[{"data":1,"prerenderedAt":579},["ShallowReactive",2],{"uc-payer-member-service-virtual-assistant":3,"uc-regulations":356},{"useCase":4,"evidence":182,"blitsAiDeployments":257,"benchmarks":258,"indicative":264,"related":267,"indexability":354,"includeUnpublished":188},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":16,"functions":19,"patterns":22,"channels":26,"audience":29,"autonomy":30,"adoptionStage":31,"segment":32,"problem":33,"problemStats":34,"howItWorks":35,"valueDrivers":36,"kpis":41,"indicativeValue":47,"macroEstimates":88,"feasibility":89,"implementation":101,"risk":135,"blitsAi":159,"faq":161,"related":174,"datePublished":177,"dateModified":177,"lastVerified":177,"changelog":178,"slug":181},"AI virtual assistant for health insurance member service","Payer member service assistant","AI virtual assistant for health plan members","An AI assistant answers health plan members on coverage, claims and providers. UnitedHealthcare says members using Avery needed no advocate 90% of the time.","published","A conversational AI agent that answers health plan members' questions about coverage, benefits, claims, costs and in network providers using their own plan data. Depending on the payer, it also estimates costs before care, schedules appointments, and hands the conversation to a live advocate with context when a question is too complex, sensitive or clinical to answer alone.",[12,13,14,15],"health plan chatbot","member self service virtual assistant","payer virtual assistant","health insurance AI assistant",[17,18],"healthcare","insurance",[20,21],"customer-service","claims",[23,24,25],"conversational-agent","rag-knowledge-assistant","agentic-workflow",[27,28],"mobile-app","web-chat","customer-facing","supervised-agent","emerging","front-office","A health plan member trying to understand a bill, check whether a procedure is covered, or find an\nin network specialist usually has to navigate several separate systems: a benefits summary, a\nprovider directory, a claims portal and a call center, often for a question that has a single,\nspecific answer buried in their own plan documents. Large payers field many of these routine\nquestions, and a member who cannot get a clear answer quickly either calls an advocate for\nsomething self service could resolve, or may put off care while the cost stays unclear.\n\nAnswering well is harder than it looks: every member has a different plan, different cost sharing\nand a different claims history, so a generic answer about \"health insurance\" is often wrong for the\nspecific person asking, and a wrong coverage answer can leave a member with a real, unexpected bill.",[],"1. **Authenticate the member.** The assistant confirms identity and pulls the member's own plan,\n   benefits, cost sharing and claims data, never a generic description of coverage.\n2. **Answer in plain language.** Questions like \"is my surgery covered, and how much will it cost\"\n   are answered with the member's specific coverage details, an in network provider list and a\n   personalized cost estimate.\n3. **Act.** Where the payer has connected the right systems, the assistant can check a claim's\n   status or send a digital ID card, and some assistants book care: UnitedHealthcare's Avery calls\n   network primary care providers to schedule an appointment on a member's behalf. The member does\n   not repeat information across systems.\n4. **Escalate with context.** When a question involves an appeal, a complaint, a denial or anything\n   needing clinical judgment, the assistant hands off to a live advocate with a full synopsis, so the\n   member does not start over.\n5. **Learn and widen coverage.** Each new topic area is measured for accuracy before the assistant is\n   allowed to answer it without a human in the loop, and coverage widens by plan type, language and\n   topic over time.",[37,38,39,40],"cost-to-serve","customer-experience","employee-productivity","inclusion-and-access",[42,43,44,45,46],"containment-rate","first-contact-resolution","customer-satisfaction","handling-time-reduction","interactions-handled",{"referenceOrg":48,"inputs":49,"formula":83,"currency":84,"period":85,"resultLabel":86,"caveat":87},"A health plan with 5 million members",[50,55,62,69,76],{"key":51,"label":52,"low":53,"high":53,"unit":51,"note":54},"members","Members",5000000,"The reference plan.",{"key":56,"label":57,"low":58,"high":59,"unit":60,"note":61},"contactsPerMember","Assisted contacts per member per year",1,2,"contacts per member per year","Editorial assumption for a health plan's member service volume; replace with your own.",{"key":63,"label":64,"low":65,"high":66,"unit":67,"note":68},"eligibleShare","Share of contacts suited to self service (coverage, claim status, provider search, cost estimate)",0.3,0.5,"fraction of contacts","Editorial assumption, replace with your own contact reason breakdown.",{"key":70,"label":71,"low":72,"high":73,"unit":74,"note":75},"containment","Share of eligible contacts the assistant resolves without an advocate",0.4,0.7,"fraction of eligible contacts","Conservative against the UnitedHealthcare figure: UnitedHealthcare says members using Avery needed no advocate 90% of the time, a company reported figure with no stated measurement period, member cohort or topic scope. Aetna's AI powered chat is the page's only other evidence record and publishes no resolution figure, so the 90% stands alone and the low end of the range stays well below it.",{"key":77,"label":78,"low":79,"high":80,"unit":81,"note":82},"costPerContact","Cost of an advocate handled contact",6,12,"USD per contact","Editorial assumption for a blended phone and chat health plan member service contact; replace with your own fully loaded cost.","members * contactsPerMember * eligibleShare * containment * costPerContact","USD","per year","Advocate handled contact cost avoided","Gross avoided contact cost only. It leaves out the cost of building and running the assistant, the cost of a wrong or incomplete answer, and any effect on member satisfaction, retention or appropriate care seeking.",[],{"complexity":90,"complexityNote":91,"dataPrerequisites":92,"integrations":96},"medium","Answering benefit and claims questions needs live, per member integration with the core claims administration, eligibility and provider directory systems. The accuracy bar is high: a wrong coverage answer creates a real, unexpected bill for the member, so grounding every answer in the member's own plan data matters more here than in most customer service use cases.",[93,94,95],"Member specific benefits, eligibility and cost sharing data reachable through APIs","Claims status and explanation of benefits data","An accurate, network specific provider directory",[97,98,99,100],"Core claims and benefits administration system","Provider directory and network status system","Appointment scheduling or provider call center system","CRM or case management system for advocate handover",{"steps":102,"guardrails":118,"humanInTheLoop":122,"kpisToInstrument":123,"failureModes":128},[103,106,109,112,115],{"title":104,"detail":105},"Start with the highest volume, lowest risk questions","Coverage lookups, claim status, ID card requests and provider search before cost estimates, appeals or anything involving a denial.",{"title":107,"detail":108},"Ground every answer in the member's own plan data","Never let the model generalize about \"health insurance\"; retrieve the member's specific plan document, benefit summary and claims record for every answer, and refuse when retrieval is uncertain.",{"title":110,"detail":111},"Design the advocate handover before launch","Build the escalation path and the context transfer to a live advocate first, so a question the assistant cannot answer well never becomes a dead end.",{"title":113,"detail":114},"Pilot with a defined member segment and measure per topic","Launch with one plan type or member group, track containment and accuracy per topic, and only widen once accuracy holds on a reviewed sample.",{"title":116,"detail":117},"Widen by plan type and language once accuracy holds","Add plan types, benefit designs and languages one at a time, each validated against its own plan documents before going live.",[119,120,121],"Answers only from the member's own verified plan, benefit and claims data, never a general guess about coverage","Automatic handover to a live advocate on appeals, complaints, denials and anything needing clinical judgment","Multi factor authentication before any account specific information is shared","Advocates own appeals, complaints, denials and anything requiring clinical judgment. They review a sample of contained conversations for accuracy every week, and each new topic area is approved before the assistant answers it unsupervised.",[124,125,126,127],"Containment rate per topic, counting repeat contacts within seven days as not contained","Accuracy of benefit and cost answers against the member's source plan documents, on a reviewed sample","Member satisfaction on assisted conversations versus advocate handled ones","Handover rate and handover reasons",[129,132],{"title":130,"detail":131},"Confidently wrong benefit answers","The assistant states a coverage or cost figure that is not accurate for the member's specific plan, creating a real bill or a denied expectation. Prevent by grounding every answer in the member's own plan document and refusing rather than guessing when retrieval is uncertain.",{"title":133,"detail":134},"Containment that hides frustration","Members give up rather than escalate, which looks like resolution in the dashboard. Count repeat contacts on the same topic and track satisfaction on contained conversations, not only the containment rate.",{"euAiAct":136,"regulations":139,"guidance":145,"controls":152,"incidents":158},{"tier":137,"basis":138},"limited","Article 50(1): members must be told they are talking to an AI system. Answering benefit and claims status questions is not itself an Annex III use. It would become high risk under Annex III point 5(c) if the same system assessed or priced an individual's health insurance risk, or under point 5(a) if it decided eligibility for a public health scheme; keep those decisions in the plan's existing underwriting and adjudication process, which this use case only informs the member about.",[140,141,142,143,144],"eu-ai-act","gdpr","hipaa","nist-ai-rmf","iso-42001",[146],{"title":147,"issuer":148,"region":149,"url":150,"note":151},"HIPAA Privacy Rule","US Department of Health and Human Services","north-america","https:\u002F\u002Fwww.hhs.gov\u002Fhipaa\u002Ffor-professionals\u002Fprivacy\u002Findex.html","Governs the use and disclosure of protected health information the assistant handles, including the authentication needed before releasing claims or benefit detail tied to an individual member.",[153,154,155,156,157],"Multi factor authentication before disclosing account specific benefit, cost or claims information","Grounding every benefit and cost answer in the member's own plan documents, with a refusal when retrieval is uncertain","Automatic handover on appeals, complaints, denials and anything needing clinical judgment","Logged, auditable trail of every answer and the plan document it was grounded in","Regular accuracy sampling of benefit and cost answers against the source plan documents",[],{"howToBuild":160},"On Blits.ai this is a customer facing **AI agent** combined with a **knowledge base** loaded per\nplan with approved benefit summaries and cost sharing documents, retrieved with hybrid search, so\nanswers are grounded in the member's actual plan rather than a general description of health\ninsurance. A small set of **custom functions** call the payer's claims, eligibility and provider\ndirectory systems as REST calls, each scoped to one action, such as claim status, ID card or\nprovider search; identity verification itself is done by the payer's own systems, reached the same\nway, so account specific detail is only shared once those systems confirm the member. Scheduling an\nappointment runs as an **agentic workflow** action, with human in the loop approval above a\nconfigurable threshold before the booking is made.\n\nThe same agent serves **web chat**, with the payer's mobile app connecting through the **REST or\nWebSocket API channel**, and **guardrails** and **PII masking** of member identifiers at the\ngateway. Configurable **handover rules** (or a flow) encode the escalation rules for appeals,\ncomplaints and denials and trigger **human handover**, with an AI summarized conversation history\npassed to the advocate, so the member does not repeat themselves. **Test suites** run per topic\nconversation sets before each release, and **analytics** show satisfaction and top intents out of\nthe box, with a custom\ncalculated statistic for handover rate. The platform is **model agnostic** and supports **EU and\nUAE data residency** for health plans operating outside the United States.",[162,165,168,171],{"question":163,"answer":164},"What can a payer virtual assistant actually resolve without a human?","It varies by company and by topic. UnitedHealthcare says that 90% of the time, members who use its Avery assistant have not required assistance from a live advocate; the company gives no measurement period, cohort or topic scope for that figure, and it is not a guarantee for every question. Aetna describes an AI powered chat in its member app that gives immediate answers and connects to its call centers when a member needs more help, but publishes no resolution figure.",{"question":166,"answer":167},"Is this the same as claims adjudication, prior authorization or a policy servicing assistant?","No. A member service assistant answers questions about coverage, cost and claim status using data the plan already holds; it does not decide whether a claim or a prior authorization request is approved. That belongs to the health insurance prior authorization and claims adjudication use case. A general insurance policy servicing assistant answers from one policy; a health plan assistant adds claims status, personalized cost estimates, provider search and, in the United States, protected health information under HIPAA (in the EU, health data is special category data under the GDPR).",{"question":169,"answer":170},"Is a payer virtual assistant high risk under the EU AI Act?","Usually not. It falls under the Article 50 transparency duty: members must know they are talking to AI. It would become high risk if it assessed or priced an individual's health insurance risk, or decided eligibility for a public health scheme, rather than only answering questions about an existing plan.",{"question":172,"answer":173},"What happens when the assistant cannot answer a question?","A well built assistant refuses to guess and hands off to a live advocate with the conversation context, rather than generating a plausible sounding but unverified answer about coverage or cost. UnitedHealthcare says Avery transfers members to advocates automatically when a live call is needed or requested.",[175,176],"health-prior-authorization-and-claims-adjudication","insurance-policy-servicing-agent","2026-10-13",[179],{"date":177,"note":180},"First published","payer-member-service-virtual-assistant",[183,218,237],{"title":184,"useCases":185,"organization":186,"vendors":190,"summary":191,"stage":192,"year":193,"channels":194,"languages":195,"metrics":197,"outcomeDisclosed":206,"sources":207,"verification":212,"grade":215,"id":216,"organizationSlug":217},"UnitedHealthcare: Avery AI companion for members",[181],{"name":187,"anonymized":188,"country":189,"region":149,"industry":17},"UnitedHealthcare",false,"US",[],"UnitedHealthcare introduced Avery, a generative AI companion available through the UnitedHealthcare app and myuhc.com, that answers members' questions about coverage, claims, costs, providers and rewards in natural language, gives customer advocates real time insights into a member's history so a handoff needs no repetition, and can call network primary care providers to schedule appointments on a member's behalf. At launch it was available to about 6.5 million members with employer sponsored plans and 160,000 Medicare Advantage members, with a stated plan to reach 20.5 million commercial, Medicare and Medicaid members by the end of 2026.","production",2026,[27,28],[196],"en",[198],{"kpi":42,"value":199,"unit":200,"qualifier":201,"period":202,"claimant":203,"quote":204,"sourceUrl":205},90,"percent","exact","reported in the March 26, 2026 launch release; measurement period not stated","organization","While 90% of the time, members who use Avery have not required assistance from an advocate, Avery will automatically transfer members to advocates when a live call is needed or requested.","https:\u002F\u002Fwww.unitedhealthgroup.com\u002Fnewsroom\u002F2026\u002F2026-03-26-uhc-introduces-ai-companion-empowering-people-with-simpler-navigation-personal-experience.html",true,[208],{"url":205,"title":209,"publisher":210,"date":211},"UnitedHealthcare Introduces AI Companion Empowering People with Simpler Navigation, Personal Experience","UnitedHealth Group","2026-03-26",{"level":213,"checkedAt":214},"source-verified","2026-09-28","B","unitedhealthcare-avery-member-assistant",null,{"title":219,"useCases":220,"organization":221,"vendors":223,"summary":224,"stage":192,"year":225,"channels":226,"languages":227,"metrics":228,"outcomeDisclosed":188,"sources":229,"verification":235,"grade":215,"id":236,"organizationSlug":217},"Aetna: AI powered chat in the Aetna Health app",[181],{"name":222,"anonymized":188,"country":189,"region":149,"industry":17},"Aetna",[],"In a July 29, 2025 press release, Aetna, a CVS Health company, said members would find a chat icon on the Aetna Health app home screen and core landing pages by the end of July. Aetna describes the chat as AI powered, giving members immediate answers and connecting to its call centers when a higher touch is needed. The same release lists claims cost visualization, personalized cost tracking, provider search and vaccine scheduling as other app features, so the chat sits inside a wider self service app. No usage or resolution figure is given for the chat itself.",2025,[27],[196],[],[230],{"url":231,"title":232,"publisher":233,"date":234},"https:\u002F\u002Fwww.cvshealth.com\u002Fnews\u002Finnovation\u002Faetna-launches-new-ai-and-digital-tools-to-improve-access-and-care.html","Aetna Launches New AI and Digital Tools to Improve Access and Care","CVS Health","2025-07-29",{"level":213,"checkedAt":177},"aetna-health-app-ai-chat",{"title":238,"useCases":239,"organization":240,"vendors":243,"summary":244,"stage":192,"year":225,"channels":245,"languages":246,"metrics":248,"outcomeDisclosed":206,"sources":249,"verification":254,"grade":215,"id":255,"organizationSlug":256},"Elevance Health: Virtual Assistant for member navigation",[181],{"name":241,"anonymized":188,"country":189,"region":149,"industry":17,"wikidata":242},"Elevance Health","Q677488",[],"Elevance Health expanded its Virtual Assistant, available through the Sydney Health app and Elevance Health affiliated health plan websites, to about 22 million members with commercial plans. Elevance Health describes it as using conversational technology, not as an AI system; it answers plain language questions such as whether a surgery is covered and what it will cost, returning in network providers, a personalized cost estimate and a coverage breakdown, and it integrates with the company's Find Care platform and supports Spanish. Expansion to Medicare members was planned for 2026. Elevance Health says early pilot results showed nearly 9 out of 10 pilot users were able to use the Virtual Assistant to find answers to their questions.",[27,28],[196,247],"es",[],[250],{"url":251,"title":252,"publisher":241,"date":253},"https:\u002F\u002Fwww.elevancehealth.com\u002Fnewsroom\u002Felevance-health-expands-virtual-assistant-to-help-members-navigate-healthcare-with-confidence","Elevance Health Expands Virtual Assistant to Help Members Navigate Healthcare with Confidence","2025-12-05",{"level":213,"checkedAt":214},"elevance-health-virtual-assistant","elevance-health",0,[259],{"kpi":42,"label":260,"unit":200,"aggregate":206,"higherIsBetter":206,"n":58,"nUpTo":257,"median":199,"min":199,"max":199,"byClaimant":261,"vendorOnly":188,"points":262},"Containment rate",{"organization":58,"vendor":257,"regulator":257,"independent":257},[263],{"evidenceId":216,"organization":187,"value":199,"qualifier":201,"claimant":203,"grade":215,"pooled":206},{"low":265,"high":266},3600000,42000000,[268,298,317,336],{"slug":175,"title":269,"shortTitle":270,"definition":271,"status":9,"industries":272,"functions":273,"patterns":276,"audience":281,"autonomy":282,"adoptionStage":283,"segment":21,"evidenceCount":79,"publicEvidenceCount":79,"organizations":284,"bestGrade":215,"headline":291,"lastVerified":297,"indexable":206},"AI for health insurance prior authorization and claims adjudication support","Health prior authorization and adjudication","AI for health insurance prior authorization and claims adjudication reads prior authorization requests, medical claims and appeals, and prepares a summary and recommendation for a clinician or adjudicator. It works from the clinical and billing documents attached to each case, extracts diagnoses, treatments and costs, and checks them against the policy and published clinical criteria, while the clinician or adjudicator makes every adverse decision.",[18,17],[21,274,275],"case-management","operations",[277,278,24,279,280],"document-processing","summarization","classification-and-routing","content-generation","employee-facing","copilot","early-adopters",[285,286,287,288,289,290],"Acentra Health","AdvanceCare","Centers for Medicare and Medicaid Services","Humana","ICICI Lombard","Manulife",{"kpi":45,"label":292,"unit":200,"n":293,"nUpTo":257,"kind":294,"value":295,"qualifier":201,"claimant":296,"organization":217,"vendorReported":206},"Handling time reduction",3,"median",50,"vendor","2026-09-27",{"slug":176,"title":299,"shortTitle":300,"definition":301,"status":9,"industries":302,"functions":303,"patterns":304,"audience":29,"autonomy":30,"adoptionStage":283,"segment":306,"evidenceCount":79,"publicEvidenceCount":79,"organizations":307,"bestGrade":215,"headline":314,"lastVerified":297,"indexable":206},"AI agent for insurance policy servicing","Policy servicing agent","An insurance policy servicing agent is AI that answers policyholders' coverage questions from their own policy documents and completes routine policy changes and document requests across chat, messaging and phone. Examples include address and vehicle changes, adding a named driver or item, payment method updates, and certificates and proof of cover, and it hands anything complex or sensitive to a human with the context.",[18],[20,275],[23,305,24,25],"voice-agent","policy-administration",[308,309,310,311,312,313],"LAQO","Lemonade","Nsure.com","Sun Life","Waterdrop","Zurich Insurance (Hong Kong)",{"kpi":42,"label":260,"unit":200,"n":59,"nUpTo":257,"kind":315,"value":295,"qualifier":316,"claimant":203,"organization":309,"vendorReported":188},"reported","at-least",{"slug":318,"title":319,"shortTitle":320,"definition":321,"status":9,"industries":322,"functions":323,"patterns":324,"audience":29,"autonomy":30,"adoptionStage":283,"segment":21,"evidenceCount":325,"publicEvidenceCount":325,"organizations":326,"bestGrade":215,"headline":333,"lastVerified":297,"indexable":206},"claims-first-notice-of-loss-agent","AI agent for first notice of loss claims intake","First notice of loss agent","A first notice of loss agent is an AI agent that takes the first notice of loss from a policyholder by phone, chat or app. It identifies the policy, collects the facts of the incident and the evidence the claim type needs, opens the claim in the claims system, tells the customer what happens next, and hands complex, injured or vulnerable claimants to a human handler.",[18],[21,20],[23,305,25,277],7,[327,328,329,309,330,331,332],"DOMCURA","Heritage Insurance Holdings","Hippo","Ohio Mutual Insurance Group","Progressive","Travelers",{"kpi":334,"label":335,"unit":200,"n":58,"nUpTo":257,"kind":315,"value":199,"qualifier":201,"claimant":296,"organization":327,"vendorReported":206},"accuracy","Accuracy",{"slug":337,"title":338,"shortTitle":339,"definition":340,"status":9,"industries":341,"functions":343,"patterns":344,"audience":29,"autonomy":30,"adoptionStage":31,"segment":21,"evidenceCount":293,"publicEvidenceCount":59,"organizations":346,"bestGrade":215,"headline":349,"lastVerified":297,"indexable":206},"travel-insurance-claims-and-assistance-agent","AI agent for travel insurance claims and assistance","Travel insurance claims and assistance","A travel insurance claims and assistance agent is an AI agent that helps insured travellers with claims and assistance around the clock, in their own language. It answers cover questions, takes claims for delays, cancellations, lost baggage and medical costs, reads the receipts and certificates travellers upload, settles simple claims within set limits, and connects medical emergencies and complex cases to the assistance team at once.",[18,342],"travel-and-hospitality",[21,20],[23,305,277,25,345],"translation",[347,348],"Allianz Partners","General Insurance Association of Singapore",{"kpi":350,"label":351,"unit":200,"n":257,"nUpTo":58,"kind":315,"value":352,"qualifier":353,"claimant":203,"organization":347,"vendorReported":188},"automation-rate","Automation rate",70,"up-to",{"indexable":206,"reasons":355},[],[357,364,369,376,382,389,395,402,410,417,424,430,436,443,448,455,461,467,474,479,484,490,496,503,508,513,519,524,531,536,544,550,556,562,568,573],{"id":140,"label":358,"issuer":359,"region":360,"url":361,"description":362,"useCases":363,"indexable":206},"EU AI Act","European Union","europe","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.",275,{"id":141,"label":365,"issuer":359,"region":360,"url":366,"description":367,"useCases":368,"indexable":206},"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.",246,{"id":144,"label":370,"issuer":371,"region":372,"url":373,"description":374,"useCases":375,"indexable":206},"ISO\u002FIEC 42001","ISO and IEC","global","https:\u002F\u002Fwww.iso.org\u002Fstandard\u002F81230.html","The international management system standard for AI.",143,{"id":143,"label":377,"issuer":378,"region":149,"url":379,"description":380,"useCases":381,"indexable":206},"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.",110,{"id":383,"label":384,"issuer":385,"region":360,"url":386,"description":387,"useCases":388,"indexable":206},"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.",81,{"id":390,"label":391,"issuer":359,"region":360,"url":392,"description":393,"useCases":394,"indexable":206},"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.",72,{"id":396,"label":397,"issuer":398,"region":360,"url":399,"description":400,"useCases":401,"indexable":206},"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.",51,{"id":403,"label":404,"issuer":405,"region":406,"url":407,"description":408,"useCases":409,"indexable":206},"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":411,"label":412,"issuer":413,"region":406,"url":414,"description":415,"useCases":416,"indexable":206},"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":418,"label":419,"issuer":420,"region":149,"url":421,"description":422,"useCases":423,"indexable":206},"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.",23,{"id":425,"label":426,"issuer":359,"region":360,"url":427,"description":428,"useCases":429,"indexable":206},"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.",22,{"id":431,"label":432,"issuer":433,"region":372,"url":434,"description":435,"useCases":429,"indexable":206},"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":437,"label":438,"issuer":439,"region":360,"url":440,"description":441,"useCases":442,"indexable":206},"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":142,"label":444,"issuer":148,"region":149,"url":445,"description":446,"useCases":447,"indexable":206},"HIPAA","https:\u002F\u002Fwww.hhs.gov\u002Fhipaa\u002Findex.html","US rules for the privacy and security of protected health information.",17,{"id":449,"label":450,"issuer":451,"region":372,"url":452,"description":453,"useCases":454,"indexable":206},"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.",15,{"id":456,"label":457,"issuer":359,"region":360,"url":458,"description":459,"useCases":460,"indexable":206},"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.",14,{"id":462,"label":463,"issuer":464,"region":149,"url":465,"description":466,"useCases":460,"indexable":206},"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":468,"label":469,"issuer":470,"region":149,"url":471,"description":472,"useCases":473,"indexable":206},"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.",13,{"id":475,"label":476,"issuer":359,"region":360,"url":477,"description":478,"useCases":473,"indexable":206},"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":480,"label":481,"issuer":359,"region":360,"url":482,"description":483,"useCases":473,"indexable":206},"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":485,"label":486,"issuer":487,"region":149,"url":488,"description":489,"useCases":80,"indexable":206},"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":491,"label":492,"issuer":493,"region":372,"url":494,"description":495,"useCases":80,"indexable":206},"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":497,"label":498,"issuer":499,"region":360,"url":500,"description":501,"useCases":502,"indexable":206},"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":504,"label":505,"issuer":359,"region":360,"url":506,"description":507,"useCases":502,"indexable":206},"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":509,"label":510,"issuer":359,"region":360,"url":511,"description":512,"useCases":502,"indexable":206},"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":514,"label":515,"issuer":405,"region":406,"url":516,"description":517,"useCases":518,"indexable":206},"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":520,"label":521,"issuer":359,"region":360,"url":522,"description":523,"useCases":518,"indexable":206},"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":525,"label":526,"issuer":527,"region":149,"url":528,"description":529,"useCases":530,"indexable":206},"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":532,"label":533,"issuer":359,"region":360,"url":534,"description":535,"useCases":325,"indexable":206},"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":537,"label":538,"issuer":539,"region":540,"url":541,"description":542,"useCases":543,"indexable":206},"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.",5,{"id":545,"label":546,"issuer":359,"region":360,"url":547,"description":548,"useCases":549,"indexable":206},"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.",4,{"id":551,"label":552,"issuer":553,"region":360,"url":554,"description":555,"useCases":549,"indexable":206},"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":557,"label":558,"issuer":559,"region":360,"url":560,"description":561,"useCases":549,"indexable":206},"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":563,"label":564,"issuer":565,"region":406,"url":566,"description":567,"useCases":293,"indexable":206},"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":569,"label":570,"issuer":359,"region":360,"url":571,"description":572,"useCases":293,"indexable":206},"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":574,"label":575,"issuer":576,"region":149,"url":577,"description":578,"useCases":293,"indexable":206},"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.",1791904361986]