[{"data":1,"prerenderedAt":588},["ShallowReactive",2],{"uc-ai-dubbing-and-voice-localization-for-video":3,"uc-regulations":365},{"useCase":4,"evidence":173,"blitsAiDeployments":261,"benchmarks":262,"indicative":269,"related":272,"indexability":363,"includeUnpublished":179},{"title":5,"shortTitle":6,"seoTitle":5,"metaDescription":7,"status":8,"definition":9,"aliases":10,"industries":15,"functions":17,"patterns":20,"channels":24,"audience":25,"autonomy":26,"adoptionStage":27,"problem":28,"problemStats":29,"howItWorks":30,"valueDrivers":31,"kpis":36,"indicativeValue":41,"macroEstimates":75,"feasibility":76,"implementation":89,"risk":131,"blitsAi":151,"faq":153,"related":166,"datePublished":168,"dateModified":168,"lastVerified":168,"changelog":169,"slug":172},"AI dubbing and voice localization for video","AI dubbing for video","AI dubbing translates video audio into other languages. YouTube reports over 6 million daily viewers of auto dubbed content; Prime Video runs a pilot.","published","AI dubbing transcribes a video's speech, translates it and generates a synthetic voice track in another language, so titles can be released in languages they were never dubbed into. Publishers and streamers use it for licensed catalogs and creator videos, and Prime Video describes a pilot in which localization professionals work with the AI to control quality.",[11,12,13,14],"AI voice dubbing","automated video dubbing","synthetic dubbing","auto dubbing",[16],"media-and-entertainment",[18,19],"operations","marketing",[21,22,23],"translation","content-generation","speech-analytics",[],"customer-facing","supervised-agent","emerging","Most video is released in one language. Subtitles are cheap and fast, but they ask the viewer to\nread instead of watch, and a viewer who wants to listen in their own language has no option when\na title was never dubbed. Prime Video says language barriers can prevent customers from enjoying\ncontent that originates in other countries and territories.\n\nStudio dubbing solves the quality side and fails on cost and time. A series needs translators,\nadapters, casting, recording sessions and mixing for every target language, so catalogs are\ndubbed into a handful of large languages and the long tail of titles is skipped. Deepdub, an AI\ndubbing vendor, calls the cost of localizing content libraries into European languages a\nlongstanding challenge for free ad supported streaming channels, and the CEO of Love TV Channels\ndescribes difficult trade offs between cost and reach.",[],"1. **Prepare the audio.** The pipeline takes the dialogue track, or separates speech from music\n   and effects, and transcribes it with timestamps and speaker labels.\n2. **Translate and adapt.** A translation step produces text that fits the timing of each line,\n   using a glossary for names, brand terms and recurring phrases. Adaptation matters as much as\n   translation, because a literal sentence that runs long cannot fit the scene.\n3. **Generate the voices.** A speech model produces the target language voice for each speaker,\n   either from a stock voice or from a voice built for the character or the creator. Voice\n   cloning should only happen with the consent of the person whose voice it is.\n4. **Review.** Linguists check meaning, tone and timing and fix the lines the model got wrong.\n   Prime Video describes its pilot as a hybrid in which localization professionals collaborate\n   with AI to control quality.\n5. **Mix and publish.** The new track is mixed under the original music and effects and added to\n   the title as an alternative audio track. Viewers pick it in the player or through a preferred\n   language setting, and the original audio stays available.",[32,33,34,35],"revenue-growth","cost-to-serve","speed","inclusion-and-access",[37,38,39,40],"cost-reduction","processing-time-reduction","users-served","revenue-uplift",{"referenceOrg":42,"inputs":43,"formula":70,"currency":71,"period":72,"resultLabel":73,"caveat":74},"A video publisher that dubs 200 hours of catalog into two or three languages each year (an editorial example, not a publisher named on this page)",[44,50,56,63],{"key":45,"label":46,"low":47,"high":47,"unit":48,"note":49},"contentHours","Hours of content dubbed per language",200,"hours per year","Editorial assumption, replace with your own catalog plan.",{"key":51,"label":52,"low":53,"high":54,"unit":51,"note":55},"languages","Target languages",2,3,"Editorial assumption of two or three target languages. Replace with your own language plan.",{"key":57,"label":58,"low":59,"high":60,"unit":61,"note":62},"studioCostPerHour","Cost of studio dubbing per finished hour and language",1500,3000,"USD per hour per language","Editorial assumption for scripted and factual content. Replace with a quote from your own dubbing studio.",{"key":64,"label":65,"low":66,"high":67,"unit":68,"note":69},"costReduction","Share of the studio cost the AI workflow removes",0.3,0.6,"fraction of studio cost","Editorial assumption, replace with your own quote. Set well below Deepdub's general product claim of reductions of over 80% against traditional dubbing benchmarks, which does not say what is reduced and is not independently published, and because the human review step stays in the cost.","contentHours * languages * studioCostPerHour * costReduction","USD","per year","Dubbing cost avoided","Gross dubbing cost avoided only. It leaves out the platform fees, the linguist review time that remains, rights and talent consents, any new audience revenue and the cost of titles that a reviewer rejects.",[],{"complexity":77,"complexityNote":78,"dataPrerequisites":79,"integrations":84},"medium","The build needs dialogue stems or a clean mix, a media asset system that can receive new audio tracks, a glossary per title, signed consents for any cloned voice and a queue for linguist review. Lip sync, which changes the video itself, adds a separate image processing step.",[80,81,82,83],"Original audio with dialogue separated from music and effects where possible","Scripts or transcripts, when they exist, to check the transcription","A glossary of names, brand terms and recurring phrases per title","Written consent from every person whose voice is cloned",[85,86,87,88],"Media asset management system holding the source audio and the finished tracks","Speech to text, translation and text to speech services","Review queue for linguists with the video and the proposed lines side by side","Video player or streaming platform that supports alternative audio tracks",{"steps":90,"guardrails":106,"humanInTheLoop":112,"kpisToInstrument":113,"failureModes":118},[91,94,97,100,103],{"title":92,"detail":93},"Start with titles that have no dub","Choose titles and languages where the alternative is no audio localization at all, as Prime Video does by limiting its pilot to titles without dubbing support. This avoids replacing a studio dub that viewers already like.",{"title":95,"detail":96},"Set the quality bar with a reviewer panel","Have native speaker linguists score a sample of dubbed minutes on meaning, tone, timing and voice naturalness, and write down the score a title needs before it is released.",{"title":98,"detail":99},"Build the glossary and the consent register","Keep one glossary per title and one register of voice consents with the scope of each (language, title, duration). Block cloning when a consent is missing.",{"title":101,"detail":102},"Release as an alternative track","Publish the AI dub next to the original audio and let viewers choose, with a label that the voice is synthetic. Watch listening time per track before widening to more titles.",{"title":104,"detail":105},"Widen by language and genre","Add languages and genres in the order of the scores your reviewer panel gives. Keep studio dubbing for titles where timing and performance carry the scene.",[107,108,109,110,111],"No voice cloning without a signed consent that covers the language and the title","Every dubbed title passes a native speaker review before it is released","A visible label that the audio is synthetic, plus a way for viewers to choose the original","Glossary checks that block wrong names, brand terms and sensitive words","A take down route for a rights holder or performer who objects","Linguists approve the translation and the voice for each title and own the final cut. The rights team owns consents, and an editor decides which titles are not dubbed at all, such as content where performance carries the work or where a wrong word has legal weight.",[114,115,116,117],"Cost and turnaround days per finished hour, split into AI steps and human review","Linguist score per dubbed sample and the share of lines edited by reviewers","Listening time on the dubbed track versus the original, per language","Viewer complaints and reports about the dubbed audio",[119,122,125,128],{"title":120,"detail":121},"Fluent but wrong translation","A confident line changes the meaning of a sentence or a joke. Prevent with linguist review on every title and extra checks on names, numbers and legal terms.",{"title":123,"detail":124},"Voices that sound flat or the same","Many characters get similar voices and emotional scenes lose their effect. Test voice casting on the hardest scenes first and keep studio dubbing for titles where performance matters.",{"title":126,"detail":127},"Timing that drifts","A translation that is longer than the original forces fast speech or cuts lines. Adapt the text to the timing of each line, not only the meaning.",{"title":129,"detail":130},"Consent and rights gaps","A voice is cloned beyond the scope that was agreed. Keep the consent register as a hard gate in the workflow.",{"euAiAct":132,"regulations":135,"guidance":138,"controls":145,"incidents":150},{"tier":133,"basis":134},"limited","Article 50 sets transparency duties for synthetic audio, and they have applied since 2 August 2026. Providers of systems that generate synthetic audio must mark the output in a machine readable way (Article 50(2)). Deployers of a system that produces a deep fake, meaning audio that resembles existing persons, objects, places, entities or events and would falsely appear authentic, must disclose that it was artificially generated (Article 50(4)), with a lighter duty for evidently artistic, creative, satirical or fictional work. Whether a dub is a deep fake depends on the content and the use. Dubbing is not an Annex III use.",[136,137],"eu-ai-act","gdpr",[139],{"title":140,"issuer":141,"region":142,"url":143,"note":144},"Article 50, transparency obligations for providers and deployers of certain AI systems","European Union","europe","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2024\u002F1689\u002Foj","Sets the marking duty for synthetic audio and the disclosure duty for deep fakes.",[146,147,148,149],"Machine readable marking of synthetic audio and a visible label for viewers","Consent register for every cloned voice, linked to the title and language","Review record that shows who approved each dubbed title and when","Change control when the translation or voice model is replaced",[],{"howToBuild":152},"On Blits.ai this is an **agentic workflow** that is triggered through the API or on a schedule.\nA custom function fetches the transcript or the dialogue track from the media asset system,\nand the workflow translates the text with **language translation** or an LLM, retrieving the\nglossary of names, brand terms and recurring phrases from the **knowledge base**. Custom\nfunctions call the publisher's own speech and voice services where audio has to be generated,\nand **human in the loop** approval lets a reviewer approve or reject each output before a\nsecond custom function returns the result to the publisher's system. Blits.ai does not render\nthe dubbed audio track, edit video or create lip sync: voice generation, mixing, the linguist\nediting tool and delivery to the player stay in the publisher's media pipeline.\n\n**Test suites** score samples of translated lines against reference translations on every\nchange of model, the speech to text quality check utility compares transcription providers on\nword error rate, and **analytics** and the run history show volumes and outcomes. The platform is **model\nagnostic**, so translation providers can be changed per language, and EU or UAE\n**data residency** applies to where the audio is processed.",[154,157,160,163],{"question":155,"answer":156},"How much cheaper is AI dubbing than studio dubbing?","This page has no measured saving from a named deployment. Deepdub, a vendor, says in a release that its AI dubbing delivers reductions of over 80% versus traditional dubbing benchmarks. The release does not say what is reduced, the claim is about Deepdub's product in general and not a result at Love TV Channels, and it is not independently published. Plan on a smaller saving, because linguist review and the cost of rejected titles stay in the budget.",{"question":158,"answer":159},"Is a human involved in AI dubbing at large platforms?","Prime Video describes its pilot as a hybrid in which localization professionals collaborate with AI to control quality. YouTube describes an automatic system that creators can switch off or replace with their own dubs, and does not state a review step.",{"question":161,"answer":162},"Does AI dubbing need to be labelled under the EU AI Act?","Since 2 August 2026, Article 50 requires synthetic audio to be marked in a machine readable way by the provider. The deployer must disclose a deep fake, meaning audio that resembles existing persons, objects, places, entities or events and would falsely appear authentic. Whether a dub counts depends on the content. A visible label in the player is one way to show it.",{"question":164,"answer":165},"How many viewers watch AI dubbed videos on YouTube?","YouTube reports that as of December 2025 over 6 million viewers watched 10 minutes or more of auto dubbed content every day, in a service that offers 27 languages.",[167],"audio-and-video-transcription-and-captioning","2026-10-13",[170],{"date":168,"note":171},"First published","ai-dubbing-and-voice-localization-for-video",[174,205,234],{"title":175,"useCases":176,"organization":177,"vendors":183,"summary":186,"stage":187,"year":188,"channels":189,"languages":190,"metrics":193,"outcomeDisclosed":179,"sources":194,"verification":200,"grade":202,"id":203,"organizationSlug":204},"Prime Video: AI aided dubbing pilot on licensed titles without a dub",[172],{"name":178,"anonymized":179,"country":180,"region":181,"industry":16,"wikidata":182},"Amazon Prime Video",false,"US","north-america","Q4740856",[184],{"name":178,"role":185},"in-house","In March 2025 Prime Video began an AI dubbing pilot in English and Latin American Spanish on 12 licensed movies and series. It applies only to titles that have no existing dub, and Amazon describes it as a hybrid approach in which localization professionals collaborate with AI to keep quality under control. The announcement gives no results.","pilot",2025,[],[191,192],"en","es",[],[195],{"url":196,"title":197,"publisher":198,"date":199},"https:\u002F\u002Faboutamazon.com\u002Fnews\u002Fentertainment\u002Fprime-video-ai-dubbing-english-spanish","Prime Video begins an AI dubbing pilot program on licensed movies and series","Amazon","2025-03-05",{"level":201,"checkedAt":168},"source-verified","B","prime-video-ai-aided-dubbing",null,{"title":206,"useCases":207,"organization":208,"vendors":211,"summary":213,"stage":214,"year":188,"channels":215,"languages":216,"metrics":217,"outcomeDisclosed":226,"sources":227,"verification":232,"grade":202,"id":233,"organizationSlug":204},"YouTube: auto dubbing translates creators' videos into 27 languages",[172],{"name":209,"anonymized":179,"country":180,"region":181,"industry":16,"wikidata":210},"YouTube","Q866",[212],{"name":209,"role":185},"YouTube auto dubbing takes the original audio of a video, translates it and dubs it over the video in other languages. YouTube says it is available in 27 languages, with eight offering Expressive Speech, and that millions of channels already use it. Viewers choose through their preferred language settings or the player which videos they hear dubbed, and creators can submit their own dubs or turn auto dubbing off.","scaled",[],[],[218],{"kpi":39,"value":219,"unit":220,"qualifier":221,"period":222,"claimant":223,"quote":224,"sourceUrl":225},6000000,"count","at-least","per day, December 2025, viewers watching 10 minutes or more of auto dubbed content","organization","As of December 2025, there were over 6 million viewers watching 10 minutes or more of auto dubbed content on YouTube every day.","https:\u002F\u002Fblog.youtube\u002Fcreator-and-artist-stories\u002Fyoutube-auto-dubbing-explained\u002F",true,[228],{"url":225,"title":229,"publisher":230,"date":231},"YouTube auto dubbing, explained","YouTube Blog","2026-05-15",{"level":201,"checkedAt":168},"youtube-auto-dubbing",{"title":235,"useCases":236,"organization":237,"vendors":240,"summary":244,"stage":245,"year":246,"channels":247,"languages":248,"metrics":251,"outcomeDisclosed":179,"sources":252,"verification":258,"grade":259,"id":260,"organizationSlug":204},"Love TV Channels: Deepdub AI dubbing of Cineflix factual series for European FAST channels",[172],{"name":238,"anonymized":179,"country":239,"region":142,"industry":16},"Love TV Channels","ES",[241],{"name":242,"role":243},"Deepdub","platform","Love TV Channels, a Barcelona based publisher of thematic free ad supported streaming (FAST) channels, partnered with Deepdub in February 2026 to dub premium factual programming from Cineflix Rights into Castilian Spanish, Italian and French. The titles had not been available in those languages on its channels. The release gives no results from Love TV Channels. It carries one general claim from Deepdub, the vendor, of reductions of over 80% versus traditional dubbing benchmarks, which does not say what is reduced and is not a measured result of this deployment.","announced",2026,[],[192,249,250],"it","fr",[],[253],{"url":254,"title":255,"publisher":256,"date":257},"https:\u002F\u002Fwww.prnewswire.com\u002Fil\u002Fnews-releases\u002Fdeepdub-and-love-tv-channels-establish-a-scalable-model-to-overcome-localization-barriers-and-premier-previously-unreleased-content-on-european-fast-channels-302694430.html","Deepdub and Love TV Channels Establish a Scalable Model to Overcome Localization Barriers and Premier Previously Unreleased Content on European FAST Channels","Deepdub (PR Newswire)","2026-02-23",{"level":201,"checkedAt":168},"C","love-tv-channels-deepdub-fast-dubbing",0,[263],{"kpi":39,"label":264,"unit":220,"aggregate":179,"higherIsBetter":226,"n":265,"nUpTo":261,"median":219,"min":219,"max":219,"byClaimant":266,"vendorOnly":179,"points":267},"Users served",1,{"organization":265,"vendor":261,"regulator":261,"independent":261},[268],{"evidenceId":233,"organization":209,"value":219,"qualifier":221,"claimant":223,"grade":202,"pooled":226},{"low":270,"high":271},180000,1080000,[273,304,323,341],{"slug":167,"title":274,"shortTitle":275,"definition":276,"status":8,"industries":277,"functions":280,"patterns":282,"audience":283,"autonomy":284,"adoptionStage":285,"evidenceCount":286,"publicEvidenceCount":287,"organizations":288,"bestGrade":202,"headline":296,"lastVerified":303,"indexable":226},"AI transcription, subtitles and captions for audio and video","Transcription and captioning","AI transcription and captioning is AI that transcribes recorded audio and video, such as podcasts, broadcasts, lessons, interviews and hearings, in several languages. It separates the speakers and produces timed transcripts, subtitles and captions for a human editor to check, delivered as files for publishing or the archive.",[16,278,279],"education","cross-industry",[18,281],"knowledge-management",[23,21,22],"back-office","copilot","mainstream",8,7,[289,290,291,292,293,294,295],"Ateme","BBC","Comeen","Pacers Sports & Entertainment","Sveriges Television (SVT)","University of Florida","Warner Bros. Discovery",{"kpi":37,"label":297,"unit":298,"n":265,"nUpTo":261,"kind":299,"value":300,"qualifier":301,"claimant":302,"organization":295,"vendorReported":226},"Cost reduction","percent","reported",50,"exact","vendor","2026-09-26",{"slug":305,"title":306,"shortTitle":307,"definition":308,"status":8,"industries":309,"functions":310,"patterns":311,"audience":25,"autonomy":313,"adoptionStage":27,"segment":314,"evidenceCount":315,"publicEvidenceCount":315,"organizations":316,"bestGrade":259,"headline":204,"lastVerified":322,"indexable":226},"live-sports-commentary-generation","AI generated live sports commentary and data storytelling","Live sports commentary","AI live sports commentary turns a sporting event's own data into written commentary and insight for fans as the action happens, instead of or alongside a human broadcaster. It works from inputs such as ball and player tracking, match events and statistics, and can optionally use text to speech to voice the output for a spoken version.",[16],[19,18],[22,312,21],"summarization","autonomous","fan engagement",5,[317,318,319,320,321],"The All England Lawn Tennis Club (Wimbledon)","Bundesliga (DFL Deutsche Fußball Liga)","Masters Tournament (Augusta National)","Major League Baseball (MLB)","United States Tennis Association (USTA)","2026-09-30",{"slug":324,"title":325,"shortTitle":326,"definition":327,"status":8,"industries":328,"functions":329,"patterns":330,"audience":333,"autonomy":284,"adoptionStage":285,"segment":334,"evidenceCount":315,"publicEvidenceCount":315,"organizations":335,"bestGrade":202,"headline":204,"lastVerified":322,"indexable":226},"automated-sports-highlights-and-clipping","AI agent for automated sports highlights and clipping","Sports highlights and clipping","An AI agent for sports highlights and clipping watches a live sports broadcast and detects key moments such as goals, saves or penalties as they happen. It automatically extracts and reformats a clip and puts it in front of an editor to review and publish, instead of a person watching every feed and clipping moments by hand.",[16],[18,19],[331,332,22],"computer-vision","classification-and-routing","employee-facing","content operations",[336,337,338,339,340],"Deutsche Telekom","Fox Sports","Lega Serie A","National Basketball Association (NBA)","Premier Sports",{"slug":342,"title":343,"shortTitle":344,"definition":345,"status":8,"industries":346,"functions":348,"patterns":349,"audience":283,"autonomy":26,"adoptionStage":285,"evidenceCount":350,"publicEvidenceCount":350,"organizations":351,"bestGrade":202,"headline":357,"lastVerified":362,"indexable":226},"product-content-and-catalog-enrichment","AI product content and catalog enrichment for online retail","Product content and catalog enrichment","AI catalog enrichment is AI that drafts and repairs product content, such as titles, descriptions and alt text, for online retailers at catalog scale. It also extracts missing attributes such as color, size and material from supplier text and product images, and checks its own output before the content is published to the store and to search engines. A human owns the rules, the quality thresholds and the exceptions.",[347,279],"retail-and-ecommerce",[19,18],[22,331,332],6,[198,352,353,354,355,356],"eBay","Elemis","Etsy","Walmart","Zalando",{"kpi":358,"label":359,"unit":298,"n":265,"nUpTo":261,"kind":299,"value":360,"qualifier":361,"claimant":223,"organization":356,"vendorReported":179},"accuracy","Accuracy",75,"approximately","2026-09-27",{"indexable":226,"reasons":364},[],[366,370,375,383,390,397,403,410,418,425,432,438,444,451,458,465,471,477,484,489,494,501,507,514,519,524,530,535,541,546,553,559,565,571,577,582],{"id":136,"label":367,"issuer":141,"region":142,"url":143,"description":368,"useCases":369,"indexable":226},"EU AI Act","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":137,"label":371,"issuer":141,"region":142,"url":372,"description":373,"useCases":374,"indexable":226},"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":376,"label":377,"issuer":378,"region":379,"url":380,"description":381,"useCases":382,"indexable":226},"iso-42001","ISO\u002FIEC 42001","ISO and IEC","global","https:\u002F\u002Fwww.iso.org\u002Fstandard\u002F81230.html","The international management system standard for AI.",143,{"id":384,"label":385,"issuer":386,"region":181,"url":387,"description":388,"useCases":389,"indexable":226},"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.",110,{"id":391,"label":392,"issuer":393,"region":142,"url":394,"description":395,"useCases":396,"indexable":226},"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":398,"label":399,"issuer":141,"region":142,"url":400,"description":401,"useCases":402,"indexable":226},"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":404,"label":405,"issuer":406,"region":142,"url":407,"description":408,"useCases":409,"indexable":226},"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":411,"label":412,"issuer":413,"region":414,"url":415,"description":416,"useCases":417,"indexable":226},"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":419,"label":420,"issuer":421,"region":414,"url":422,"description":423,"useCases":424,"indexable":226},"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":426,"label":427,"issuer":428,"region":181,"url":429,"description":430,"useCases":431,"indexable":226},"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":433,"label":434,"issuer":141,"region":142,"url":435,"description":436,"useCases":437,"indexable":226},"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":439,"label":440,"issuer":441,"region":379,"url":442,"description":443,"useCases":437,"indexable":226},"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":445,"label":446,"issuer":447,"region":142,"url":448,"description":449,"useCases":450,"indexable":226},"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":452,"label":453,"issuer":454,"region":181,"url":455,"description":456,"useCases":457,"indexable":226},"hipaa","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.",17,{"id":459,"label":460,"issuer":461,"region":379,"url":462,"description":463,"useCases":464,"indexable":226},"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":466,"label":467,"issuer":141,"region":142,"url":468,"description":469,"useCases":470,"indexable":226},"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":472,"label":473,"issuer":474,"region":181,"url":475,"description":476,"useCases":470,"indexable":226},"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":478,"label":479,"issuer":480,"region":181,"url":481,"description":482,"useCases":483,"indexable":226},"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":485,"label":486,"issuer":141,"region":142,"url":487,"description":488,"useCases":483,"indexable":226},"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":490,"label":491,"issuer":141,"region":142,"url":492,"description":493,"useCases":483,"indexable":226},"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":495,"label":496,"issuer":497,"region":181,"url":498,"description":499,"useCases":500,"indexable":226},"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.",12,{"id":502,"label":503,"issuer":504,"region":379,"url":505,"description":506,"useCases":500,"indexable":226},"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":508,"label":509,"issuer":510,"region":142,"url":511,"description":512,"useCases":513,"indexable":226},"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":515,"label":516,"issuer":141,"region":142,"url":517,"description":518,"useCases":513,"indexable":226},"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":520,"label":521,"issuer":141,"region":142,"url":522,"description":523,"useCases":513,"indexable":226},"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":525,"label":526,"issuer":413,"region":414,"url":527,"description":528,"useCases":529,"indexable":226},"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":531,"label":532,"issuer":141,"region":142,"url":533,"description":534,"useCases":529,"indexable":226},"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":536,"label":537,"issuer":538,"region":181,"url":539,"description":540,"useCases":286,"indexable":226},"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.",{"id":542,"label":543,"issuer":141,"region":142,"url":544,"description":545,"useCases":287,"indexable":226},"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":547,"label":548,"issuer":549,"region":550,"url":551,"description":552,"useCases":315,"indexable":226},"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":554,"label":555,"issuer":141,"region":142,"url":556,"description":557,"useCases":558,"indexable":226},"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":560,"label":561,"issuer":562,"region":142,"url":563,"description":564,"useCases":558,"indexable":226},"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":566,"label":567,"issuer":568,"region":142,"url":569,"description":570,"useCases":558,"indexable":226},"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":572,"label":573,"issuer":574,"region":414,"url":575,"description":576,"useCases":54,"indexable":226},"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":578,"label":579,"issuer":141,"region":142,"url":580,"description":581,"useCases":54,"indexable":226},"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":583,"label":584,"issuer":585,"region":181,"url":586,"description":587,"useCases":54,"indexable":226},"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.",1791904356506]