[{"data":1,"prerenderedAt":577},["ShallowReactive",2],{"uc-ai-tutor-for-students":3,"uc-regulations":370},{"useCase":4,"evidence":201,"blitsAiDeployments":291,"benchmarks":292,"indicative":293,"related":296,"indexability":368,"includeUnpublished":207},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":16,"functions":18,"patterns":20,"channels":23,"audience":26,"autonomy":27,"adoptionStage":28,"problem":29,"problemStats":30,"howItWorks":36,"valueDrivers":37,"kpis":41,"indicativeValue":45,"macroEstimates":86,"feasibility":87,"implementation":98,"risk":144,"blitsAi":183,"faq":185,"related":195,"datePublished":196,"dateModified":196,"lastVerified":196,"changelog":197,"slug":200},"AI tutor that coaches students through problems","AI tutor for students","AI tutor for students: results and risks","AI tutors guide students with hints, not answers. Harvard's CS50 has run one since 2023; a Khanmigo trial in 18 Tennessee schools found small gains and rare use.","published","An AI tutor that works with a student on course material in a conversation, asking questions and giving hints instead of handing over answers, grounded in the course content and set up by the school or teacher, with limits on use and a clear route to a human teacher.",[12,13,14,15],"AI tutoring assistant","Socratic AI tutor","virtual tutor for students","AI homework helper",[17],"education",[19],"customer-service",[21,22],"conversational-agent","rag-knowledge-assistant",[24,25],"web-chat","mobile-app","customer-facing","assist","emerging","A 2026 working paper on AI tutoring sums up the research on human tutoring: the best one to one\nprogrammes produce gains of a third of a standard deviation or more, but high dosage tutoring often\ncosts several thousand dollars per student per year. In large courses the queue for help is the\nbottleneck: Harvard's CS50 recalls times when office hours became unmanageable and the average\nwait could be as long as an hour.\n\nGeneral purpose chatbots answer every question fully and fluently, which is exactly what a\nlearner does not need: a finished answer skips the struggle that produces learning, and it makes\ncheating trivial. The job is different from a help desk. A tutor has to hold back, ask the next\nquestion, spot the misconception and push the student to do the work, within the course's rules\non academic honesty.\n\nThe evidence so far is mixed. A randomized trial of Khan Academy's Khanmigo in 18 Tennessee\nmiddle schools found small gains that resembled those from Khan Academy practice without AI, and\nthat almost every student tried the tutor but rarely engaged it in substantive mathematical\ndialogue; the authors suggest low engagement as one explanation. A World Bank pilot in Nigeria, run with\nteacher support, reported large gains in six weeks, and larger gains for students who\nattended more sessions. The Khanmigo authors conclude that realizing the promise of AI tutoring\nwill require getting students to use it, not just giving them access.",[31],{"statement":32,"sourceTitle":33,"sourceUrl":34,"year":35},"A 2026 EdWorkingPaper by Philip Oreopoulos and Nina Low, citing Nickow et al. (2024), puts the average effect of tutoring programmes at roughly 0.3 standard deviations, and notes that high dosage programmes often cost several thousand dollars per student per year.","One Click Away: AI Tutoring with Khanmigo in a Two-Year School Experiment","https://edworkingpapers.com/sites/default/files/ai26-1551.pdf",2026,"1. **Set the scope.** The school or teacher defines the course, the material the tutor may use\n   and the rules: no full solutions to graded work, adherence to the academic honesty policy,\n   escalation topics such as wellbeing concerns.\n2. **Ground the tutor in the course.** Lecture notes, readings and worked examples are indexed so\n   the tutor explains in the course's own terms and cites where a concept is taught.\n3. **Coach, do not solve.** The tutor asks what the student has tried, gives the smallest useful\n   hint, checks understanding with a question and only then moves on. A second check reviews each\n   reply before the student sees it and can reject or retry replies that give away an answer.\n4. **Limit and pace use.** A cap on questions per period (CS50 uses a \"heart\" system) stops\n   students from replacing thinking with hundreds of prompts, and prompts inside the exercise flow nudge students who are\n   stuck but not asking.\n5. **Keep the teacher in the loop.** Teachers see aggregated topics and misconceptions, can read\n   conversations under the school's policy, and take over for anything personal or sensitive.",[38,39,40],"inclusion-and-access","customer-experience","employee-productivity",[42,43,44],"users-served","interactions-handled","customer-satisfaction",{"referenceOrg":46,"inputs":47,"formula":81,"currency":82,"period":83,"resultLabel":84,"caveat":85},"A school district with 10,000 students in grades 6 to 12",[48,53,60,67,74],{"key":49,"label":50,"low":51,"high":51,"unit":49,"note":52},"students","Students with access to the tutor",10000,"The reference district.",{"key":54,"label":55,"low":56,"high":57,"unit":58,"note":59},"activeShare","Share of students who use the tutor substantively",0.15,0.35,"fraction of students","Conservative on purpose. In the Khanmigo trial on this page, 96 percent of students tried the tutor but the median student messaged it on only a third of practice days. Editorial assumption, replace with your own usage data.",{"key":61,"label":62,"low":63,"high":64,"unit":65,"note":66},"hoursPerStudent","Tutoring hours per active student per year",5,15,"hours per student per year","Editorial assumption, replace with your own usage data.",{"key":68,"label":69,"low":70,"high":71,"unit":72,"note":73},"equivalence","Value of an AI tutoring hour relative to a human tutoring hour",0.1,0.4,"fraction of a human tutoring hour","Editorial assumption. The Khanmigo trial on this page found gains similar to Khan Academy practice without AI, so the trial evidence does not support treating an AI tutoring hour as equal to a human one.",{"key":75,"label":76,"low":77,"high":78,"unit":79,"note":80},"tutorCostPerHour","Cost of an hour of human tutoring",20,40,"USD per hour","Editorial assumption for group or online tutoring, replace with your local rate.","students * activeShare * hoursPerStudent * equivalence * tutorCostPerHour","USD","per year","Equivalent value of tutoring time delivered","A proxy, not a learning outcome. It prices tutoring time, discounted heavily because AI tutoring is not equivalent to a human tutor, and leaves out licence and integration costs, teacher time to supervise and the risk that students use the tutor to avoid work. The larger randomized trial on this page (Khanmigo, 18 Tennessee middle schools) found no clear gain from the AI tutor beyond what the same practice platform delivers without it, so the value may be close to zero where students rarely engage; the positive Nigerian pilot was short, ran with teacher support and was reported by the World Bank team ahead of formal publication. Measure learning gains against a comparison group before claiming more.",[],{"complexity":88,"complexityNote":89,"dataPrerequisites":90,"integrations":94},"medium","A chatbot is easy; a tutor that reliably holds back answers, stays inside the course and is used well by students is hard. Most of the work is pedagogy, safeguarding and embedding the tutor in the exercise flow, not integration.",[91,92,93],"Course materials, worked examples and rubrics the school has the right to use","The course's academic honesty policy written as rules the tutor can follow","A set of real student questions and misconceptions to test against",[95,96,97],"Learning management system or course platform (single sign on, course roster)","Exercise or practice platform, so the tutor can appear where students get stuck","Safeguarding and wellbeing referral process",{"steps":99,"guardrails":118,"humanInTheLoop":124,"kpisToInstrument":125,"failureModes":131},[100,103,106,109,112,115],{"title":101,"detail":102},"Start with one course and one teacher team","Pick a course with high demand for help and a teacher team willing to shape the tutor's behaviour. Write down what the tutor must never do (give a full solution to graded work) and what it should always do (ask what the student tried).",{"title":104,"detail":105},"Ground it in the course","Index the course's own notes, readings and examples, and make the tutor cite where a concept is taught. Refuse or redirect questions outside the course.",{"title":107,"detail":108},"Add an answer check","Review every reply before the student sees it with a second pass that rejects replies that contain full solutions or break the honesty policy. CS50 reports that instructions alone were not enough.",{"title":110,"detail":111},"Put the tutor where students get stuck","Embed it in the exercise flow and prompt it after a wrong answer, rather than as a separate chat tab students must choose to open. The Khanmigo trial shows that optional access alone produces little use.",{"title":113,"detail":114},"Pace use and involve teachers","Cap questions per student per period, show teachers the common misconceptions each week and agree how teachers follow up with students who over rely on the tutor or show signs of distress.",{"title":116,"detail":117},"Evaluate learning, not usage","Compare learning outcomes with a comparison group over at least a term, and report engagement honestly, including off topic use and attempts to extract answers.",[119,120,121,122,123],"A reply check that blocks full solutions to graded work and anything against the honesty policy","Answers grounded in approved course material, with a refusal outside the course","A cap on questions per student per period","Age appropriate content filters and escalation of wellbeing or safeguarding signals to staff","No emotion recognition of students, which the EU AI Act prohibits in education","Teachers own the course scope, the rules and the follow up. They review aggregated topics and a sample of conversations each week, handle any safeguarding signal, and decide grades; the tutor never grades or places a student.",[126,127,128,129,130],"Share of students who use the tutor substantively each week, not just once","Share of stuck moments (wrong answers) in which the student asks the tutor for help","Replies blocked or retried by the answer check","Learning gains against a comparison group over a term","Student and teacher satisfaction",[132,135,138,141],{"title":133,"detail":134},"Access without engagement","Students try the tutor once and stop, or ask it off topic questions. Embed it in the work and prompt it at the moment of error.",{"title":136,"detail":137},"Answer vending","Students talk the tutor into giving the solution, which removes the learning. Check replies before they are shown and log extraction attempts.",{"title":139,"detail":140},"Over reliance","A few students ask hundreds of questions instead of thinking. Cap questions per period and let teachers follow up.",{"title":142,"detail":143},"Confidently wrong explanations","The tutor explains a concept incorrectly. Ground it in course material, test it on known misconceptions and let students flag errors to teachers.",{"euAiAct":145,"regulations":148,"guidance":154,"controls":176,"incidents":182},{"tier":146,"basis":147},"context-dependent","A tutor that only converses with students falls under the transparency duty of Article 50. It becomes high risk under Annex III point 3(b) when it evaluates learning outcomes, including when those outcomes are used to steer a student's learning process, and under point 3(c) when it assesses the level of education a student should receive. Inferring students' emotions is prohibited in education institutions under Article 5(1)(f).",[149,150,151,152,153],"eu-ai-act","gdpr","uk-gdpr","nist-ai-rmf","iso-42001",[155,161,167,172],{"title":156,"issuer":157,"region":158,"url":159,"note":160},"Guidance for generative AI in education and research","UNESCO","global","https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research","UNESCO's first global guidance on generative AI in education; it proposes protecting learners' data privacy and setting an age limit for independent conversations with generative AI platforms.",{"title":162,"issuer":163,"region":164,"url":165,"note":166},"Generative artificial intelligence (AI) in education","UK Department for Education","europe","https://www.gov.uk/government/publications/generative-artificial-intelligence-in-education","The department's position on generative AI tools in schools and colleges, to be read together with its product safety expectations for generative AI.",{"title":168,"issuer":169,"region":164,"url":170,"note":171},"Regulation (EU) 2024/1689 (AI Act), Annex III point 3, education and vocational training","European Union","https://eur-lex.europa.eu/eli/reg/2024/1689/oj/eng","Lists as high risk AI that evaluates learning outcomes, including when those outcomes steer the learning process, and AI that assesses the appropriate level of education a person will receive (point 3(b) and 3(c)).",{"title":173,"issuer":169,"region":164,"url":174,"note":175},"Article 5, prohibited AI practices","https://artificialintelligenceact.eu/article/5/","Prohibits AI systems that infer the emotions of a natural person in education institutions, except for medical or safety reasons.",[177,178,179,180,181],"AI disclosure to students and parents, with the school's rules for use","A data protection impact assessment covering minors and conversation logs","Inventory entry with an accountable owner per course","Regression tests for answer giving and off topic behaviour on every prompt or model change","Teacher review of aggregated topics and a sample of conversations",[],{"howToBuild":184},"On Blits.ai this is an **AI agent** with a tutoring persona and prompt versioning, grounded in a\n**knowledge base** that holds only the course's own material, retrieved with hybrid search.\n**Output guardrails** with an admin authored policy check every reply before the student sees\nit, so replies that hand over a full solution or break the honesty policy are blocked, and the\ndeterministic content scanner and profanity detection keep the conversation age appropriate.\n\nThe tutor runs in the **web chat** widget or inside the school's own learning platform through\nthe **REST or WebSocket API** channel, with voice input and spoken replies where that helps\nyounger or struggling readers, and multi language support for students learning in a second\nlanguage. **Human handover** routes wellbeing signals to staff, **test suites** with LLM grading,\nrun after each change, check that the tutor still refuses to give answers, and **analytics** and\nconversation logs let teachers follow usage and review a sample of conversations. The platform is model agnostic and supports EU data residency.",[186,189,192],{"question":187,"answer":188},"Do AI tutors improve learning?","Sometimes, and it depends on how they are used. A World Bank pilot in Edo, Nigeria, run with teacher support, reported gains of about 0.3 standard deviations in six weeks. A two year randomized trial of Khanmigo in 18 Tennessee middle schools found small gains similar to Khan Academy practice without AI; the authors suggest low engagement as one explanation, as the median student messaged the tutor on only a third of the days they practiced.",{"question":190,"answer":191},"How do you stop an AI tutor from giving students the answers?","Instructions alone are not enough. Harvard's CS50 combines prompting with code that tries to evaluate each reply before the student sees it and sometimes rejects or retries it, plus a limit on questions per period. Test the tutor against real attempts to extract answers on every change.",{"question":193,"answer":194},"Is an AI tutor high risk under the EU AI Act?","A tutor that only converses is subject to the transparency duty. It is high risk under Annex III point 3(b) if it evaluates learning outcomes, including when those outcomes steer a student's learning, or under point 3(c) if it assesses the level of education a student should receive. Inferring students' emotions in education is prohibited outright.",[],"2026-09-27",[198],{"date":196,"note":199},"First published","ai-tutor-for-students",[202,239,265],{"title":203,"useCases":204,"organization":205,"vendors":210,"summary":214,"stage":215,"year":216,"channels":217,"languages":218,"metrics":220,"outcomeDisclosed":221,"sources":222,"verification":234,"grade":236,"id":237,"organizationSlug":238},"Hamilton County Schools: Khanmigo AI tutor in a two year randomized trial in 18 middle schools",[200],{"name":206,"anonymized":207,"country":208,"region":209,"industry":17},"Hamilton County Schools",false,"US","north-america",[211],{"name":212,"role":213},"Khan Academy","platform","Philip Oreopoulos and Nina Low ran a two year cluster randomized trial in 18 Tennessee middle schools in Hamilton County in the 2024/25 and 2025/26 school years, in which randomly assigned students used Khan Academy with its AI tutor Khanmigo, configured to coach rather than give answers, during existing daily remedial maths sessions. Assignment raised maths achievement by 1.3 national percentile ranks per term, similar to Khan Academy practice without AI. Almost every student tried Khanmigo, but the median student messaged it on only a third of the days they practiced and in only 17 percent of the exercise sessions in which they made a mistake, and the messages students did send were mostly bare answers or clicks on suggested prompts. Chalkbeat reports that Khan Academy has since redesigned its interface to integrate Khanmigo better.","pilot",2024,[24],[219],"en",[],true,[223,227,229],{"url":224,"title":225,"publisher":226},"https://edworkingpapers.com/ai26-1551","One Click Away: AI Tutoring with Khanmigo in a Two-Year School Experiment (EdWorkingPaper 26-1551)","Annenberg Institute at Brown University",{"url":34,"title":228,"publisher":226},"One Click Away: AI Tutoring with Khanmigo in a Two-Year School Experiment (full paper, PDF)",{"url":230,"title":231,"publisher":232,"date":233},"https://www.chalkbeat.org/2026/08/25/ai-tutoring-students-khanmigo-khan-academy-engagement-study/","Students rarely engaged with Khan Academy's AI-powered tutor Khanmigo, study finds","Chalkbeat","2026-08-25",{"level":235,"checkedAt":196},"source-verified","B","hamilton-county-schools-khanmigo-trial",null,{"title":240,"useCases":241,"organization":242,"vendors":246,"summary":249,"stage":215,"year":216,"channels":250,"languages":251,"metrics":252,"outcomeDisclosed":221,"sources":253,"verification":263,"grade":236,"id":264,"organizationSlug":238},"World Bank: generative AI tutor pilot in after school English classes in Edo, Nigeria",[200],{"name":243,"anonymized":207,"country":244,"region":245,"industry":17},"World Bank","NG","africa",[247],{"name":248,"role":213},"Microsoft","In June and July 2024 a World Bank team, working with the Edo State education authorities, ran a six week after school programme in Edo, Nigeria, in which 800 first year senior secondary students used Microsoft Copilot as a tutor, mainly to learn English, with teacher support: teachers introduced each session's topic, suggested prompts and mentored students as they worked with the tool. In a randomized evaluation, participants outperformed their peers in English, AI knowledge and digital skills, and also did better in their end of year exams. The team reports learning gains of about 0.3 standard deviations, says the programme outperformed 80% of the interventions in a database of randomized evaluations in developing countries, and reports that the more sessions students attended, the greater their gains; girls, who started behind boys, seemed to gain even more.",[],[219],[],[254,259],{"url":255,"title":256,"publisher":257,"date":258},"https://blogs.worldbank.org/en/education/From-chalkboards-to-chatbots-Transforming-learning-in-Nigeria","From chalkboards to chatbots: Transforming learning in Nigeria, one prompt at a time","World Bank Blogs","2025-01-09",{"url":260,"title":261,"publisher":257,"date":262},"https://blogs.worldbank.org/en/education/From-chalkboards-to-chatbots-in-Nigeria","From chalkboards to chatbots in Nigeria: 7 lessons to pioneer generative AI for education","2024-09-18",{"level":235,"checkedAt":196},"world-bank-edo-nigeria-ai-tutor-pilot",{"title":266,"useCases":267,"organization":268,"vendors":270,"summary":277,"stage":278,"year":279,"channels":280,"languages":281,"metrics":282,"outcomeDisclosed":207,"sources":283,"verification":289,"grade":236,"id":290,"organizationSlug":238},"Harvard University: the CS50 Duck, an AI tutor that guides instead of answering",[200],{"name":269,"anonymized":207,"country":208,"region":209,"industry":17},"Harvard University",[271,274],{"name":272,"role":273},"OpenAI","model-provider",{"name":275,"role":276},"Harvard CS50","in-house","Since spring 2023 Harvard's introductory computer science course CS50 has run the \"CS50 Duck\", an AI tutor built on the ChatGPT API that is deliberately less helpful than a general chatbot: it asks more questions than it answers and avoids giving outright solutions. The course combines prompting with its own code that tries to evaluate each reply before the student sees it and sometimes rejects or retries it, and added a \"heart system\" that limits questions per period after some students asked around 200 questions. David Malan calls it a net positive but acknowledges the Duck still sometimes returns code despite instructions not to.","production",2023,[24],[219],[],[284],{"url":285,"title":286,"publisher":287,"date":288},"https://news.harvard.edu/gazette/story/2026/09/taming-the-duck-for-starters/","Taming the Duck, for starters","Harvard Gazette","2026-09-25",{"level":235,"checkedAt":196},"harvard-cs50-duck-ai-tutor",0,[],{"low":294,"high":295},15000,840000,[297,311,327,354],{"slug":298,"title":299,"shortTitle":300,"definition":301,"status":9,"industries":302,"functions":303,"patterns":304,"audience":26,"autonomy":27,"adoptionStage":28,"evidenceCount":305,"publicEvidenceCount":305,"organizations":306,"bestGrade":236,"headline":238,"lastVerified":310,"indexable":221},"academic-advising-assistant","AI academic advising assistant for course selection and degree requirements","Academic advising assistant","An AI assistant that answers students' questions about degree requirements, course selection, prerequisites and majors, grounded in the institution's own catalog and advising documents, so students get quick answers to routine questions and are directed to a human advisor for anything that needs judgment, is time sensitive, or falls outside what the assistant can see.",[17],[19],[21,22],3,[307,308,309],"Elon University","Harvard College","University of Utah","2026-09-28",{"slug":312,"title":313,"shortTitle":314,"definition":315,"status":9,"industries":316,"functions":317,"patterns":319,"audience":26,"autonomy":321,"adoptionStage":322,"evidenceCount":305,"publicEvidenceCount":305,"organizations":323,"bestGrade":236,"headline":238,"lastVerified":196,"indexable":221},"student-enrollment-and-services-assistant","AI assistant for student enrollment and student services","Student enrollment assistant","An AI assistant that answers admitted and current students' questions about admissions, financial aid, registration, housing and deadlines by text message and web chat, sends timely reminders for the tasks each student still has to complete, and hands personal or complex cases to staff.",[17],[19,318],"operations",[21,22,320],"classification-and-routing","supervised-agent","early-adopters",[324,325,326],"Adelphi University","Austin Peay State University","Georgia State University",{"slug":328,"title":329,"shortTitle":330,"definition":331,"status":9,"industries":332,"functions":335,"patterns":336,"audience":26,"autonomy":321,"adoptionStage":339,"segment":340,"evidenceCount":341,"publicEvidenceCount":342,"organizations":343,"bestGrade":236,"headline":346,"lastVerified":196,"indexable":221},"account-and-card-servicing-agent","AI agent for account and card servicing","Account and card servicing","An AI agent that resolves routine account and card requests end to end, such as balances, statements, card blocks and replacements, PIN resets and limit changes, across app, web, messaging and phone, and hands anything sensitive or unusual to a human with the full context.",[333,334],"banking","payments",[19,318],[21,337,338,22],"voice-agent","agentic-workflow","mainstream","front-office",4,2,[344,345],"Commonwealth Bank of Australia","DBS Bank",{"kpi":347,"label":348,"unit":349,"n":342,"nUpTo":291,"kind":350,"value":351,"qualifier":352,"claimant":353,"organization":345,"vendorReported":207},"containment-rate","Containment rate","percent","reported",90,"approximately","organization",{"slug":355,"title":356,"shortTitle":357,"definition":358,"status":9,"industries":359,"functions":361,"patterns":363,"audience":26,"autonomy":321,"adoptionStage":322,"evidenceCount":305,"publicEvidenceCount":305,"organizations":364,"bestGrade":236,"headline":238,"lastVerified":196,"indexable":221},"apartment-leasing-and-resident-service-agent","AI agent for apartment leasing inquiries and resident service","Leasing and resident service agent","An AI agent that answers rental prospects and residents by chat, text, email and phone for a property manager: it answers questions about apartments and policies, books tours, takes maintenance requests, sends renewal and payment reminders, and hands anything that needs judgment to leasing or service staff.",[360],"real-estate",[19,362,318],"sales",[21,337,338,22],[365,366,367],"Asset Living","AvalonBay Communities","Equity Residential",{"indexable":221,"reasons":369},[],[371,376,381,387,393,399,405,412,420,427,433,439,446,452,458,463,470,476,482,488,494,500,506,511,516,523,530,535,541,548,554,560,566,571],{"id":149,"label":372,"issuer":169,"region":164,"url":373,"description":374,"useCases":375,"indexable":221},"EU AI Act","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.",197,{"id":150,"label":377,"issuer":169,"region":164,"url":378,"description":379,"useCases":380,"indexable":221},"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":153,"label":382,"issuer":383,"region":158,"url":384,"description":385,"useCases":386,"indexable":221},"ISO/IEC 42001","ISO and IEC","https://www.iso.org/standard/81230.html","The international management system standard for AI.",110,{"id":152,"label":388,"issuer":389,"region":209,"url":390,"description":391,"useCases":392,"indexable":221},"NIST AI Risk Management Framework","NIST","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":394,"label":395,"issuer":169,"region":164,"url":396,"description":397,"useCases":398,"indexable":221},"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":151,"label":400,"issuer":401,"region":164,"url":402,"description":403,"useCases":404,"indexable":221},"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":406,"label":407,"issuer":408,"region":164,"url":409,"description":410,"useCases":411,"indexable":221},"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":413,"label":414,"issuer":415,"region":416,"url":417,"description":418,"useCases":419,"indexable":221},"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":421,"label":422,"issuer":423,"region":416,"url":424,"description":425,"useCases":426,"indexable":221},"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":428,"label":429,"issuer":430,"region":158,"url":431,"description":432,"useCases":77,"indexable":221},"pci-dss","PCI DSS","PCI Security Standards Council","https://www.pcisecuritystandards.org/","Security standard for any system that stores, processes or transmits cardholder data.",{"id":434,"label":435,"issuer":436,"region":209,"url":437,"description":438,"useCases":77,"indexable":221},"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":440,"label":441,"issuer":442,"region":164,"url":443,"description":444,"useCases":445,"indexable":221},"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":447,"label":448,"issuer":449,"region":158,"url":450,"description":451,"useCases":64,"indexable":221},"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.",{"id":453,"label":454,"issuer":169,"region":164,"url":455,"description":456,"useCases":457,"indexable":221},"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":459,"label":460,"issuer":169,"region":164,"url":461,"description":462,"useCases":457,"indexable":221},"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":464,"label":465,"issuer":466,"region":209,"url":467,"description":468,"useCases":469,"indexable":221},"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":471,"label":472,"issuer":169,"region":164,"url":473,"description":474,"useCases":475,"indexable":221},"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":477,"label":478,"issuer":479,"region":209,"url":480,"description":481,"useCases":475,"indexable":221},"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":483,"label":484,"issuer":485,"region":158,"url":486,"description":487,"useCases":475,"indexable":221},"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":489,"label":490,"issuer":169,"region":164,"url":491,"description":492,"useCases":493,"indexable":221},"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":495,"label":496,"issuer":497,"region":209,"url":498,"description":499,"useCases":493,"indexable":221},"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":501,"label":502,"issuer":415,"region":416,"url":503,"description":504,"useCases":505,"indexable":221},"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.",10,{"id":507,"label":508,"issuer":169,"region":164,"url":509,"description":510,"useCases":505,"indexable":221},"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":512,"label":513,"issuer":169,"region":164,"url":514,"description":515,"useCases":505,"indexable":221},"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":517,"label":518,"issuer":519,"region":164,"url":520,"description":521,"useCases":522,"indexable":221},"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.",9,{"id":524,"label":525,"issuer":526,"region":209,"url":527,"description":528,"useCases":529,"indexable":221},"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.",8,{"id":531,"label":532,"issuer":169,"region":164,"url":533,"description":534,"useCases":529,"indexable":221},"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":536,"label":537,"issuer":169,"region":164,"url":538,"description":539,"useCases":540,"indexable":221},"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":542,"label":543,"issuer":544,"region":545,"url":546,"description":547,"useCases":63,"indexable":221},"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":549,"label":550,"issuer":551,"region":164,"url":552,"description":553,"useCases":341,"indexable":221},"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":555,"label":556,"issuer":557,"region":164,"url":558,"description":559,"useCases":341,"indexable":221},"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":561,"label":562,"issuer":563,"region":416,"url":564,"description":565,"useCases":305,"indexable":221},"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":567,"label":568,"issuer":169,"region":164,"url":569,"description":570,"useCases":305,"indexable":221},"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":572,"label":573,"issuer":574,"region":209,"url":575,"description":576,"useCases":305,"indexable":221},"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.",1790598306921]