[{"data":1,"prerenderedAt":556},["ShallowReactive",2],{"uc-legislative-drafting-and-parliamentary-question-support":3,"uc-regulations":335},{"useCase":4,"evidence":181,"blitsAiDeployments":247,"benchmarks":248,"indicative":255,"related":258,"indexability":333,"includeUnpublished":187},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":16,"functions":18,"patterns":21,"channels":25,"audience":27,"autonomy":28,"adoptionStage":29,"problem":30,"problemStats":31,"howItWorks":37,"valueDrivers":38,"kpis":41,"indicativeValue":46,"macroEstimates":85,"feasibility":86,"implementation":97,"risk":132,"blitsAi":160,"faq":162,"related":172,"datePublished":176,"dateModified":176,"lastVerified":176,"changelog":177,"slug":180},"AI for legislative drafting and parliamentary question support","Legislative drafting and parliamentary support","AI for parliamentary research and bill notes","UK civil servants use Parlex to search parliament's public record, and New Zealand tested an AI proof of concept for bill explanatory notes.","published","An AI tool that helps legislative counsel, policy officials and ministers' private offices search, summarise and draft the material behind new laws and government responses to parliamentarians, from finding the relevant debates and prior questions to producing a first draft of an explanatory note or a briefing, with the legal drafter or policy official responsible for the final text.",[12,13,14,15],"parliamentary question answering AI","legislative drafting assistant","bill drafting AI","parliamentary intelligence tool",[17],"government",[19,20],"legal","knowledge-management",[22,23,24],"rag-knowledge-assistant","content-generation","summarization",[26],"internal-tools","employee-facing","copilot","emerging","Governments answer a large volume of parliamentary business: written and oral questions, debates,\nconsultations and the bills themselves. Before anyone can answer a question well or draft an\nexplanatory note, someone has to find what has already been said on the topic, by whom, and in what\ncontext, inside years of proceedings that are public but not easy to search by meaning rather than\nkeyword. Legislative counsel then has to turn policy intent into a clause, and produce the supporting\nexplanatory material that lets legislators and the public understand what it does.\n\nIn the United States, Warren Burke, who leads the House Office of the Legislative Counsel, testified\nthat requests for legislation the office received were up 72% in 2025 compared with two years\nearlier. An anonymous congressional staffer, quoted in the same reporting, said outside groups are\nincreasingly \"going to Claude or ChatGPT to draft the legislative language itself\", so the office\nspends more time fixing that language than it would take to draft it from scratch. The two tools on\nthis page take a different approach: a government owns and governs the AI tool built for its own\nlegislative and parliamentary work, whether built in house or with a partner, with a legal drafter or\npolicy official still responsible for what is filed or said.",[32],{"statement":33,"sourceTitle":34,"sourceUrl":35,"year":36},"Warren Burke, who leads the US House Office of the Legislative Counsel, testified that requests for legislation the office received were up 72% in 2025 compared with two years earlier.","'It's Absolutely Terrifying': AI Is Reportedly Slopping Up the Bills in Congress","https://gizmodo.com/its-absolutely-terrifying-ai-is-reportedly-slopping-up-the-bills-in-congress-2000799734",2026,"1. **Index the public record.** The tool ingests the legislature's own data, such as debates,\n   written questions and answers, and legislation, usually through an official parliamentary API,\n   and keeps it current with a daily update.\n2. **Search by meaning.** A policy official describes what they need in their own words; the tool\n   embeds the query and ranks debates, questions and answers by relevance rather than exact keyword\n   matches.\n3. **Summarise with citations.** A language model turns the matching results into a short, cited\n   summary, with every claim linked back to the original record so the user can check it directly.\n4. **Draft a first version.** For a narrower task, such as an explanatory note for a Bill clause, the\n   tool is given the Bill text and the Act it amends, and generates a draft summary of the clause's\n   effect for a drafter to open and rework.\n5. **A named official finishes the work.** The drafter or policy official edits, corrects and takes\n   ownership of the final text; nothing the tool produces is filed or sent to a parliamentarian\n   without that review.",[39,40],"employee-productivity","speed",[42,43,44,45],"productivity-gain","search-time-reduction","time-saved-per-task","users-served",{"referenceOrg":47,"inputs":48,"formula":80,"currency":81,"period":82,"resultLabel":83,"caveat":84},"A government department with 40 policy and legislative staff handling parliamentary business",[49,54,61,68,74],{"key":50,"label":51,"low":52,"high":52,"unit":50,"note":53},"staff","Policy and legislative staff answering parliamentary business",40,"The reference department.",{"key":55,"label":56,"low":57,"high":58,"unit":59,"note":60},"hoursPerWeek","Hours per staff member per week spent on parliamentary research and drafting",5,10,"hours per staff member per week","Editorial assumption for a policy team handling correspondence, debate preparation and explanatory notes. Replace with your own time study.",{"key":62,"label":63,"low":64,"high":65,"unit":66,"note":67},"timeSavedShare","Share of that research and drafting time saved",0.15,0.35,"fraction of research and drafting time","Conservative against the evidence on this page, because the UK government describes Parlex only as reducing research time and New Zealand's Parliamentary Counsel Office has not published a percentage or decided whether the results warrant further investment. Replace with your own measurement once you pilot.",{"key":69,"label":70,"low":71,"high":71,"unit":72,"note":73},"weeksPerYear","Working weeks per year",44,"weeks","Standard allowance for leave and public holidays.",{"key":75,"label":76,"low":52,"high":77,"unit":78,"note":79},"costPerHour","Fully loaded cost per policy or legislative staff hour",70,"USD per hour","Editorial assumption for a civil service policy grade. Replace with your own cost.","staff * hoursPerWeek * timeSavedShare * weeksPerYear * costPerHour","USD","per year","Policy and legislative staff time cost avoided","Gross time value only. It leaves out the cost of running and governing the tool, the review every draft still needs from a named official, and any change in the volume or complexity of parliamentary business the department handles.",[],{"complexity":87,"complexityNote":88,"dataPrerequisites":89,"integrations":93},"medium","Search and summarisation over public parliamentary data is the straightforward part. The harder work is connecting a private departmental knowledge base for briefings without exposing information the tool's users are not authorised to see, and building drafting features that follow the specific legal conventions and citation rules the legislature already uses.",[90,91,92],"Full text of the legislature's proceedings, questions and answers, and legislation, ideally through an official parliamentary data API","The Bill text and the Act it amends, structured by clause, for any drafting feature","A style guide or drafting manual for explanatory notes, briefings or correspondence",[94,95,96],"Parliamentary or legislature data API for debates, questions and legislation","The department's own document and knowledge management system for prior briefings","Legislative drafting or bill management software used by legal drafters",{"steps":98,"guardrails":114,"humanInTheLoop":119,"kpisToInstrument":120,"failureModes":125},[99,102,105,108,111],{"title":100,"detail":101},"Start with search, not drafting","Launch with semantic search and cited summarisation over public parliamentary and legislative records before adding any generation of new legal text, because a poor search result is easy to spot and a drafting error is not.",{"title":103,"detail":104},"Keep every output a working note","Treat every AI output as a draft for a named person to rework, the way New Zealand's own proof of concept let drafters regenerate and compare several explanatory note drafts before choosing what to keep, rather than a text anyone can file directly.",{"title":106,"detail":107},"Ground every summary with a citation","Link every generated summary back to the original debate, question or clause it is based on, so a policy official can check it in seconds instead of trusting it on faith.",{"title":109,"detail":110},"Pilot with a small, named group first","Register a limited, named group of users, as the UK government did with about 400 pilot Civil Service users spread across departments and roles, and collect structured feedback before widening access to the rest of the organisation.",{"title":112,"detail":113},"Decide the quality bar before you pick a model size","New Zealand's Parliamentary Counsel Office found that larger models tended to give more fit for purpose drafts than smaller ones, but cost more and made errors that were harder to spot. Decide how good a draft you need before you choose a model size, rather than defaulting to the biggest one available.",[115,116,117,118],"AI generated text is visibly marked wherever it appears, separate from the original record","No draft leaves the tool as a final answer; a named official signs off before it is used","The tool states plainly that it is a research starting point, not a definitive source","Access is restricted by security clearance and department, matching the sensitivity of the data","A policy official or legislative drafter reviews, edits and takes ownership of every summary or draft before it appears in a briefing, a Bill or an answer to a parliamentarian. The tool never submits or publishes anything on its own behalf.",[121,122,123,124],"Time from a request to a usable first draft or summary","Share of registered users who return weekly","Editing distance between the AI draft and the final approved text","User reported trust and accuracy from structured feedback",[126,129],{"title":127,"detail":128},"A summary that misses the political context","The UK government's own transparency record for Parlex warns that the tool \"may not capture nuances in debate, such as tone and broader political context\" that a human researcher would catch. Keep a human judgment step before anything reaches a minister or the public record.",{"title":130,"detail":131},"Confident search results that are not actually relevant","Semantic search can rank a loosely related debate above the one that matters most. Show the relevance ranking and the original text alongside the AI summary, not the summary alone.",{"euAiAct":133,"regulations":136,"guidance":142,"controls":154,"incidents":159},{"tier":134,"basis":135},"minimal","A research and drafting aid that a policy official or legal drafter reviews before use is not listed in Annex III. Article 50(4) exempts AI generated text that has undergone human review and carries a named person's editorial responsibility from the disclosure duty that otherwise applies to AI generated content published on matters of public interest, which is how both tools on this page are designed to work. If a tool moved from drafting support to deciding the outcome of a request for a public service or benefit, Annex III point 5(a) could apply instead.",[137,138,139,140,141],"eu-ai-act","gdpr","uk-gdpr","uk-atrs","iso-42001",[143,149],{"title":144,"issuer":145,"region":146,"url":147,"note":148},"Algorithmic Transparency Recording Standard hub","UK government","europe","https://www.gov.uk/government/collections/algorithmic-transparency-recording-standard-hub","UK departments publish transparency records for tools such as Parlex, including their phase, registered user numbers and underlying model.",{"title":150,"issuer":151,"region":146,"url":152,"note":153},"DSIT - Parlex (algorithmic transparency record)","Department for Science, Innovation and Technology","https://www.gov.uk/algorithmic-transparency-records/dsit-parlex","States that Parlex does not function in a decision making capacity and that users must verify and validate its outputs before relying on them.",[155,156,157,158],"AI generated content visibly marked wherever it is shown","Named official reviews and approves every draft or briefing before use","Access limited by security clearance and need to know","Source citations kept attached to every generated summary",[],{"howToBuild":161},"On Blits.ai this is a knowledge base built over the legislature's public data (debates, questions\nand answers, bill text) with hybrid retrieval, paired with an agent that turns a policy question\ninto a grounded, cited summary. A second, narrower agent, built as a flow with a fixed set of steps,\nhandles a drafting task such as a first version of an explanatory note: it takes the clause and the\ntext it amends as input and returns a structured draft, ready for a drafter to open and edit.\n\nThe service runs as an internal tool behind the department's own authentication, with guardrails\nthat check output against the approved sources and an agentic workflow with human in the loop\napproval, so nothing the agent produces is final until a named official approves it. Per agent\nusage metrics and response feedback show how the service is used, and a test suite checks its\nanswers stay grounded before a department expands access. EU and UAE data residency options keep\nthe underlying documents inside one of those regions, and the platform's model agnostic routing\nlets a department change the underlying model without rebuilding the workflow around it.",[163,166,169],{"question":164,"answer":165},"Does a tool like Parlex write the answer to a parliamentary question?","No. The UK government's own transparency record for Parlex says the tool does not function in a decision making capacity and that users must verify and validate its findings. It retrieves and summarises public parliamentary information; the civil servant still writes and takes responsibility for the answer.",{"question":167,"answer":168},"Has any government measured how much time this saves?","Not yet with a published figure. The UK government's Parlex had about 400 registered pilot users according to its own transparency record, and New Zealand's Parliamentary Counsel Office reported that its proof of concept produced first drafts a drafter could refine, but neither has published a percentage or an hours figure. Parlex is in pilot; New Zealand's work is an internal research and development proof of concept, not yet a pilot with live users.",{"question":170,"answer":171},"Can AI draft an actual bill?","Not on its own, and neither example here tries to. New Zealand's Parliamentary Counsel Office scoped its trial to the explanatory notes that accompany an amendment Bill, not the legal text of the Bill itself, and its own report says the office has yet to determine whether the results are good enough to warrant further investment.",[173,174,175],"civil-servant-drafting-copilot","policy-drafting-and-gap-analysis","regulatory-horizon-scanning","2026-09-29",[178],{"date":176,"note":179},"First published","legislative-drafting-and-parliamentary-question-support",[182,222],{"title":183,"useCases":184,"organization":185,"vendors":189,"summary":193,"stage":194,"year":195,"channels":196,"languages":197,"metrics":199,"outcomeDisclosed":207,"sources":208,"verification":217,"grade":219,"id":220,"organizationSlug":221},"UK government i.AI: Parlex parliamentary intelligence search tool",[180],{"name":186,"anonymized":187,"country":188,"region":146,"industry":17},"Department for Science, Innovation and Technology (Incubator for Artificial Intelligence)",false,"GB",[190],{"name":191,"role":192},"Incubator for Artificial Intelligence (i.AI)","in-house","Parlex is a semantic search and generative summary tool built by the UK government's Incubator for Artificial Intelligence for parliamentary data: Hansard debates, member profiles and written parliamentary questions. It lets policy teams, private offices and bill teams search this archive by meaning rather than keyword, and generate a cited summary of what it finds. The tool does not decide or draft an answer to a parliamentary question itself; it is a research aid that users must verify against the original record. It is one of the tools in the government's \"Humphrey\" AI package for civil servants, launched in January 2025, and is in beta.","pilot",2025,[26],[198],"en",[200],{"kpi":45,"value":201,"unit":202,"qualifier":203,"period":204,"claimant":205,"quote":206,"sourceUrl":152},400,"count","approximately","at the time of the transparency record","organization","It has ~400 registered pilot Civil Service users across a variety of government departments and roles.",true,[209,212],{"url":152,"title":210,"publisher":211},"DSIT - Parlex - GOV.UK","GOV.UK",{"url":213,"title":214,"publisher":215,"date":216},"https://www.globalgovernmentforum.com/yes-civil-servant-meet-humphrey-the-governments-ai-package-for-officials/","Yes, civil servant: Meet Humphrey, the UK government's AI package for officials","Global Government Forum","2025-01-23",{"level":218,"checkedAt":176},"source-verified","B","dsit-parlex-parliamentary-search","department-for-science-innovation-and-technology-incubator-for-artificial-intelligence",{"title":223,"useCases":224,"organization":225,"vendors":229,"summary":233,"stage":234,"year":195,"channels":235,"languages":236,"metrics":237,"outcomeDisclosed":187,"sources":238,"verification":244,"grade":219,"id":245,"organizationSlug":246},"New Zealand Parliamentary Counsel Office: AI proof of concept for drafting explanatory notes",[180],{"name":226,"anonymized":187,"country":227,"region":228,"industry":17},"Parliamentary Counsel Office (New Zealand)","NZ","asia-pacific",[230],{"name":231,"role":232},"Catalyst IT","integrator","New Zealand's Parliamentary Counsel Office ran a six month research and development programme with five companies to test where AI could help its work. One stream, a proof of concept built with Catalyst, explored whether a large language model could generate a useful first draft of the clause by clause explanatory note that accompanies an amendment Bill, given the Bill text and the principal Act it changes. The team tested several model sizes, hosted where possible in New Zealand for data and security control, and published a report and open source code. The office describes the result as a proof of concept only, says it can \"now begin a formal evaluation of the tool\", and has not decided whether the results are good enough to warrant further investment.","announced",[26],[198],[],[239],{"url":240,"title":241,"publisher":226,"date":242,"archivedUrl":243},"https://pco.govt.nz/about-us/legislative-data-and-technology/How-successful-is-AI-at-drafting-an-explanatory-note","How successful is AI at drafting an explanatory note?","2025-10-08","https://web.archive.org/web/20260127111742/https://pco.govt.nz/about-us/legislative-data-and-technology/How-successful-is-AI-at-drafting-an-explanatory-note",{"level":218,"checkedAt":176},"nz-pco-explanatory-note-drafting",null,0,[249],{"kpi":45,"label":250,"unit":202,"aggregate":187,"higherIsBetter":207,"n":251,"nUpTo":247,"median":201,"min":201,"max":201,"byClaimant":252,"vendorOnly":187,"points":253},"Users served",1,{"organization":251,"vendor":247,"regulator":247,"independent":247},[254],{"evidenceId":220,"organization":186,"value":201,"qualifier":203,"claimant":205,"grade":219,"pooled":207},{"low":256,"high":257},52800,431200,[259,274,294,314],{"slug":173,"title":260,"shortTitle":261,"definition":262,"status":9,"industries":263,"functions":264,"patterns":267,"audience":27,"autonomy":28,"adoptionStage":29,"evidenceCount":57,"publicEvidenceCount":57,"organizations":268,"bestGrade":219,"headline":246,"lastVerified":273,"indexable":207},"AI drafting copilot for civil servants for correspondence, briefings and ministerial replies","Civil servant drafting copilot","A generative AI assistant that drafts replies to correspondence from the public and elected representatives, briefings, submissions and summaries for civil servants, grounded in the department's approved lines, policy documents and case data, with the official editing and approving every word before it is sent or cleared.",[17],[265,20,266],"citizen-services","case-management",[23,22,24],[269,270,271,186,272],"Cabinet Office (Government Communication Service)","Crown Prosecution Service","Department for Education","Government Digital Service","2026-09-27",{"slug":174,"title":275,"shortTitle":276,"definition":277,"status":9,"industries":278,"functions":283,"patterns":285,"audience":27,"autonomy":28,"adoptionStage":29,"segment":287,"evidenceCount":288,"publicEvidenceCount":288,"organizations":289,"bestGrade":219,"headline":246,"lastVerified":293,"indexable":207},"AI for policy drafting and policy gap analysis","Policy drafting and gaps","An assistant that takes a new or changed obligation, finds every internal policy, standard and procedure it touches, flags clauses that now conflict or are silent, and drafts the updated wording in house style as a redline for the policy owner to approve.",[279,280,281,282,17],"cross-industry","banking","insurance","capital-markets",[284,19,20],"regulatory-compliance",[22,23,286,24],"document-processing","second-line",3,[290,291,292],"Federal Deposit Insurance Corporation","Administration for Children and Families","Health Resources and Services Administration","2026-09-26",{"slug":175,"title":295,"shortTitle":296,"definition":297,"status":9,"industries":298,"functions":302,"patterns":304,"audience":27,"autonomy":307,"adoptionStage":308,"segment":309,"evidenceCount":310,"publicEvidenceCount":311,"organizations":312,"bestGrade":219,"headline":246,"lastVerified":273,"indexable":207},"AI regulatory horizon scanning and obligation mapping","Regulatory horizon scanning","An AI system that continuously reads publications from the regulators and standard setters an organization answers to, classifies each item by relevance and urgency, breaks new rules into individual obligations and maps them to the internal policies and controls that meet them, so compliance owners see what changed and where the gaps are.",[279,280,281,299,300,301,17],"payments","wealth-and-asset-management","pharma-and-life-sciences",[284,19,303],"risk-management",[305,286,22,24,306],"classification-and-routing","agentic-workflow","assist","early-adopters","compliance",4,2,[313,291],"Financial Conduct Authority",{"slug":315,"title":316,"shortTitle":317,"definition":318,"status":9,"industries":319,"functions":321,"patterns":322,"audience":27,"autonomy":28,"adoptionStage":308,"evidenceCount":310,"publicEvidenceCount":310,"organizations":323,"bestGrade":219,"headline":328,"lastVerified":273,"indexable":207},"legal-research-and-drafting-assistant","AI legal research and drafting assistant for lawyers","Legal research and drafting","A generative AI assistant for lawyers in firms, legal departments and public bodies that finds and summarises case law, legislation and internal know how, answers legal questions with citations and drafts first versions of memos, briefings, letters and filings, which a lawyer verifies and signs off.",[320,279,17],"professional-services",[19,20],[22,23,24,286],[324,325,326,327],"A&O Shearman","Ashurst Perkins Coie","U.S. Department of Justice","U.S. Securities and Exchange Commission",{"kpi":42,"label":329,"unit":330,"n":251,"nUpTo":247,"kind":331,"value":332,"qualifier":203,"claimant":205,"organization":325,"vendorReported":187},"Productivity gain","percent","reported",45,{"indexable":207,"reasons":334},[],[336,342,347,354,362,368,374,380,387,394,401,408,414,418,425,432,438,445,451,457,463,470,475,481,486,491,496,502,509,515,522,528,534,540,545,550],{"id":137,"label":337,"issuer":338,"region":146,"url":339,"description":340,"useCases":341,"indexable":207},"EU AI Act","European Union","https://eur-lex.europa.eu/eli/reg/2024/1689/oj","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.",230,{"id":138,"label":343,"issuer":338,"region":146,"url":344,"description":345,"useCases":346,"indexable":207},"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.",207,{"id":141,"label":348,"issuer":349,"region":350,"url":351,"description":352,"useCases":353,"indexable":207},"ISO/IEC 42001","ISO and IEC","global","https://www.iso.org/standard/81230.html","The international management system standard for AI.",122,{"id":355,"label":356,"issuer":357,"region":358,"url":359,"description":360,"useCases":361,"indexable":207},"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.",92,{"id":139,"label":363,"issuer":364,"region":146,"url":365,"description":366,"useCases":367,"indexable":207},"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.",71,{"id":369,"label":370,"issuer":338,"region":146,"url":371,"description":372,"useCases":373,"indexable":207},"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":375,"label":376,"issuer":313,"region":146,"url":377,"description":378,"useCases":379,"indexable":207},"uk-consumer-duty","FCA Consumer Duty","https://www.fca.org.uk/firms/consumer-duty","UK rules that require firms to deliver good outcomes for retail customers, including through automated channels.",50,{"id":381,"label":382,"issuer":383,"region":228,"url":384,"description":385,"useCases":386,"indexable":207},"mas-ai-risk-management","MAS AI risk management guidelines","Monetary Authority of Singapore","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.",37,{"id":388,"label":389,"issuer":390,"region":228,"url":391,"description":392,"useCases":393,"indexable":207},"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":395,"label":396,"issuer":397,"region":358,"url":398,"description":399,"useCases":400,"indexable":207},"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.",22,{"id":402,"label":403,"issuer":404,"region":350,"url":405,"description":406,"useCases":407,"indexable":207},"pci-dss","PCI DSS","PCI Security Standards Council","https://www.pcisecuritystandards.org/","Security standard for any system that stores, processes or transmits cardholder data.",21,{"id":409,"label":410,"issuer":338,"region":146,"url":411,"description":412,"useCases":413,"indexable":207},"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.",17,{"id":140,"label":415,"issuer":416,"region":146,"url":147,"description":417,"useCases":413,"indexable":207},"UK Algorithmic Transparency Recording Standard","UK Government","Mandatory transparency records for algorithmic tools used by UK central government.",{"id":419,"label":420,"issuer":421,"region":358,"url":422,"description":423,"useCases":424,"indexable":207},"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.",16,{"id":426,"label":427,"issuer":428,"region":350,"url":429,"description":430,"useCases":431,"indexable":207},"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":433,"label":434,"issuer":338,"region":146,"url":435,"description":436,"useCases":437,"indexable":207},"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":439,"label":440,"issuer":441,"region":358,"url":442,"description":443,"useCases":444,"indexable":207},"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":446,"label":447,"issuer":448,"region":358,"url":449,"description":450,"useCases":444,"indexable":207},"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":452,"label":453,"issuer":338,"region":146,"url":454,"description":455,"useCases":456,"indexable":207},"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":458,"label":459,"issuer":460,"region":350,"url":461,"description":462,"useCases":456,"indexable":207},"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":464,"label":465,"issuer":466,"region":358,"url":467,"description":468,"useCases":469,"indexable":207},"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.",11,{"id":471,"label":472,"issuer":338,"region":146,"url":473,"description":474,"useCases":469,"indexable":207},"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.",{"id":476,"label":477,"issuer":478,"region":146,"url":479,"description":480,"useCases":58,"indexable":207},"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":482,"label":483,"issuer":383,"region":228,"url":484,"description":485,"useCases":58,"indexable":207},"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":487,"label":488,"issuer":338,"region":146,"url":489,"description":490,"useCases":58,"indexable":207},"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":492,"label":493,"issuer":338,"region":146,"url":494,"description":495,"useCases":58,"indexable":207},"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":497,"label":498,"issuer":338,"region":146,"url":499,"description":500,"useCases":501,"indexable":207},"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.",9,{"id":503,"label":504,"issuer":505,"region":358,"url":506,"description":507,"useCases":508,"indexable":207},"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.",7,{"id":510,"label":511,"issuer":338,"region":146,"url":512,"description":513,"useCases":514,"indexable":207},"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":516,"label":517,"issuer":518,"region":519,"url":520,"description":521,"useCases":57,"indexable":207},"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":523,"label":524,"issuer":525,"region":146,"url":526,"description":527,"useCases":310,"indexable":207},"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":529,"label":530,"issuer":531,"region":146,"url":532,"description":533,"useCases":310,"indexable":207},"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":535,"label":536,"issuer":537,"region":228,"url":538,"description":539,"useCases":288,"indexable":207},"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":541,"label":542,"issuer":338,"region":146,"url":543,"description":544,"useCases":288,"indexable":207},"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":546,"label":547,"issuer":338,"region":146,"url":548,"description":549,"useCases":288,"indexable":207},"eu-mortgage-credit-directive","EU Mortgage Credit Directive","https://eur-lex.europa.eu/eli/dir/2014/17/oj","Directive 2014/17/EU: creditworthiness assessment, disclosure and advice rules for residential mortgage lending.",{"id":551,"label":552,"issuer":553,"region":358,"url":554,"description":555,"useCases":288,"indexable":207},"nyc-local-law-144","NYC Local Law 144","New York City","https://www.nyc.gov/site/dca/about/automated-employment-decision-tools.page","Bias audits and notices for automated employment decision tools used in hiring and promotion in New York City.",1790683490882]