[{"data":1,"prerenderedAt":602},["ShallowReactive",2],{"uc-marketing-and-product-content-localization":3,"uc-regulations":393},{"useCase":4,"evidence":177,"blitsAiDeployments":270,"benchmarks":271,"indicative":290,"related":293,"indexability":391,"includeUnpublished":184},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":18,"functions":23,"patterns":25,"channels":28,"audience":31,"autonomy":32,"adoptionStage":33,"problem":34,"problemStats":35,"howItWorks":36,"valueDrivers":37,"kpis":42,"indicativeValue":47,"macroEstimates":75,"feasibility":76,"implementation":89,"risk":130,"blitsAi":156,"faq":158,"related":168,"datePublished":172,"dateModified":172,"lastVerified":172,"changelog":173,"slug":176},"AI localization of marketing, product and web content","Content localization","AI localization for marketing and web content","AI translates and adapts campaigns, product pages and web content for each market. Google Cloud reports Swarovski localizes campaigns 10x faster with AI.","published","AI that translates and adapts an organization's commercial content, such as campaigns, emails, product pages, help content and websites, for each market and language, using the brand's glossary, style guide and past approved translations, and routes the output to human linguists and local marketers for review in proportion to how visible and risky the content is.",[12,13,14,15,16,17],"AI translation for marketing","AI transcreation","machine translation with post editing","website localization AI","multilingual content generation","LLM localization",[19,20,21,22],"cross-industry","retail-and-ecommerce","professional-services","manufacturing",[24],"marketing",[26,27],"translation","content-generation",[29,30],"internal-tools","api","employee-facing","supervised-agent","early-adopters","A brand that sells in twenty markets needs every campaign, product page, email and help article in\ntwenty languages, adapted to local tone, regulation and culture, and it needs them at the same time\nas the source market. Traditional localization runs through agencies and translation vendors, and\nevery language adds review and delivery time. The risk is that smaller markets get content late,\nget less of it, or get a literal translation that reads badly.\n\nClassic machine translation solved part of this for high volume, low visibility text, but it did\nnot follow brand voice, terminology or local marketing conventions well enough for campaigns.\nLarge language models can take a glossary, a style guide and examples in the prompt, adapt rather\nthan translate, and check their own output, which moves the human effort from translating to\nreviewing.",[],"1. **Prepare the language assets.** Glossaries, do not translate lists, style guides per market\n   and a memory of past approved translations are loaded as reference material.\n2. **Classify the content.** Each item is tiered by visibility and risk: a legal notice or a hero\n   campaign line gets full human review, a long tail product description or help article may get\n   sampling only.\n3. **Translate and adapt.** The AI produces the target version with the terminology and tone\n   rules applied, adapts idioms, units, currencies and cultural references, and flags passages\n   it is unsure about.\n4. **Check quality.** Automated checks catch terminology violations, missing placeholders, length\n   limits and numbers that changed; a quality estimate decides which segments go to a linguist.\n5. **Review and learn.** Linguists and local marketers edit where needed, and their approved\n   versions flow back into the translation memory and glossary for the next job.",[38,39,40,41],"speed","cost-to-serve","inclusion-and-access","revenue-growth",[43,44,45,46],"processing-time-reduction","productivity-gain","users-served","cost-reduction",{"referenceOrg":48,"inputs":49,"formula":70,"currency":71,"period":72,"resultLabel":73,"caveat":74},"A consumer brand that localizes 3 million words of commercial content a year",[50,56,63],{"key":51,"label":52,"low":53,"high":53,"unit":54,"note":55},"words","Translated words per year, all target languages",3000000,"words per year","The reference brand, for example 300,000 source words into 10 languages.",{"key":57,"label":58,"low":59,"high":60,"unit":61,"note":62},"costPerWord","Current cost per translated word",0.1,0.2,"USD per word","Editorial assumption for professional human translation with review. Replace with your own vendor rates.",{"key":64,"label":65,"low":66,"high":67,"unit":68,"note":69},"savingShare","Share of localization cost saved",0.15,0.3,"fraction of cost","Editorial assumption, replace with your own. No evidence record on this page reports a cost figure (Bosch Digital mentions saving time and costs without a number), and human review remains for visible and regulated content, so the range is kept conservative.","words * costPerWord * savingShare","USD","per year","Localization cost avoided","Direct translation cost only. It leaves out the value of launching in all markets at the same time, the cost of the models and tooling, and the internal review time that remains.",[],{"complexity":77,"complexityNote":78,"dataPrerequisites":79,"integrations":84},"low","The models are good enough for most commercial content. The work is building the glossary and style guides, tiering content by risk, and connecting the content management systems so text does not travel by spreadsheet.",[80,81,82,83],"A glossary with approved and forbidden terms per language","Style guides per market, including tone and formality","A translation memory of past approved translations","A content inventory tiered by visibility, legal weight and risk",[85,86,87,88],"Content management system and ecommerce platform","Translation management system or translation memory","Marketing automation and email platform","Digital asset management for images with text",{"steps":90,"guardrails":106,"humanInTheLoop":111,"kpisToInstrument":112,"failureModes":117},[91,94,97,100,103],{"title":92,"detail":93},"Tier the content","Sort content into tiers: legal and regulated text, high visibility campaign copy, product and help content, and internal or user generated text. Decide the review level per tier before choosing any tool.",{"title":95,"detail":96},"Build the language assets","Consolidate glossaries, style guides and translation memories per market, and have local marketers approve them. The AI's output will only be as consistent as these assets.",{"title":98,"detail":99},"Benchmark against your own translations","Take a sample of content your linguists already approved, translate it with the candidate setup, and have reviewers score both blind before deciding where to use AI.",{"title":101,"detail":102},"Automate the checks, not only the translation","Add automatic checks for terminology, numbers, placeholders, length limits and brand names, and use quality estimation to send only uncertain segments to a linguist.",{"title":104,"detail":105},"Feed corrections back","Store every approved correction in the translation memory and glossary, and track which languages and content types still need heavy editing.",[107,108,109,110],"Human review for legal, regulated, safety and price related content in every language","Glossary and do not translate lists enforced automatically on every output","Numbers, prices, dates and product specifications checked against the source","No publication of machine output in a tier that requires review until a reviewer signs off","Local marketers and professional linguists own the glossaries and style guides, review content in the higher tiers, and sample the lower tiers. Legal or compliance reviewers approve regulated text in each market, as they would for a human translation.",[113,114,115,116],"Turnaround time from source approval to publication per language","Edit distance or share of segments changed by reviewers, per language and content type","Cost per word or per asset, including review","Terminology and number errors found after publication",[118,121,124,127],{"title":119,"detail":120},"Fluent but wrong","The translation reads well but changes a number, a claim or a legal meaning. Check numbers and claims automatically and keep humans on regulated text.",{"title":122,"detail":123},"Brand voice drift","Each market's output slowly diverges from the brand's tone. Keep style guides current and sample output against them.",{"title":125,"detail":126},"Scaled thin pages","Automatically translated pages published in bulk can be treated as low value by search engines. Localize what people in that market need, and review it.",{"title":128,"detail":129},"Language law breaches","Some jurisdictions require certain content in the local language with specific quality or precedence. Check local language requirements per market.",{"euAiAct":131,"regulations":134,"guidance":137,"controls":150,"incidents":155},{"tier":132,"basis":133},"context-dependent","Translating and adapting commercial content is not an Annex III use and makes no decisions about people. When an organization uses a third party translation or generation tool, the use is minimal risk for the organization: the Article 50(2) duty to mark generated text in a machine readable way falls on the provider of that system, and beyond AI literacy no specific deployer obligations apply. When an organization builds and operates its own generating system and puts it into service under its own name, it is the provider and must mark the output, unless the exception for systems that only assist standard editing or do not substantially alter the input or its semantics applies. A faithful translation may fall within that exception; transcreation that rewrites the message for a market alters the semantics and is less likely to. Article 50(4) covers deepfakes and text published to inform the public on matters of public interest, not marketing translations. Consumer protection and advertising rules apply to the translated text as to the original.",[135,136],"eu-ai-act","gdpr",[138,144],{"title":139,"issuer":140,"region":141,"url":142,"note":143},"Spam policies for Google web search, scaled content abuse","Google Search Central","global","https://developers.google.com/search/docs/essentials/spam-policies","Lists scraping feeds, search results or other content to generate many pages, including through automated transformations such as translating, as an example of scaled content abuse when little value is provided to users.",{"title":145,"issuer":146,"region":147,"url":148,"note":149},"Regulation (EU) 2024/1689 (AI Act), Article 50 on transparency obligations","European Union","europe","https://eur-lex.europa.eu/eli/reg/2024/1689/oj","Sets out who must mark or disclose AI generated content, including the provider duty to mark generated text and its exception for systems that do not substantially alter the input or its semantics.",[151,152,153,154],"A tiering policy that sets the review level for each content type and market","Versioned glossaries and style guides with a named owner per market","Records of which content was machine translated, which model and who reviewed it","Personal data removed or masked before customer content is sent for translation",[],{"howToBuild":157},"On Blits.ai this is an **agentic workflow** triggered on a schedule or from the content system\nthrough an API token: an **AI agent** translates and adapts each item using a\n**knowledge base** that holds the glossary, style guides and past approved translations\n(retrieved with **hybrid retrieval**), and returns the result with **structured output** per\nsegment. **Custom functions** read from and write back to the content management or ecommerce\nsystem through REST.\n\n**Human in the loop** confirmation makes a linguist or local marketer approve or reject the write\nback of higher tier content before it is published,\n**guardrails** check terminology and block unapproved claims, and **PII masking** at the gateway\nremoves personal data before text reaches a model. **Test suites** with LLM based grading score\noutput against approved reference translations per language, including Arabic with regional\nmodels, and the platform is model agnostic, so each language can use the model that scores best.",[159,162,165],{"question":160,"answer":161},"Can AI replace translators for marketing content?","Not for the content that carries the brand or legal weight, which people should still review. Lionbridge, a localization provider, uses AI to flag sensitive content for human review before delivery and reports up to 30% shorter turnaround times. Google Cloud reports that Swarovski's campaign localization became 10 times faster with AI assisted translation and asset adaptation.",{"question":163,"answer":164},"What is the difference between machine translation and AI localization?","Classic machine translation converts sentences one by one. Localization with large language models can also apply a glossary and style guide, adapt tone, idioms and units for the market, and flag its own uncertain passages for a reviewer.",{"question":166,"answer":167},"Does machine translated content hurt search rankings?","Google's spam policies give scraping content to generate many pages, including through automated translation, as an example of scaled content abuse when the pages provide little value to users. Translation as such is not the target: localized pages that people in the market actually need, reviewed for quality, fall outside that example.",[169,170,171],"public-service-translation","marketing-content-compliance-copilot","product-content-and-catalog-enrichment","2026-09-27",[174],{"date":172,"note":175},"First published","marketing-and-product-content-localization",[178,219,238],{"title":179,"useCases":180,"organization":182,"vendors":186,"summary":190,"stage":191,"year":192,"channels":193,"languages":194,"metrics":195,"outcomeDisclosed":210,"sources":211,"verification":214,"grade":216,"id":217,"organizationSlug":218},"Swarovski: Génie generative AI portal speeds up campaign localization",[176,181],"personalized-marketing-at-scale",{"name":183,"anonymized":184,"country":185,"region":147,"industry":20},"Swarovski",false,"AT",[187],{"name":188,"role":189},"Google Cloud","platform","Swarovski, which sells in more than 140 markets, launched Génie in 2023, a generative AI portal on Vertex AI and Gemini, on top of a BigQuery data foundation consolidated with the partner CloudSufi. More than 1,000 employees use it for tasks including content translation into over 20 languages, creative asset generation and testing visuals and descriptions for different regions. Google Cloud reports that campaign localization became 10 times faster through AI assisted translation and asset adaptation, and that Génie's AI personalized email campaigns see 17% higher open rates and 7% higher click through rates. Every AI application is evaluated against an internal ethics and risk model.","production",2025,[29],[],[196,204],{"kpi":43,"value":197,"unit":198,"qualifier":199,"period":200,"claimant":201,"quote":202,"sourceUrl":203},10,"multiplier","exact","speed of campaign localization","vendor","Campaign localization is 10x faster, thanks to AI-assisted translation and asset adaptation","https://cloud.google.com/customers/swarovski",{"kpi":45,"value":205,"unit":206,"qualifier":207,"period":208,"claimant":201,"quote":209,"sourceUrl":203},1000,"count","at-least","employees using the Génie portal","Over 1,000 employees now utilize Génie for tasks such as contract review, content translation into over 20 languages, creative digital asset generation, and campaign inspirations, and product design cost estimation.",true,[212],{"url":203,"title":213,"publisher":188},"Letting data shine bright: How Swarovski personalizes luxury with Google Cloud",{"level":215,"checkedAt":172},"source-verified","C","swarovski-genie-campaign-localization",null,{"title":220,"useCases":221,"organization":222,"vendors":224,"summary":226,"stage":191,"year":227,"channels":228,"languages":229,"metrics":230,"outcomeDisclosed":184,"sources":231,"verification":236,"grade":216,"id":237,"organizationSlug":218},"Bosch Digital: Gemini models for localizing marketing content across business units",[176],{"name":223,"anonymized":184,"region":147,"industry":22},"Bosch Digital",[225],{"name":188,"role":189},"Google Cloud lists Bosch Digital, which it describes as one of Europe's leading technology and services companies, as using Gemini models to localize marketing content for different markets and demographics, with many business units having started. The entry mentions time and cost savings but gives no figures.",2024,[29],[],[],[232],{"url":233,"title":234,"publisher":188,"archivedUrl":235},"https://cloud.google.com/transform/101-real-world-generative-ai-use-cases-from-industry-leaders","Real-world gen AI use cases from the world's leading organizations","https://web.archive.org/web/20250104231021/https://cloud.google.com/transform/101-real-world-generative-ai-use-cases-from-industry-leaders",{"level":215,"checkedAt":172},"bosch-gemini-marketing-localization",{"title":239,"useCases":240,"organization":241,"vendors":244,"summary":247,"stage":248,"year":227,"channels":249,"languages":250,"metrics":251,"outcomeDisclosed":210,"sources":264,"verification":268,"grade":216,"id":269,"organizationSlug":218},"Lionbridge: GPT-4 on Azure OpenAI in translation and localization workflows",[176],{"name":242,"anonymized":184,"country":243,"region":141,"industry":21},"Lionbridge","US",[245],{"name":246,"role":189},"Microsoft","Lionbridge, a translation and localization provider with more than 6,500 employees, began building generative AI into its workflows with GPT-4 on Azure OpenAI in 2023, alongside its long standing use of machine translation. Employees use it to translate and localize content, build project glossaries and style guides, and flag sensitive content for human review before delivery. Within nine months the new workflows served hundreds of customers, and the company reports turnaround times up to 30% shorter.","scaled",[29,30],[],[252,260],{"kpi":43,"value":253,"unit":254,"qualifier":255,"period":256,"claimant":257,"quote":258,"sourceUrl":259},30,"percent","up-to","project turnaround time","organization","We’ve reduced turnaround times by up to 30% and cut days or hours off delivery.","https://www.microsoft.com/en/customers/story/1792260322207475324-lionbridge-technologies-azure-openai-service-other-en-united-states",{"kpi":45,"value":261,"unit":206,"qualifier":207,"period":262,"claimant":257,"quote":263,"sourceUrl":259},500,"client organizations using AI for content optimization, not only localization","We already have more than 500 customers using AI to help with content optimization, and we’re getting that content to market with high efficiency and quality",[265],{"url":259,"title":266,"publisher":246,"date":267},"Lionbridge disrupts localization industry using Azure OpenAI Service and reduces turnaround times by up to 30%","2024-07-18",{"level":215,"checkedAt":172},"lionbridge-azure-openai-localization",0,[272,281,286],{"kpi":45,"label":273,"unit":206,"aggregate":184,"higherIsBetter":210,"n":274,"nUpTo":270,"median":275,"min":261,"max":205,"byClaimant":276,"vendorOnly":184,"points":278},"Users served",2,750,{"organization":277,"vendor":277,"regulator":270,"independent":270},1,[279,280],{"evidenceId":217,"organization":183,"value":205,"qualifier":207,"claimant":201,"grade":216,"pooled":210},{"evidenceId":269,"organization":242,"value":261,"qualifier":207,"claimant":257,"grade":216,"pooled":210},{"kpi":43,"label":282,"unit":198,"aggregate":210,"higherIsBetter":210,"n":277,"nUpTo":270,"median":197,"min":197,"max":197,"byClaimant":283,"vendorOnly":210,"points":284},"Cycle time reduction",{"organization":270,"vendor":277,"regulator":270,"independent":270},[285],{"evidenceId":217,"organization":183,"value":197,"qualifier":199,"claimant":201,"grade":216,"pooled":210},{"kpi":43,"label":282,"unit":254,"aggregate":210,"higherIsBetter":210,"n":270,"nUpTo":277,"median":218,"min":218,"max":218,"byClaimant":287,"vendorOnly":184,"points":288},{"organization":270,"vendor":270,"regulator":270,"independent":270},[289],{"evidenceId":269,"organization":242,"value":253,"qualifier":255,"claimant":257,"grade":216,"pooled":184},{"low":291,"high":292},45000,180000,[294,322,348,368],{"slug":169,"title":295,"shortTitle":296,"definition":297,"status":9,"industries":298,"functions":300,"patterns":304,"audience":308,"autonomy":309,"adoptionStage":33,"evidenceCount":310,"publicEvidenceCount":310,"organizations":311,"bestGrade":320,"headline":218,"lastVerified":321,"indexable":210},"AI translation and interpretation for multilingual public services","Public service translation","AI that translates government content, documents and conversations between officials and the public, in writing and in real time speech, so people can use public services in their own language, with human translators and interpreters reviewing what carries legal or safety weight.",[299],"government",[301,302,303],"citizen-services","customer-service","operations",[26,305,306,307],"conversational-agent","speech-analytics","document-processing","customer-facing","copilot",8,[312,313,314,315,316,317,318,319],"Baltimore City 911 (Emergency Communications)","Delaware County","European Commission","Federal Emergency Management Agency","Internal Revenue Service","Madrid Destino","Montgomery County Government","U.S. Department of State (Bureau of Consular Affairs)","B","2026-09-26",{"slug":170,"title":323,"shortTitle":324,"definition":325,"status":9,"industries":326,"functions":332,"patterns":335,"audience":31,"autonomy":309,"adoptionStage":33,"evidenceCount":338,"publicEvidenceCount":339,"organizations":340,"bestGrade":320,"headline":344,"lastVerified":172,"indexable":210},"AI copilot for marketing content with compliance pre review","Marketing content and compliance","A copilot that drafts campaign copy, product explainers and social posts on brand and in the customer's language from approved product facts, then runs a first pass compliance check against advertising rules and required disclosures, flagging unsupported claims and missing warnings before a human in marketing compliance approves publication.",[19,327,328,329,330,331],"banking","insurance","payments","wealth-and-asset-management","pharma-and-life-sciences",[24,333,334],"regulatory-compliance","legal",[27,336,337,26],"rag-knowledge-assistant","classification-and-routing",5,3,[341,342,343],"Ally Financial","JPMorgan Chase","Klarna",{"kpi":44,"label":345,"unit":254,"n":277,"nUpTo":270,"kind":346,"value":347,"qualifier":199,"claimant":257,"organization":341,"vendorReported":184},"Productivity gain","reported",34,{"slug":171,"title":349,"shortTitle":350,"definition":351,"status":9,"industries":352,"functions":353,"patterns":354,"audience":356,"autonomy":32,"adoptionStage":357,"evidenceCount":358,"publicEvidenceCount":358,"organizations":359,"bestGrade":320,"headline":364,"lastVerified":172,"indexable":210},"AI product content and catalog enrichment for online retail","Product content and catalog enrichment","AI that writes and repairs product content at catalog scale: it drafts titles, descriptions and image alt text, and extracts missing attributes such as color, size and material from supplier text and product images, then 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.",[20,19],[24,303],[27,355,337],"computer-vision","back-office","mainstream",4,[360,361,362,363],"Amazon","eBay","Etsy","Walmart",{"kpi":365,"label":366,"unit":254,"n":277,"nUpTo":270,"kind":346,"value":367,"qualifier":199,"claimant":257,"organization":360,"vendorReported":184},"quality-score-uplift","Quality score uplift",40,{"slug":369,"title":370,"shortTitle":371,"definition":372,"status":9,"industries":373,"functions":375,"patterns":377,"audience":31,"autonomy":309,"adoptionStage":33,"evidenceCount":381,"publicEvidenceCount":382,"organizations":383,"bestGrade":216,"headline":218,"lastVerified":172,"indexable":210},"outbound-sales-prospecting-agent","AI agent for outbound sales prospecting and personalized outreach","Outbound sales prospecting","An AI agent that researches target accounts and contacts, drafts personalized outbound outreach (emails, LinkedIn messages and call scripts) from the campaign, the prospect's context and the sales goals, and sequences the follow ups, with a sales development rep approving or sending every message.",[19,374,21],"technology",[376,24],"sales",[27,378,379,380],"agentic-workflow","recommendation-and-personalization","prediction-and-scoring",9,7,[384,385,386,387,388,389,390],"A-LIGN","ANS","Dun & Bradstreet","Lumen Technologies","Merge","Oyster","Unifonic",{"indexable":210,"reasons":392},[],[394,398,403,410,418,424,431,438,446,453,460,466,473,480,486,491,498,504,510,516,522,528,533,538,543,549,555,560,566,573,579,585,591,596],{"id":135,"label":395,"issuer":146,"region":147,"url":148,"description":396,"useCases":397,"indexable":210},"EU AI Act","Regulation (EU) 2024/1689: risk based rules for AI systems, with obligations for high risk systems listed in Annex III and transparency duties under Article 50.",197,{"id":136,"label":399,"issuer":146,"region":147,"url":400,"description":401,"useCases":402,"indexable":210},"GDPR","https://eur-lex.europa.eu/eli/reg/2016/679/oj","General Data Protection Regulation, including Article 22 on decisions based solely on automated processing.",180,{"id":404,"label":405,"issuer":406,"region":141,"url":407,"description":408,"useCases":409,"indexable":210},"iso-42001","ISO/IEC 42001","ISO and IEC","https://www.iso.org/standard/81230.html","The international management system standard for AI.",110,{"id":411,"label":412,"issuer":413,"region":414,"url":415,"description":416,"useCases":417,"indexable":210},"nist-ai-rmf","NIST AI Risk Management Framework","NIST","north-america","https://www.nist.gov/itl/ai-risk-management-framework","Voluntary US framework to map, measure, manage and govern AI risk, with a generative AI profile.",83,{"id":419,"label":420,"issuer":146,"region":147,"url":421,"description":422,"useCases":423,"indexable":210},"dora","DORA","https://eur-lex.europa.eu/eli/reg/2022/2554/oj","Digital Operational Resilience Act for financial entities: ICT risk, incident reporting and third party risk, including AI providers.",66,{"id":425,"label":426,"issuer":427,"region":147,"url":428,"description":429,"useCases":430,"indexable":210},"uk-gdpr","UK GDPR","Information Commissioner's Office","https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/","The UK's version of the GDPR, including rules on solely automated decisions.",64,{"id":432,"label":433,"issuer":434,"region":147,"url":435,"description":436,"useCases":437,"indexable":210},"uk-consumer-duty","FCA Consumer Duty","Financial Conduct Authority","https://www.fca.org.uk/firms/consumer-duty","UK rules that require firms to deliver good outcomes for retail customers, including through automated channels.",47,{"id":439,"label":440,"issuer":441,"region":442,"url":443,"description":444,"useCases":445,"indexable":210},"mas-ai-risk-management","MAS AI risk management guidelines","Monetary Authority of Singapore","asia-pacific","https://www.mas.gov.sg/news/media-releases/2025/mas-guidelines-for-artificial-intelligence-risk-management","Singapore's supervisory expectations for AI risk management at financial institutions, building on the FEAT principles.",36,{"id":447,"label":448,"issuer":449,"region":442,"url":450,"description":451,"useCases":452,"indexable":210},"apra-cps-230","APRA CPS 230","Australian Prudential Regulation Authority","https://www.apra.gov.au/operational-risk-management","Australian operational risk standard covering critical operations and material service providers.",25,{"id":454,"label":455,"issuer":456,"region":141,"url":457,"description":458,"useCases":459,"indexable":210},"pci-dss","PCI DSS","PCI Security Standards Council","https://www.pcisecuritystandards.org/","Security standard for any system that stores, processes or transmits cardholder data.",20,{"id":461,"label":462,"issuer":463,"region":414,"url":464,"description":465,"useCases":459,"indexable":210},"us-sr-11-7","SR 11-7 model risk management","Federal Reserve and OCC","https://www.federalreserve.gov/boarddocs/srletters/2011/sr1107.htm","US supervisory guidance on model risk management, applied by banks to AI and machine learning models.",{"id":467,"label":468,"issuer":469,"region":147,"url":470,"description":471,"useCases":472,"indexable":210},"uk-atrs","UK Algorithmic Transparency Recording Standard","UK Government","https://www.gov.uk/government/collections/algorithmic-transparency-recording-standard-hub","Mandatory transparency records for algorithmic tools used by UK central government.",16,{"id":474,"label":475,"issuer":476,"region":141,"url":477,"description":478,"useCases":479,"indexable":210},"fatf-recommendations","FATF Recommendations","Financial Action Task Force","https://www.fatf-gafi.org/en/publications/Fatfrecommendations/Fatf-recommendations.html","Global standards for anti money laundering and counter terrorist financing that national rules implement.",15,{"id":481,"label":482,"issuer":146,"region":147,"url":483,"description":484,"useCases":485,"indexable":210},"eu-amlr","EU Anti Money Laundering Regulation","https://eur-lex.europa.eu/eli/reg/2024/1624/oj","Regulation (EU) 2024/1624: the single EU rulebook for customer due diligence, beneficial ownership and suspicious transaction reporting.",14,{"id":487,"label":488,"issuer":146,"region":147,"url":489,"description":490,"useCases":485,"indexable":210},"nis2","NIS2 Directive","https://eur-lex.europa.eu/eli/dir/2022/2555/oj","Directive (EU) 2022/2555 on cybersecurity for essential and important entities, including telecom networks, energy and public administration.",{"id":492,"label":493,"issuer":494,"region":414,"url":495,"description":496,"useCases":497,"indexable":210},"us-bsa","Bank Secrecy Act","FinCEN","https://www.fincen.gov/resources/statutes-and-regulations/bank-secrecy-act","US anti money laundering law: customer due diligence, suspicious activity reports and record keeping.",13,{"id":499,"label":500,"issuer":146,"region":147,"url":501,"description":502,"useCases":503,"indexable":210},"eu-accessibility-act","European Accessibility Act","https://eur-lex.europa.eu/eli/dir/2019/882/oj","Directive (EU) 2019/882: accessibility requirements for banking services, ecommerce and other digital services, applicable since June 2025.",12,{"id":505,"label":506,"issuer":507,"region":414,"url":508,"description":509,"useCases":503,"indexable":210},"hipaa","HIPAA","US Department of Health and Human Services","https://www.hhs.gov/hipaa/index.html","US rules for the privacy and security of protected health information.",{"id":511,"label":512,"issuer":513,"region":141,"url":514,"description":515,"useCases":503,"indexable":210},"telecom-consumer-rules","Telecom consumer protection rules","National telecom regulators","https://www.berec.europa.eu/","National rules on telecom contracts, switching, billing disputes and marketing consent.",{"id":517,"label":518,"issuer":146,"region":147,"url":519,"description":520,"useCases":521,"indexable":210},"eecc","European Electronic Communications Code","https://eur-lex.europa.eu/eli/dir/2018/1972/oj","Directive (EU) 2018/1972: consumer protection, contract, switching and security rules for telecom operators.",11,{"id":523,"label":524,"issuer":525,"region":414,"url":526,"description":527,"useCases":521,"indexable":210},"us-tcpa","Telephone Consumer Protection Act","Federal Communications Commission","https://www.fcc.gov/consumers/guides/stop-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":529,"label":530,"issuer":441,"region":442,"url":531,"description":532,"useCases":197,"indexable":210},"mas-notice-626","MAS Notice 626","https://www.mas.gov.sg/regulation/notices/notice-626","Singapore's anti money laundering and counter terrorism financing requirements for banks.",{"id":534,"label":535,"issuer":146,"region":147,"url":536,"description":537,"useCases":197,"indexable":210},"mifid-ii","MiFID II","https://eur-lex.europa.eu/eli/dir/2014/65/oj","Directive 2014/65/EU on markets in financial instruments: suitability and appropriateness of advice, record keeping and product governance.",{"id":539,"label":540,"issuer":146,"region":147,"url":541,"description":542,"useCases":197,"indexable":210},"eu-psd2","PSD2","https://eur-lex.europa.eu/eli/dir/2015/2366/oj","Payment Services Directive 2: strong customer authentication, transaction risk analysis exemptions and open banking access.",{"id":544,"label":545,"issuer":546,"region":147,"url":547,"description":548,"useCases":381,"indexable":210},"eba-loan-origination","EBA Guidelines on loan origination and monitoring","European Banking Authority","https://www.eba.europa.eu/regulation-and-policy/credit-risk/guidelines-on-loan-origination-and-monitoring","Expectations for credit decisioning, including the use of automated models.",{"id":550,"label":551,"issuer":552,"region":414,"url":553,"description":554,"useCases":310,"indexable":210},"us-ecoa-reg-b","ECOA and Regulation B","Consumer Financial Protection Bureau","https://www.consumerfinance.gov/rules-policy/regulations/1002/9/","US fair lending rules, including specific reasons in adverse action notices, which also apply when credit decisions use AI models.",{"id":556,"label":557,"issuer":146,"region":147,"url":558,"description":559,"useCases":310,"indexable":210},"solvency-ii","Solvency II","https://eur-lex.europa.eu/eli/dir/2009/138/oj","Directive 2009/138/EC: risk based capital, governance and model requirements for insurers.",{"id":561,"label":562,"issuer":146,"region":147,"url":563,"description":564,"useCases":565,"indexable":210},"eu-idd","Insurance Distribution Directive","https://eur-lex.europa.eu/eli/dir/2016/97/oj","Directive (EU) 2016/97: conduct rules for selling insurance, including demands and needs testing and advice.",6,{"id":567,"label":568,"issuer":569,"region":570,"url":571,"description":572,"useCases":338,"indexable":210},"cbuae-ai-guidance","CBUAE guidance on AI and ML","Central Bank of the UAE","middle-east","https://www.centralbank.ae/","UAE central bank expectations for the enabling technologies, AI and machine learning used by licensed financial institutions.",{"id":574,"label":575,"issuer":576,"region":147,"url":577,"description":578,"useCases":358,"indexable":210},"pra-ss1-23","PRA SS1/23 model risk management","Prudential Regulation Authority","https://www.bankofengland.co.uk/prudential-regulation/publication/2023/may/model-risk-management-principles-for-banks-ss","UK model risk management principles for banks, covering AI and machine learning models.",{"id":580,"label":581,"issuer":582,"region":147,"url":583,"description":584,"useCases":358,"indexable":210},"uk-psr-app-reimbursement","UK APP scam reimbursement rules","Payment Systems Regulator","https://www.psr.org.uk/our-work/app-scams/","Mandatory reimbursement of authorised push payment scam victims by UK payment firms, which shifts scam losses onto banks.",{"id":586,"label":587,"issuer":588,"region":442,"url":589,"description":590,"useCases":339,"indexable":210},"au-scams-prevention-framework","Australian Scams Prevention Framework","Australian Treasury","https://treasury.gov.au/consultation/c2024-573813","Economy wide obligations for banks, telcos and digital platforms to prevent, detect, disrupt and respond to scams.",{"id":592,"label":593,"issuer":146,"region":147,"url":594,"description":595,"useCases":339,"indexable":210},"eu-mar","EU Market Abuse Regulation","https://eur-lex.europa.eu/eli/reg/2014/596/oj","Regulation (EU) 596/2014: insider dealing and market manipulation, including the duty to detect and report suspicious orders and transactions.",{"id":597,"label":598,"issuer":599,"region":414,"url":600,"description":601,"useCases":339,"indexable":210},"us-fcra","Fair Credit Reporting Act","Federal Trade Commission","https://www.ftc.gov/legal-library/browse/statutes/fair-credit-reporting-act","US rules on consumer reports, their accuracy and permissible use, relevant to credit scoring and screening.",1790598302596]