kpi":38,"value":63,"unit":207,"qualifier":208,"claimant":209,"quote":241,"sourceUrl":242},"We ran a pilot study with 10 patients to test out this technology.","https:\u002F\u002Fwww.urotoday.com\u002Fvideo-lectures\u002Fprostate-cancer\u002Fvideo\u002F5164-using-an-ai-generated-avatar-to-deliver-pre-visit-patient-counseling-avi-baskin.html",[244],{"url":242,"title":245,"publisher":246,"date":247},"Using an AI-Generated Avatar to Deliver Pre-Visit Patient Counseling","UroToday","2025-11-07",{"level":224,"checkedAt":184},"C","vanderbilt-university-medical-center-ai-avatar-previsit-counseling",{"title":252,"useCases":253,"organization":254,"vendors":258,"summary":265,"stage":199,"year":266,"channels":267,"languages":268,"metrics":270,"outcomeDisclosed":195,"sources":271,"verification":281,"grade":249,"id":282,"organizationSlug":227},"The Ottawa Hospital: Digital Teammate avatar for surgical pre admission patients",[188],{"name":255,"anonymized":195,"country":256,"region":155,"industry":16,"wikidata":257},"The Ottawa Hospital","CA","Q3145270",[259,262],{"name":260,"role":261},"Deloitte","integrator",{"name":263,"role":264},"NVIDIA","platform","The Ottawa Hospital piloted a lifelike AI avatar called Digital Teammate, built with Deloitte Canada on its CortexAI platform and NVIDIA technology. Patients scheduled for surgery usually have a single Pre-Admission Unit appointment two to six weeks beforehand, so the avatar gives them a 24 hour source of approved answers in English and French, including questions about anesthesia and the procedure. A first test phase also placed it at hospital campuses to answer questions about the new campus. NVIDIA describes patient access by smartphone, tablet or home computer. The vendor reports no measured outcomes.",2024,[21],[203,269],"fr",[],[272,276],{"url":273,"title":274,"publisher":275},"https:\u002F\u002Fwww.deloitte.com\u002Fca\u002Fen\u002Fwhat-we-do\u002Fcase-studies-collection\u002Fredefining-patient-experience-ottawa-hospital","AI at the heart of healing: Redefining the patient experience, The Ottawa Hospital","Deloitte Canada",{"url":277,"title":278,"publisher":279,"date":280},"https:\u002F\u002Fblogs.nvidia.com\u002Fblog\u002Fdeloitte-ai-agents-healthcare\u002F","NVIDIA Works With Deloitte to Deploy Digital AI Agents for Healthcare","NVIDIA Blog","2024-10-21",{"level":224,"checkedAt":184},"ottawa-hospital-deloitte-digital-teammate",0,[285],{"kpi":38,"label":286,"unit":207,"aggregate":195,"higherIsBetter":212,"n":287,"nUpTo":283,"median":288,"min":63,"max":206,"byClaimant":289,"vendorOnly":195,"points":290},"Users served",2,484,{"organization":287,"vendor":283,"regulator":283,"independent":283},[291,292],{"evidenceId":226,"organization":194,"value":206,"qualifier":208,"claimant":209,"grade":225,"pooled":212},{"evidenceId":250,"organization":232,"value":63,"qualifier":208,"claimant":209,"grade":249,"pooled":212},{"low":294,"high":295},10000,116666.66666666667,[297,331,352,383],{"slug":181,"title":298,"shortTitle":299,"definition":300,"status":8,"industries":301,"functions":302,"patterns":304,"audience":27,"autonomy":308,"adoptionStage":309,"evidenceCount":310,"publicEvidenceCount":311,"organizations":312,"bestGrade":225,"headline":322,"lastVerified":330,"indexable":212},"AI agent for patient appointment scheduling, reminders and no show reduction","Patient scheduling and reminders","An AI agent for patient scheduling and reminders books, moves and cancels patient appointments by phone and messaging, and reminds and confirms patients. It follows the provider's scheduling rules (referral, triage level, clinician and visit type, preparation), confirms and reminds patients in two way conversations, predicts who is likely to miss an appointment, and offers freed slots to patients on the waiting list. Unlike a general branch and appointment booking agent, it writes into the electronic health record and must respect clinical constraints, so anything clinical goes to staff.",[16],[18,303],"operations",[305,23,306,307],"voice-agent","prediction-and-scoring","agentic-workflow","supervised-agent","early-adopters",12,9,[313,314,315,316,317,318,319,320,321],"Audibel","Good Shepherd Rehabilitation Network","Howard Brown Health","Mid and South Essex NHS Foundation Trust","North Kansas City Hospital","Reid Health","Sheffield Children's NHS Foundation Trust","University Hospitals Coventry and Warwickshire NHS Trust","WellSpan Health",{"kpi":323,"label":324,"unit":325,"n":326,"nUpTo":283,"kind":327,"value":328,"qualifier":208,"claimant":329,"organization":315,"vendorReported":212},"containment-rate","Containment rate","percent",1,"reported",30,"vendor","2026-09-27",{"slug":182,"title":332,"shortTitle":333,"definition":334,"status":8,"industries":335,"functions":336,"patterns":337,"audience":338,"autonomy":339,"adoptionStage":309,"evidenceCount":340,"publicEvidenceCount":340,"organizations":341,"bestGrade":225,"headline":346,"lastVerified":351,"indexable":212},"AI drafting of clinician replies to patient portal messages","Patient portal message reply drafting","Generative AI for patient portal message reply drafting reads an incoming patient portal message together with the patient's own chart and drafts a reply for the care team. A clinician, nurse, advanced practice clinician or pharmacist reviews, edits and sends it, so the care team starts from a draft instead of a blank reply box on every message.",[16],[18,303],[22,24],"employee-facing","copilot",4,[342,343,344,345],"NYU Langone Health","Stanford Health Care","UC San Diego Health","UW Health",{"kpi":347,"label":348,"unit":325,"n":326,"nUpTo":283,"kind":327,"value":349,"qualifier":350,"claimant":209,"organization":342,"vendorReported":195},"response-time-reduction","Response time reduction",7,"approximately","2026-09-29",{"slug":183,"title":353,"shortTitle":354,"definition":355,"status":8,"industries":356,"functions":360,"patterns":362,"audience":27,"autonomy":365,"adoptionStage":309,"evidenceCount":366,"publicEvidenceCount":367,"organizations":368,"bestGrade":225,"headline":227,"lastVerified":382,"indexable":212},"AI visitor and tour guide for cities, museums and events","Visitor and tour guide","An AI visitor and tour guide tells visitors of cities, museums, heritage sites and events the stories behind what is around them, and answers their questions in their own language. It is often spoken, location and context aware, grounded in the organization's curated content and in the visitor's position or the object they scan.",[357,358,359],"travel-and-hospitality","media-and-entertainment","government",[18,361,19],"marketing",[24,23,305,21,363,364],"computer-vision","translation","autonomous",14,13,[369,370,371,372,373,374,375,376,377,378,379,380,381],"Art Basel","Bloomberg Connects","Centre Pompidou","Elliott Museum","Leeds Castle","Liverpool City Region Destination Partnership","Madrid Destino","Museo Miraflores","National Gallery Singapore","Presidency of Religious Affairs at the Grand Mosque and the Prophet's Mosque","Saudi Tourism Authority","Schladming-Dachstein Tourist Board","Visit Qatar","2026-09-26",{"slug":384,"title":385,"shortTitle":386,"definition":387,"status":8,"industries":388,"functions":390,"patterns":392,"audience":338,"autonomy":28,"adoptionStage":309,"segment":394,"evidenceCount":395,"publicEvidenceCount":395,"organizations":396,"bestGrade":225,"headline":403,"lastVerified":330,"indexable":212},"retail-store-and-kiosk-assistant","AI assistant for telecom retail stores, from associate copilot to digital human kiosk","Retail store and kiosk assistant","A retail store and kiosk assistant is AI for telecom shops that gives store associates quick, sourced answers on plans, promotions, devices and the customer's account during the conversation. It can also greet and serve customers directly on an in store screen or kiosk, sometimes as a digital human, handing them to an associate when they are ready to buy or need help.",[389],"telecommunications",[391,18,19],"sales",[24,21,23,393],"recommendation-and-personalization","front-office",6,[397,398,399,400,401,402],"Bouygues Telecom","Deutsche Telekom","Orange Slovakia","Singtel","T-Mobile","Vodafone New Zealand",{"kpi":41,"label":404,"unit":325,"n":326,"nUpTo":283,"kind":327,"value":405,"qualifier":208,"claimant":329,"organization":397,"vendorReported":212},"Accuracy",95,{"indexable":212,"reasons":407},[],[409,414,419,427,434,441,447,454,462,469,475,481,487,492,499,505,511,517,522,528,533,538,544,550,557,562,567,572,579,584,591,597,602,608,615,620,625],{"id":142,"label":410,"issuer":148,"region":149,"url":411,"description":412,"useCases":413,"indexable":212},"EU AI Act","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2024\u002F1689\u002Foj","Regulation (EU) 2024\u002F1689: risk based rules for AI systems, with obligations for high risk systems listed in Annex III and transparency duties under Article 50.",295,{"id":143,"label":415,"issuer":148,"region":149,"url":416,"description":417,"useCases":418,"indexable":212},"GDPR","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2016\u002F679\u002Foj","General Data Protection Regulation, including Article 22 on decisions based solely on automated processing.",265,{"id":420,"label":421,"issuer":422,"region":423,"url":424,"description":425,"useCases":426,"indexable":212},"iso-42001","ISO\u002FIEC 42001","ISO and IEC","global","https:\u002F\u002Fwww.iso.org\u002Fstandard\u002F81230.html","The international management system standard for AI.",148,{"id":428,"label":429,"issuer":430,"region":155,"url":431,"description":432,"useCases":433,"indexable":212},"nist-ai-rmf","NIST AI Risk Management Framework","NIST","https:\u002F\u002Fwww.nist.gov\u002Fitl\u002Fai-risk-management-framework","Voluntary US framework to map, measure, manage and govern AI risk, with a generative AI profile.",115,{"id":435,"label":436,"issuer":437,"region":149,"url":438,"description":439,"useCases":440,"indexable":212},"uk-gdpr","UK GDPR","Information Commissioner's Office","https:\u002F\u002Fico.org.uk\u002Ffor-organisations\u002Fuk-gdpr-guidance-and-resources\u002F","The UK's version of the GDPR, including rules on solely automated decisions.",84,{"id":442,"label":443,"issuer":148,"region":149,"url":444,"description":445,"useCases":446,"indexable":212},"dora","DORA","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2022\u002F2554\u002Foj","Digital Operational Resilience Act for financial entities: ICT risk, incident reporting and third party risk, including AI providers.",73,{"id":448,"label":449,"issuer":450,"region":149,"url":451,"description":452,"useCases":453,"indexable":212},"uk-consumer-duty","FCA Consumer Duty","Financial Conduct Authority","https:\u002F\u002Fwww.fca.org.uk\u002Ffirms\u002Fconsumer-duty","UK rules that require firms to deliver good outcomes for retail customers, including through automated channels.",53,{"id":455,"label":456,"issuer":457,"region":458,"url":459,"description":460,"useCases":461,"indexable":212},"mas-ai-risk-management","MAS AI risk management guidelines","Monetary Authority of Singapore","asia-pacific","https:\u002F\u002Fwww.mas.gov.sg\u002Fnews\u002Fmedia-releases\u002F2025\u002Fmas-guidelines-for-artificial-intelligence-risk-management","Singapore's supervisory expectations for AI risk management at financial institutions, building on the FEAT principles.",37,{"id":463,"label":464,"issuer":465,"region":458,"url":466,"description":467,"useCases":468,"indexable":212},"apra-cps-230","APRA CPS 230","Australian Prudential Regulation Authority","https:\u002F\u002Fwww.apra.gov.au\u002Foperational-risk-management","Australian operational risk standard covering critical operations and material service providers.",26,{"id":470,"label":471,"issuer":148,"region":149,"url":472,"description":473,"useCases":474,"indexable":212},"nis2","NIS2 Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2022\u002F2555\u002Foj","Directive (EU) 2022\u002F2555 on cybersecurity for essential and important entities, including telecom networks, energy and public administration.",23,{"id":476,"label":477,"issuer":478,"region":423,"url":479,"description":480,"useCases":474,"indexable":212},"pci-dss","PCI DSS","PCI Security Standards Council","https:\u002F\u002Fwww.pcisecuritystandards.org\u002F","Security standard for any system that stores, processes or transmits cardholder data.",{"id":482,"label":483,"issuer":484,"region":155,"url":485,"description":486,"useCases":474,"indexable":212},"us-sr-11-7","SR 11-7 model risk management","Federal Reserve and OCC","https:\u002F\u002Fwww.federalreserve.gov\u002Fboarddocs\u002Fsrletters\u002F2011\u002Fsr1107.htm","US supervisory guidance on model risk management, applied by banks to AI and machine learning models.",{"id":144,"label":488,"issuer":154,"region":155,"url":489,"description":490,"useCases":491,"indexable":212},"HIPAA","https:\u002F\u002Fwww.hhs.gov\u002Fhipaa\u002Findex.html","US rules for the privacy and security of protected health information.",20,{"id":493,"label":494,"issuer":495,"region":149,"url":496,"description":497,"useCases":498,"indexable":212},"uk-atrs","UK Algorithmic Transparency Recording Standard","UK Government","https:\u002F\u002Fwww.gov.uk\u002Fgovernment\u002Fcollections\u002Falgorithmic-transparency-recording-standard-hub","Mandatory transparency records for algorithmic tools used by UK central government.",18,{"id":500,"label":501,"issuer":148,"region":149,"url":502,"description":503,"useCases":504,"indexable":212},"eu-accessibility-act","European Accessibility Act","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2019\u002F882\u002Foj","Directive (EU) 2019\u002F882: accessibility requirements for banking services, ecommerce and other digital services, applicable since June 2025.",15,{"id":506,"label":507,"issuer":508,"region":423,"url":509,"description":510,"useCases":504,"indexable":212},"fatf-recommendations","FATF Recommendations","Financial Action Task Force","https:\u002F\u002Fwww.fatf-gafi.org\u002Fen\u002Fpublications\u002FFatfrecommendations\u002FFatf-recommendations.html","Global standards for anti money laundering and counter terrorist financing that national rules implement.",{"id":512,"label":513,"issuer":514,"region":155,"url":515,"description":516,"useCases":504,"indexable":212},"us-tcpa","Telephone Consumer Protection Act","Federal Communications Commission","https:\u002F\u002Fwww.fcc.gov\u002Fconsumers\u002Fguides\u002Fstop-unwanted-robocalls-and-texts","US consent rules for automated and prerecorded calls and texts; the FCC has confirmed AI generated voices count as artificial voices.",{"id":518,"label":519,"issuer":148,"region":149,"url":520,"description":521,"useCases":366,"indexable":212},"eu-amlr","EU Anti Money Laundering Regulation","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2024\u002F1624\u002Foj","Regulation (EU) 2024\u002F1624: the single EU rulebook for customer due diligence, beneficial ownership and suspicious transaction reporting.",{"id":523,"label":524,"issuer":525,"region":155,"url":526,"description":527,"useCases":367,"indexable":212},"us-bsa","Bank Secrecy Act","FinCEN","https:\u002F\u002Fwww.fincen.gov\u002Fresources\u002Fstatutes-and-regulations\u002Fbank-secrecy-act","US anti money laundering law: customer due diligence, suspicious activity reports and record keeping.",{"id":529,"label":530,"issuer":148,"region":149,"url":531,"description":532,"useCases":367,"indexable":212},"eu-psd2","PSD2","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2015\u002F2366\u002Foj","Payment Services Directive 2: strong customer authentication, transaction risk analysis exemptions and open banking access.",{"id":534,"label":535,"issuer":148,"region":149,"url":536,"description":537,"useCases":367,"indexable":212},"solvency-ii","Solvency II","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2009\u002F138\u002Foj","Directive 2009\u002F138\u002FEC: risk based capital, governance and model requirements for insurers.",{"id":539,"label":540,"issuer":541,"region":423,"url":542,"description":543,"useCases":367,"indexable":212},"telecom-consumer-rules","Telecom consumer protection rules","National telecom regulators","https:\u002F\u002Fwww.berec.europa.eu\u002F","National rules on telecom contracts, switching, billing disputes and marketing consent.",{"id":545,"label":546,"issuer":547,"region":155,"url":548,"description":549,"useCases":310,"indexable":212},"us-ecoa-reg-b","ECOA and Regulation B","Consumer Financial Protection Bureau","https:\u002F\u002Fwww.consumerfinance.gov\u002Frules-policy\u002Fregulations\u002F1002\u002F9\u002F","US fair lending rules, including specific reasons in adverse action notices, which also apply when credit decisions use AI models.",{"id":551,"label":552,"issuer":553,"region":149,"url":554,"description":555,"useCases":556,"indexable":212},"eba-loan-origination","EBA Guidelines on loan origination and monitoring","European Banking Authority","https:\u002F\u002Fwww.eba.europa.eu\u002Fregulation-and-policy\u002Fcredit-risk\u002Fguidelines-on-loan-origination-and-monitoring","Expectations for credit decisioning, including the use of automated models.",11,{"id":558,"label":559,"issuer":148,"region":149,"url":560,"description":561,"useCases":556,"indexable":212},"eecc","European Electronic Communications Code","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2018\u002F1972\u002Foj","Directive (EU) 2018\u002F1972: consumer protection, contract, switching and security rules for telecom operators.",{"id":563,"label":564,"issuer":148,"region":149,"url":565,"description":566,"useCases":556,"indexable":212},"mifid-ii","MiFID II","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2014\u002F65\u002Foj","Directive 2014\u002F65\u002FEU on markets in financial instruments: suitability and appropriateness of advice, record keeping and product governance.",{"id":568,"label":569,"issuer":457,"region":458,"url":570,"description":571,"useCases":63,"indexable":212},"mas-notice-626","MAS Notice 626","https:\u002F\u002Fwww.mas.gov.sg\u002Fregulation\u002Fnotices\u002Fnotice-626","Singapore's anti money laundering and counter terrorism financing requirements for banks.",{"id":573,"label":574,"issuer":575,"region":155,"url":576,"description":577,"useCases":578,"indexable":212},"us-fcra","Fair Credit Reporting Act","Federal Trade Commission","https:\u002F\u002Fwww.ftc.gov\u002Flegal-library\u002Fbrowse\u002Fstatutes\u002Ffair-credit-reporting-act","US rules on consumer reports, their accuracy and permissible use, relevant to credit scoring and screening.",8,{"id":580,"label":581,"issuer":148,"region":149,"url":582,"description":583,"useCases":578,"indexable":212},"eu-idd","Insurance Distribution Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2016\u002F97\u002Foj","Directive (EU) 2016\u002F97: conduct rules for selling insurance, including demands and needs testing and advice.",{"id":585,"label":586,"issuer":587,"region":588,"url":589,"description":590,"useCases":395,"indexable":212},"cbuae-ai-guidance","CBUAE guidance on AI and ML","Central Bank of the UAE","middle-east","https:\u002F\u002Fwww.centralbank.ae\u002F","UAE central bank expectations for the enabling technologies, AI and machine learning used by licensed financial institutions.",{"id":592,"label":593,"issuer":594,"region":149,"url":595,"description":596,"useCases":62,"indexable":212},"uk-psr-app-reimbursement","UK APP scam reimbursement rules","Payment Systems Regulator","https:\u002F\u002Fwww.psr.org.uk\u002Four-work\u002Fapp-scams\u002F","Mandatory reimbursement of authorised push payment scam victims by UK payment firms, which shifts scam losses onto banks.",{"id":598,"label":599,"issuer":148,"region":149,"url":600,"description":601,"useCases":340,"indexable":212},"eu-mortgage-credit-directive","EU Mortgage Credit Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2014\u002F17\u002Foj","Directive 2014\u002F17\u002FEU: creditworthiness assessment, disclosure and advice rules for residential mortgage lending.",{"id":603,"label":604,"issuer":605,"region":149,"url":606,"description":607,"useCases":340,"indexable":212},"pra-ss1-23","PRA SS1\u002F23 model risk management","Prudential Regulation Authority","https:\u002F\u002Fwww.bankofengland.co.uk\u002Fprudential-regulation\u002Fpublication\u002F2023\u002Fmay\u002Fmodel-risk-management-principles-for-banks-ss","UK model risk management principles for banks, covering AI and machine learning models.",{"id":609,"label":610,"issuer":611,"region":458,"url":612,"description":613,"useCases":614,"indexable":212},"au-scams-prevention-framework","Australian Scams Prevention Framework","Australian Treasury","https:\u002F\u002Ftreasury.gov.au\u002Fconsultation\u002Fc2024-573813","Economy wide obligations for banks, telcos and digital platforms to prevent, detect, disrupt and respond to scams.",3,{"id":616,"label":617,"issuer":148,"region":149,"url":618,"description":619,"useCases":614,"indexable":212},"eu-mar","EU Market Abuse Regulation","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2014\u002F596\u002Foj","Regulation (EU) 596\u002F2014: insider dealing and market manipulation, including the duty to detect and report suspicious orders and transactions.",{"id":621,"label":622,"issuer":457,"region":458,"url":623,"description":624,"useCases":614,"indexable":212},"mas-shared-responsibility-framework","MAS Shared Responsibility Framework","https:\u002F\u002Fwww.mas.gov.sg\u002Fregulation\u002Fguidelines\u002Fguidelines-on-shared-responsibility-framework","Singapore's framework that assigns banks and telcos duties and loss sharing for phishing scams.",{"id":626,"label":627,"issuer":628,"region":155,"url":629,"description":630,"useCases":614,"indexable":212},"nyc-local-law-144","NYC Local Law 144","New York City","https:\u002F\u002Fwww.nyc.gov\u002Fsite\u002Fdca\u002Fabout\u002Fautomated-employment-decision-tools.page","Bias audits and notices for automated employment decision tools used in hiring and promotion in New York City.",1792049859799]