[{"data":1,"prerenderedAt":638},["ShallowReactive",2],{"uc-hospital-lobby-and-wayfinding-assistant":3,"uc-regulations":409},{"useCase":4,"evidence":185,"blitsAiDeployments":271,"benchmarks":272,"indicative":278,"related":281,"indexability":407,"includeUnpublished":191},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":16,"functions":18,"patterns":21,"channels":27,"audience":30,"autonomy":31,"adoptionStage":32,"segment":33,"problem":34,"problemStats":35,"howItWorks":36,"valueDrivers":37,"kpis":42,"indicativeValue":47,"macroEstimates":85,"feasibility":86,"implementation":99,"risk":140,"blitsAi":164,"faq":166,"related":179,"datePublished":180,"dateModified":180,"lastVerified":180,"changelog":181,"slug":184},"AI assistant for hospital lobby questions, symptom routing and wayfinding","Hospital lobby assistant","AI hospital lobby assistant: routing, wayfinding","A lobby kiosk answers patients, routes a described symptom to a specialty and gives directions. Gama Hospital and Princess Alexandra Hospital run lobby assistants.","published","A hospital lobby assistant is a kiosk, tablet or avatar screen in the entrance hall that patients and visitors talk to. It answers questions about doctors, clinics and services in their own language, points a described symptom to the right specialty, and gives directions to the ward or room. It does not diagnose, and urgent cases should go to staff.",[12,13,14,15],"hospital AI front desk","hospital wayfinding avatar kiosk","AI patient guide kiosk","hospital reception voice assistant",[17],"healthcare",[19,20],"customer-service","knowledge-management",[22,23,24,25,26],"voice-agent","conversational-agent","rag-knowledge-assistant","classification-and-routing","digital-human",[28,29,26],"kiosk","voice","customer-facing","supervised-agent","emerging","front-of-house","The reception desk of a large hospital fields the same questions all day: which doctor treats this\ncomplaint, where is the laboratory, is my report ready, when does the clinic open. In Tars's\ncase study, Gama Hospital's IT director lists an information queue that had become an operational\nbottleneck in Saudi Arabia,\nwith receptionists who lack the medical knowledge to route a symptom, so patients were sent from\none doctor to another, and a call center of sixteen phone lines that was frequently engaged.\n\nLanguage adds to it. Gama serves Arabic speaking patients and a large expatriate workforce, and\nthe receptionist on shift may not speak the patient's language. Mappedin's case study on Princess Alexandra\nHospital lists the same themes: complex layouts, staff under pressure and the need for multilingual\nhelp. A lobby assistant takes the repeated questions at the entrance at any hour, so staff keep\ntheir time for patients who need a person.",[],"1. **The patient walks up and speaks.** The assistant runs on a kiosk, a lobby tablet or an avatar\n   screen. Voice input suits people who are standing, carrying things, elderly or uncomfortable\n   typing in a second language. The agent detects the language and answers in it.\n2. **It answers from the hospital's own data.** Doctors mapped to specialties, department and\n   floor locations, clinic timings and services form the knowledge it is allowed to use.\n3. **It routes a symptom to a specialty.** A described complaint such as back pain or headache\n   maps to a specialty and the doctors available. Gama's agent points chest pain straight\n   to Cardiology. A safer rule sends chest pain and other red flag symptoms to staff or the\n   emergency department at once. Bangkok Hospital's registration kiosk uses an AI symptom checker\n   to recommend a clinic.\n4. **It gives directions.** The answer names the floor and the nearest landmark, or gives\n   verbal and visual directions on an indoor map, as the Princess Alexandra kiosk does with an indoor\n   mapping SDK.\n5. **It hands over.** Anything urgent, unclear or outside the approved content goes to the front\n   desk or a nurse.",[38,39,40,41],"cost-to-serve","customer-experience","employee-productivity","inclusion-and-access",[43,44,45,46],"interactions-handled","containment-rate","contact-deflection","customer-satisfaction",{"referenceOrg":48,"inputs":49,"formula":80,"currency":81,"period":82,"resultLabel":83,"caveat":84},"A hospital with one to three lobby kiosks",[50,56,63,68,73],{"key":51,"label":52,"low":53,"high":54,"unit":51,"note":55},"kiosks","Lobby kiosks in service",1,3,"Editorial assumption. Replace with your own number of entrances and devices.",{"key":57,"label":58,"low":59,"high":60,"unit":61,"note":62},"questionsPerKioskPerMonth","Questions answered per kiosk per month",400,1000,"questions per month","PAH about 800. Mappedin reports about 800 questions a month at one Princess Alexandra Hospital kiosk, a vendor report.",{"key":64,"label":65,"low":66,"high":66,"unit":64,"note":67},"months","Months in service",12,"One full year.",{"key":69,"label":70,"low":53,"high":54,"unit":71,"note":72},"staffMinutesPerQuestion","Staff minutes avoided per question","minutes","Staff time avoided per question is an editorial assumption. Mappedin's case study mentions 3 minutes per conversation, so the range stays at or below it.",{"key":74,"label":75,"low":76,"high":77,"unit":78,"note":79},"staffCost","Fully loaded cost of one front desk hour",15,30,"USD per hour","Editorial assumption, replace with your own payroll data.","kiosks * questionsPerKioskPerMonth * months * staffMinutesPerQuestion \u002F 60 * staffCost","USD","per year","Annual front desk time released","Counts front desk minutes only. It leaves out platform and integration cost, content upkeep, the effect on phone line load, wrong routing avoided, accessibility gains and patient satisfaction. Whether the minutes turn into lower cost depends on staffing rosters.",[],{"complexity":87,"complexityNote":88,"dataPrerequisites":89,"integrations":94},"medium","The build needs a maintained directory of doctors, specialties, floors and clinic timings, a clinical owner who approves the symptom to specialty mapping and the urgent symptom rules, indoor maps for directions, and a kiosk or tablet in the lobby with a microphone that works in a noisy hall. Linking to live doctor availability adds an integration with the scheduling system.",[90,91,92,93],"Doctor, specialty, department and floor directory with clinic timings","Symptom to specialty mapping approved by clinical leads, with urgent symptom rules","Indoor floor plans and landmarks for directions","Languages the patient population speaks, including local dialects",[95,96,97,98],"Doctor scheduling or availability system, for live availability","Indoor mapping or wayfinding platform","Front desk or nurse call queue, for handover","Analytics store for questions asked and unanswered",{"steps":100,"guardrails":116,"humanInTheLoop":121,"kpisToInstrument":122,"failureModes":127},[101,104,107,110,113],{"title":102,"detail":103},"Count what the desk is asked","Log a week of front desk and call center questions and group them. Start with the top four or five, which at Gama were symptom routing, doctor availability, medical report questions and wayfinding.",{"title":105,"detail":106},"Get the symptom rules signed off","Clinical leads approve the symptom to specialty table and write the list of symptoms that always mean urgent staff contact. Put each rule in the test set.",{"title":108,"detail":109},"Pilot at one entrance","Place one device where queues form, with a staff member close by. Review a sample of transcripts daily for the first weeks, including the hours after the desk quiets down.",{"title":111,"detail":112},"Test languages with real speakers","Test each language and dialect with patients and interpreters, in the lobby's real noise, before adding it to the list.",{"title":114,"detail":115},"Add live availability and maps last","Connect scheduling and indoor maps once the directory answers are right, and track which questions the agent could not answer.",[117,118,119,120],"The assistant does not diagnose and says that it routes to a specialty only","Urgent symptoms such as chest pain go to staff or emergency services first, with a clear message","Answers only from the approved directory and policies, with a plain statement when it does not know","AI disclosure on the screen and no storage of identifying health details in logs","A front desk or nurse is always reachable from the device and sees the transcript on handover. Clinical leads review a sample of routing decisions each month and the symptom table after any change to specialties or doctors.",[123,124,125,126],"Questions per day and per visitor, by hour and by language","Share of sessions that end without staff contact, and share handed over","Questions the agent could not answer, grouped by topic","Wrong specialty referrals reported by patients or clinics",[128,131,134,137],{"title":129,"detail":130},"A routed symptom hides a serious condition","Keyword style routing can send a worrying complaint to a routine clinic. Keep a conservative urgent list, add a standing line that the guide does not diagnose, and review misses with clinicians.",{"title":132,"detail":133},"The directory goes stale","Doctors move, clinics change hours and floors close. Give the directory an owner and a review date, and alert when answers cite entries older than the limit.",{"title":135,"detail":136},"Noise and accents break voice input","A busy lobby degrades recognition for the languages that most need help. Test in the hall, keep a touch fallback, and track failed sessions by language.",{"title":138,"detail":139},"Patients treat it as clinical advice","A confident answer reads as a medical opinion. Keep the wording to routing and information, and show how to reach a nurse.",{"euAiAct":141,"regulations":144,"guidance":150,"controls":157,"incidents":163},{"tier":142,"basis":143},"context-dependent","A guide that answers directory questions and gives directions is a limited risk system with transparency duties (Article 50). If it assesses symptoms in a way that influences care, it can count as medical device software, which the AI Act treats as high risk through Article 6(1) and Annex I when the device needs a third party conformity assessment. Whether symptom routing is medical device software depends on its intended purpose, so assess it under the EU MDR or UK medical device rules before launch.",[145,146,147,148,149],"eu-ai-act","gdpr","uk-gdpr","hipaa","sdaia-ai-ethics",[151],{"title":152,"issuer":153,"region":154,"url":155,"note":156},"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.",[158,159,160,161,162],"AI disclosure on screen at the start of every session","Clinical owner and review date for the symptom to specialty table and the directory","Urgent symptom rules tested on every content or model change","Masked, time limited logs with no storage of identifying health details","Privacy impact assessment covering voice recordings in a public hall",[],{"howToBuild":165},"On Blits.ai the lobby guide is an **AI agent** with a **knowledge base** built from the\nhospital's doctor, specialty, department and clinic timing documents, retrieved with **hybrid\nsearch**, plus **custom functions** that read live doctor availability from the scheduling\nsystem. It runs on a kiosk or tablet through **voice** channels, or as a **digital human**,\nwith several languages in one agent.\n\n**Guardrails** keep answers inside the approved directory and block diagnosis, **PII masking**\nremoves personal details from logs, and **human handover** passes urgent or unclear cases to the\nfront desk with the transcript. **Test suites** replay the urgent symptom and routing questions\nbefore each change, **analytics** show questions and gaps by hour and language, and the platform\nis **model agnostic** with EU or UAE data residency.",[167,170,173,176],{"question":168,"answer":169},"Does a hospital lobby assistant diagnose patients?","No. Gama Hospital's agent takes a symptom and works out which specialty the patient should see. That is routing, not diagnosis; red flag symptoms such as chest pain should go to staff or the emergency department, under rules clinicians approve.",{"question":171,"answer":172},"What results have hospitals reported?","Mappedin reports about 800 questions a month at the Princess Alexandra Hospital kiosk, about 35% of them wayfinding. Tars reports that nearly half of the conversations at Gama Hospital happen after 6pm. Both are vendor reports, and neither gives a containment rate or time saved.",{"question":174,"answer":175},"Which languages can it support?","Gama's agent handles Arabic, English, Hindi, Tamil and Malayalam. Princess Alexandra's kiosk offers five languages including British Sign Language. Each language needs testing in the real lobby with native speakers.",{"question":177,"answer":178},"Is it high risk under the EU AI Act?","Directory answers and directions carry transparency duties. Symptom routing that affects care can make the product medical device software, which changes the risk class, so check the design with a regulatory adviser.",[],"2026-11-11",[182],{"date":180,"note":183},"First published","hospital-lobby-and-wayfinding-assistant",[186,214,242],{"title":187,"useCases":188,"organization":189,"vendors":194,"summary":198,"stage":199,"year":200,"channels":201,"languages":202,"metrics":203,"outcomeDisclosed":191,"sources":204,"verification":209,"grade":211,"id":212,"organizationSlug":213},"Bangkok Hospital: Agnos Health Smart Registration kiosks with AI symptom screening",[184],{"name":190,"anonymized":191,"country":192,"region":193,"industry":17},"Bangkok Hospital",false,"TH","asia-pacific",[195],{"name":196,"role":197},"Agnos Health","platform","Bangkok Hospital built the Smart Registration system with Agnos Health, a medical AI startup, and runs it at the registration department of its headquarters hospital. Patients register at self service kiosks or on staff tablets. The kiosk checks identity by AI face recognition against an ID card or passport, runs an AI symptom checker that recommends a clinic, verifies insurance automatically and collects electronic consent. The hospital says the system aims to cut registration steps by up to 45%, which is a target, and publishes no measured result. This is a registration and clinic recommendation kiosk with an AI symptom checker, so it fits the page only in part: the description does not mention voice or open conversation.","production",2024,[28],[],[],[205],{"url":206,"title":207,"publisher":190,"date":208},"https:\u002F\u002Fwww.bangkokhospital.com\u002Fen\u002Fbangkok\u002Fcontent\u002Fnews-bangkok-hospital-and-agnos-health-introducing-the-smart-registration-innovation-pioneer","Bangkok Hospital and Agnos Health Introducing the Smart Registration Innovation Pioneer Using AI for Patient Registration","2024-06-26",{"level":210,"checkedAt":180},"source-verified","B","bangkok-hospital-agnos-health-smart-registration-kiosk",null,{"title":215,"useCases":216,"organization":217,"vendors":221,"summary":224,"stage":199,"year":225,"channels":226,"languages":227,"metrics":233,"outcomeDisclosed":234,"sources":235,"verification":239,"grade":240,"id":241,"organizationSlug":213},"Gama Hospital: Gama AI Smart Guide voice agent in the hospital lobby",[184],{"name":218,"anonymized":191,"country":219,"region":220,"industry":17},"Gama Hospital","SA","middle-east",[222],{"name":223,"role":197},"Tars","Gama Hospital, a multi specialty private hospital in Al Khobar, Saudi Arabia, launched the Gama AI Smart Guide in November 2025: a voice first AI agent on tablets in the lobby. Patients speak in Arabic, English, Hindi, Tamil or Malayalam, describe a symptom, and are pointed to a specialty, told when doctors are available and given the floor and nearest landmark. The agent runs on the hospital's own mapping of doctors to specialties, departments, floors and clinic timings, and sends a severe symptom such as chest pain to Cardiology first. The vendor's case study reports that nearly half of conversations take place after 6pm and that patients ask more than three questions per visit on average. It publishes no containment or time saving figure.",2025,[28,29],[228,229,230,231,232],"ar","en","hi","ta","ml",[],true,[236],{"url":237,"title":238,"publisher":223},"https:\u002F\u002Fhellotars.com\u002Fcase-studies\u002Fgama-hospital-lobby-ai-agent","How Gama Hospital Turned Its Crowded Lobby Into a 24\u002F7 Multilingual AI Front Desk",{"level":210,"checkedAt":180},"C","gama-hospital-tars-ai-smart-guide-lobby",{"title":243,"useCases":244,"organization":245,"vendors":248,"summary":253,"stage":199,"year":225,"channels":254,"languages":255,"metrics":256,"outcomeDisclosed":234,"sources":265,"verification":269,"grade":240,"id":270,"organizationSlug":213},"Princess Alexandra Hospital: PRSONAS iHealthAssist avatar kiosk for information and wayfinding",[184],{"name":246,"anonymized":191,"country":247,"region":154,"industry":17},"Princess Alexandra Hospital","GB",[249,251],{"name":250,"role":197},"PRSONAS",{"name":252,"role":197},"Mappedin","Princess Alexandra Hospital in Harlow, England, uses a PRSONAS iHealthAssist avatar kiosk that answers visitors' questions and guides them to wards, rooms, services and amenities, with indoor maps from the Mappedin SDK. It gives navigation support around the clock in five languages, including British Sign Language. Mappedin's case study reports about 800 questions a month, of which about 35% are wayfinding and 65% general information. The figures come from a technology partner, not from the hospital.",[28,26],[],[257],{"kpi":43,"value":258,"unit":259,"qualifier":260,"period":261,"claimant":262,"quote":263,"sourceUrl":264},800,"count","approximately","per month, on average","vendor","In one month, on average, 800 questions are asked and totaling 40 hours of interaction (estimate 3 minutes per conversation).","https:\u002F\u002Fwww.mappedin.com\u002Fresources\u002Fcase-study\u002Fhow-prsonas-ihealthassist-and-mappedin-transform-the-patient-experience\u002F",[266],{"url":264,"title":267,"publisher":252,"date":268},"Bringing indoor spaces to life: How PRSONAS iHealthAssist & Mappedin transform the patient experience","2025-06-11",{"level":210,"checkedAt":180},"princess-alexandra-hospital-prsonas-ihealthassist",0,[273],{"kpi":43,"label":274,"unit":259,"aggregate":191,"higherIsBetter":234,"n":53,"nUpTo":271,"median":258,"min":258,"max":258,"byClaimant":275,"vendorOnly":234,"points":276},"Interactions handled",{"organization":271,"vendor":53,"regulator":271,"independent":271},[277],{"evidenceId":270,"organization":246,"value":258,"qualifier":260,"claimant":262,"grade":240,"pooled":234},{"low":279,"high":280},1200,54000,[282,336,351,382],{"slug":283,"title":284,"shortTitle":285,"definition":286,"status":9,"industries":287,"functions":289,"patterns":291,"audience":30,"autonomy":31,"adoptionStage":292,"evidenceCount":293,"publicEvidenceCount":294,"organizations":295,"bestGrade":327,"headline":328,"lastVerified":335,"indexable":234},"citizen-information-assistant","AI assistant for citizen information and government services","Citizen information assistant","A citizen information assistant is an AI assistant that answers residents' and businesses' questions about government services in plain language, grounded only in official guidance with links to the source. It points them to the right online service or office, and hands anything personal, urgent or outside its content to a human with the context attached.",[288],"government",[290,19,20],"citizen-services",[24,23,22,25],"mainstream",33,31,[296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326],"Abu Dhabi Government (TAMM)","National Agency for Information Society (AKSHI), Albania","Australian Taxation Office","Bundesagentur für Arbeit","Change Please","City of Amarillo","City of Helsinki","Department of Information and Communications Technology (DICT)","Ministry of Digital Transformation of Ukraine (Diia)","Dubai Land Department (DLD)","Dubai Police","Driver and Vehicle Licensing Agency","Estonian Information System Authority (RIA)","Foreign, Commonwealth and Development Office","Gangnam-gu Office","Gemeente Tilburg","Ghana National Disaster Management Organisation","Government Digital Service","Government of the City of Buenos Aires","Madrid Destino","Ministério da Gestão e da Inovação em Serviços Públicos (MGI)","Ministry of Hajj and Umrah","Ministry of Interior (Saudi Arabia)","Montgomery County Government","City of New York","Ministry of Digital Affairs of Poland","Qatar Central Bank","Qatar Ministry of Commerce and Industry","Roads and Transport Authority, Dubai (RTA)","Vocational Education Sector, Ministry of Education, Higher Education and Vocational Education (Sri Lanka)","Sunshine Coast Council","A",{"kpi":46,"label":329,"unit":330,"n":331,"nUpTo":271,"kind":332,"value":333,"qualifier":334,"claimant":262,"organization":319,"vendorReported":234},"Customer satisfaction","percent",2,"reported",50,"exact","2026-09-27",{"slug":337,"title":338,"shortTitle":339,"definition":340,"status":9,"industries":341,"functions":342,"patterns":343,"audience":30,"autonomy":345,"adoptionStage":32,"evidenceCount":54,"publicEvidenceCount":54,"organizations":346,"bestGrade":211,"headline":213,"lastVerified":350,"indexable":234},"patient-previsit-education-avatar","AI avatar for pre visit patient education","Pre visit patient avatar","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.",[17],[19,20],[26,344,23,24],"content-generation","assist",[347,348,349],"ChristianaCare","The Ottawa Hospital","Vanderbilt University Medical Center","2026-10-14",{"slug":352,"title":353,"shortTitle":354,"definition":355,"status":9,"industries":356,"functions":359,"patterns":361,"audience":30,"autonomy":364,"adoptionStage":365,"evidenceCount":366,"publicEvidenceCount":367,"organizations":368,"bestGrade":211,"headline":213,"lastVerified":381,"indexable":234},"ai-visitor-and-tour-guide","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.",[357,358,288],"travel-and-hospitality","media-and-entertainment",[19,360,20],"marketing",[24,23,22,26,362,363],"computer-vision","translation","autonomous","early-adopters",14,13,[369,370,371,372,373,374,315,375,376,377,378,379,380],"Art Basel","Bloomberg Connects","Centre Pompidou","Elliott Museum","Leeds Castle","Liverpool City Region Destination Partnership","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":383,"title":384,"shortTitle":385,"definition":386,"status":9,"industries":387,"functions":389,"patterns":391,"audience":393,"autonomy":345,"adoptionStage":365,"segment":394,"evidenceCount":395,"publicEvidenceCount":395,"organizations":396,"bestGrade":211,"headline":403,"lastVerified":335,"indexable":234},"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.",[388],"telecommunications",[390,19,20],"sales",[24,26,23,392],"recommendation-and-personalization","employee-facing","front-office",6,[397,398,399,400,401,402],"Bouygues Telecom","Deutsche Telekom","Orange Slovakia","Singtel","T-Mobile","Vodafone New Zealand",{"kpi":404,"label":405,"unit":330,"n":53,"nUpTo":271,"kind":332,"value":406,"qualifier":334,"claimant":262,"organization":397,"vendorReported":234},"accuracy","Accuracy",95,{"indexable":234,"reasons":408},[],[410,415,420,428,436,442,448,455,462,469,475,481,487,493,500,507,512,518,523,529,534,539,545,551,558,563,568,574,581,586,592,598,604,611,617,622,627,633],{"id":145,"label":411,"issuer":153,"region":154,"url":412,"description":413,"useCases":414,"indexable":234},"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.",298,{"id":146,"label":416,"issuer":153,"region":154,"url":417,"description":418,"useCases":419,"indexable":234},"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.",268,{"id":421,"label":422,"issuer":423,"region":424,"url":425,"description":426,"useCases":427,"indexable":234},"iso-42001","ISO\u002FIEC 42001","ISO and IEC","global","https:\u002F\u002Fwww.iso.org\u002Fstandard\u002F81230.html","The international management system standard for AI.",149,{"id":429,"label":430,"issuer":431,"region":432,"url":433,"description":434,"useCases":435,"indexable":234},"nist-ai-rmf","NIST AI Risk Management Framework","NIST","north-america","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":147,"label":437,"issuer":438,"region":154,"url":439,"description":440,"useCases":441,"indexable":234},"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.",85,{"id":443,"label":444,"issuer":153,"region":154,"url":445,"description":446,"useCases":447,"indexable":234},"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":449,"label":450,"issuer":451,"region":154,"url":452,"description":453,"useCases":454,"indexable":234},"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":456,"label":457,"issuer":458,"region":193,"url":459,"description":460,"useCases":461,"indexable":234},"mas-ai-risk-management","MAS AI risk management guidelines","Monetary Authority of Singapore","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":193,"url":466,"description":467,"useCases":468,"indexable":234},"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":153,"region":154,"url":472,"description":473,"useCases":474,"indexable":234},"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":424,"url":479,"description":480,"useCases":474,"indexable":234},"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":432,"url":485,"description":486,"useCases":474,"indexable":234},"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":148,"label":488,"issuer":489,"region":432,"url":490,"description":491,"useCases":492,"indexable":234},"HIPAA","US Department of Health and Human Services","https:\u002F\u002Fwww.hhs.gov\u002Fhipaa\u002Findex.html","US rules for the privacy and security of protected health information.",21,{"id":494,"label":495,"issuer":496,"region":154,"url":497,"description":498,"useCases":499,"indexable":234},"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":501,"label":502,"issuer":503,"region":432,"url":504,"description":505,"useCases":506,"indexable":234},"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.",16,{"id":508,"label":509,"issuer":153,"region":154,"url":510,"description":511,"useCases":76,"indexable":234},"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.",{"id":513,"label":514,"issuer":515,"region":424,"url":516,"description":517,"useCases":76,"indexable":234},"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":519,"label":520,"issuer":153,"region":154,"url":521,"description":522,"useCases":366,"indexable":234},"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":524,"label":525,"issuer":526,"region":432,"url":527,"description":528,"useCases":367,"indexable":234},"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":530,"label":531,"issuer":153,"region":154,"url":532,"description":533,"useCases":367,"indexable":234},"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":535,"label":536,"issuer":153,"region":154,"url":537,"description":538,"useCases":367,"indexable":234},"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":540,"label":541,"issuer":542,"region":424,"url":543,"description":544,"useCases":367,"indexable":234},"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":546,"label":547,"issuer":548,"region":432,"url":549,"description":550,"useCases":66,"indexable":234},"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":552,"label":553,"issuer":554,"region":154,"url":555,"description":556,"useCases":557,"indexable":234},"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":559,"label":560,"issuer":153,"region":154,"url":561,"description":562,"useCases":557,"indexable":234},"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":564,"label":565,"issuer":153,"region":154,"url":566,"description":567,"useCases":557,"indexable":234},"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":569,"label":570,"issuer":458,"region":193,"url":571,"description":572,"useCases":573,"indexable":234},"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.",10,{"id":575,"label":576,"issuer":577,"region":432,"url":578,"description":579,"useCases":580,"indexable":234},"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":582,"label":583,"issuer":153,"region":154,"url":584,"description":585,"useCases":580,"indexable":234},"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":587,"label":588,"issuer":589,"region":220,"url":590,"description":591,"useCases":395,"indexable":234},"cbuae-ai-guidance","CBUAE guidance on AI and ML","Central Bank of the UAE","https:\u002F\u002Fwww.centralbank.ae\u002F","UAE central bank expectations for the enabling technologies, AI and machine learning used by licensed financial institutions.",{"id":593,"label":594,"issuer":153,"region":154,"url":595,"description":596,"useCases":597,"indexable":234},"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.",5,{"id":599,"label":600,"issuer":601,"region":154,"url":602,"description":603,"useCases":597,"indexable":234},"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":605,"label":606,"issuer":607,"region":154,"url":608,"description":609,"useCases":610,"indexable":234},"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.",4,{"id":612,"label":613,"issuer":614,"region":193,"url":615,"description":616,"useCases":54,"indexable":234},"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.",{"id":618,"label":619,"issuer":153,"region":154,"url":620,"description":621,"useCases":54,"indexable":234},"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":623,"label":624,"issuer":458,"region":193,"url":625,"description":626,"useCases":54,"indexable":234},"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":628,"label":629,"issuer":630,"region":432,"url":631,"description":632,"useCases":54,"indexable":234},"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.",{"id":149,"label":634,"issuer":635,"region":220,"url":636,"description":637,"useCases":54,"indexable":234},"SDAIA AI ethics principles","Saudi Data and AI Authority","https:\u002F\u002Fsdaia.gov.sa\u002Fen\u002FSDAIA\u002Fabout\u002FDocuments\u002Fai-principles.pdf","Saudi Arabia's national AI ethics principles, applied across sectors including finance and government.",1794393606150]