[{"data":1,"prerenderedAt":558},["ShallowReactive",2],{"uc-suitability-assessment-assistant":3,"uc-regulations":353},{"useCase":4,"evidence":197,"blitsAiDeployments":258,"benchmarks":259,"indicative":260,"related":263,"indexability":351,"includeUnpublished":203},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":16,"functions":19,"patterns":23,"channels":27,"audience":29,"autonomy":30,"adoptionStage":31,"segment":32,"problem":33,"problemStats":34,"howItWorks":35,"valueDrivers":36,"kpis":41,"indicativeValue":46,"macroEstimates":80,"feasibility":81,"implementation":94,"risk":137,"blitsAi":173,"faq":175,"related":185,"datePublished":191,"dateModified":191,"lastVerified":192,"changelog":193,"slug":196},"AI assistant for investment suitability assessment and reports","Suitability assessment","AI suitability assessment for investment advice","An AI assistant checks client fit and drafts suitability reports while hard fails stay with rules. Covers MiFID II, ESMA's AI statement and Morgan Stanley.","published","An AI assistant that checks whether a proposed product or portfolio fits a client's risk tolerance, objectives, knowledge, experience and financial situation against the firm's rules, flags mismatches, and drafts the suitability rationale and report for the advisor to confirm, while hard rule failures are decided by deterministic checks, not by the model.",[12,13,14,15],"suitability report drafting","suitability check copilot","appropriateness assessment assistant","statement of suitability generator",[17,18],"wealth-and-asset-management","banking",[20,21,22],"regulatory-compliance","sales","risk-management",[24,25,26],"agentic-workflow","content-generation","classification-and-routing",[28],"internal-tools","employee-facing","copilot","emerging","front-office","Every investment recommendation to a retail client needs a documented suitability assessment:\ndoes the product or portfolio match the client's objectives, horizon, risk tolerance, capacity for\nloss, knowledge and experience, and sustainability preferences, and why. Under MiFID II the client\nreceives a written statement of suitability, and comparable suitability or best interest duties\napply in other major markets.\n\nIn practice the rationale is written by hand from a fact find, a risk profile and product data held\nin different systems. Quality varies by advisor, reports are long and generic, and supervisors find\ngaps only when sampling after the fact. Circumstances also change: a report that was right at the\ntime of advice says nothing about whether the portfolio still fits a year later.",[],"1. **Assemble the facts.** The assistant pulls the client's profile (objectives, horizon, risk\n   tolerance, capacity for loss, knowledge and experience, preferences) and the proposed products\n   or portfolio with their risk and cost data.\n2. **Run the rules.** A deterministic rules engine applies the firm's suitability and product\n   governance rules (risk class limits, target market, concentration, complexity) and returns pass,\n   fail or refer, with reasons.\n3. **Reason about the gaps.** For referrals, the model explains the mismatch in plain language and\n   suggests what information is missing or what the advisor should consider.\n4. **Draft the report.** A suitability rationale is drafted in the firm's template, quoting the\n   client's own stated objectives and the rule results, never inventing facts.\n5. **Advisor and supervisor confirm.** The advisor edits and confirms the report; referrals and\n   hard fails go to a supervisor. Everything is logged for audit.",[37,38,39,40],"compliance","employee-productivity","risk-reduction","customer-experience",[42,43,44,45],"time-saved-per-task","error-reduction","accuracy","processing-time-reduction",{"referenceOrg":47,"inputs":48,"formula":75,"currency":76,"period":77,"resultLabel":78,"caveat":79},"A wealth manager with 500 advisors giving regulated advice",[49,54,61,68],{"key":50,"label":51,"low":52,"high":52,"unit":50,"note":53},"advisors","Advisors giving regulated advice",500,"The reference firm.",{"key":55,"label":56,"low":57,"high":58,"unit":59,"note":60},"recommendations","Recommendations with a suitability report per advisor per year",100,200,"reports per advisor per year","Editorial assumption, replace with your own advice volumes.",{"key":62,"label":63,"low":64,"high":65,"unit":66,"note":67},"minutesSaved","Minutes saved per suitability report",15,30,"minutes per report","Editorial assumption, replace with your own. No public source on this page states a time saving for AI drafted suitability reports.",{"key":69,"label":70,"low":71,"high":72,"unit":73,"note":74},"hourlyCost","Fully loaded advisor cost per hour",80,150,"USD per hour","Editorial assumption, replace with your own fully loaded cost.","advisors * recommendations * minutesSaved / 60 * hourlyCost","USD","per year","Value of advisor time released from suitability write up","Productivity only. The main value is consistent, complete suitability records and fewer unsuitable recommendations, which this figure does not price, and it leaves out rules engine and review costs.",[],{"complexity":82,"complexityNote":83,"dataPrerequisites":84,"integrations":89},"high","This is a regulated control. It needs codified suitability and product governance rules, clean client profile data, a validated risk profiling method, compliance sign off on the report template and a full audit trail.",[85,86,87,88],"Client fact find and risk profile with dates of last update","Product data such as risk class, complexity, costs and target market","Codified suitability and product governance rules per market","Approved suitability report templates and wording",[90,91,92,93],"Advice and portfolio management platform","Product governance and target market database","CRM for client profile and records","Document generation and client delivery",{"steps":95,"guardrails":111,"humanInTheLoop":117,"kpisToInstrument":118,"failureModes":124},[96,99,102,105,108],{"title":97,"detail":98},"Codify the rules before adding a model","Write the firm's suitability and target market rules as deterministic checks with clear outcomes. The model explains and drafts; it does not decide hard fails.",{"title":100,"detail":101},"Draft from facts, not from memory","The report may only cite the client's recorded profile, the rule results and product data. Anything the model cannot trace to a source is left out or flagged.",{"title":103,"detail":104},"Pilot on one advice type","Start with a common, simple advice type (for example a model portfolio recommendation) and compare AI drafted reports with manual ones in supervisory review.",{"title":106,"detail":107},"Add ongoing suitability monitoring","Once point in time assessments work, rerun the checks when markets or client circumstances change and flag portfolios that no longer fit for advisor review.",{"title":109,"detail":110},"Keep compliance in the loop","Compliance approves templates, rule changes and model changes, and samples reports every month.",[112,113,114,115,116],"Hard suitability failures decided by deterministic rules, never overridden by the model","Reports cite only recorded client facts, rule results and product data","Advisor confirmation of every report, supervisor review of referrals and overrides","Full audit log of inputs, rule outcomes, drafts and edits","No use of protected characteristics in suitability reasoning","The advisor confirms each assessment and report and remains responsible for the recommendation; supervisors decide referrals and overrides; compliance owns the rules and templates and samples output.",[119,120,121,122,123],"Time to a confirmed suitability report","Supervisory findings per hundred reports, before and after","Share of assessments referred or failed, with reasons","Advisor edit rate on drafted rationales","Portfolios flagged by ongoing monitoring and resolved",[125,128,131,134],{"title":126,"detail":127},"Model overrules the rule","A fluent rationale justifies a product that failed a hard check. Keep the verdict in the rules engine and block contradictory drafts.",{"title":129,"detail":130},"Boilerplate reports","Every report reads the same and does not reflect the client's own words. Require quotes from the fact find and supervise for generic text.",{"title":132,"detail":133},"Stale profiles","The assessment uses a risk profile that is years old. Check profile dates and require an update before advice.",{"title":135,"detail":136},"Hidden bias","Reasoning uses proxies such as age or nationality inappropriately. Test outputs across segments and restrict inputs.",{"euAiAct":138,"regulations":141,"guidance":149,"controls":166,"incidents":172},{"tier":139,"basis":140},"context-dependent","Investment suitability assessment is not listed in Annex III, so the tier depends on design. It becomes high risk where the same system assesses creditworthiness, for example for lending against a portfolio (Annex III point 5(b)). MiFID II suitability duties apply regardless of the AI Act tier.",[142,143,144,145,146,147,148],"eu-ai-act","gdpr","uk-consumer-duty","mas-ai-risk-management","us-sr-11-7","iso-42001","mifid-ii",[150,156,160],{"title":151,"issuer":152,"region":153,"url":154,"note":155},"Guidelines on certain aspects of the MiFID II suitability requirements","European Securities and Markets Authority","europe","https://www.esma.europa.eu/document/guidelines-certain-aspects-mifid-ii-suitability-requirements-1","The current guidelines (ESMA35-43-3172, 2022), which replaced the 2018 version (ESMA35-43-1163). They set out how firms collect client information, including sustainability preferences, assess suitability and document it, with specific points on automated advice.",{"title":157,"issuer":152,"region":153,"url":158,"note":159},"ESMA public statement on the use of AI in the provision of retail investment services","https://www.esma.europa.eu/sites/default/files/2024-05/ESMA35-335435667-5924__Public_Statement_on_AI_and_investment_services.pdf","Says firms that use AI in investment advice and portfolio management must apply heightened vigilance and diligence, particularly in ensuring the suitability of services and financial instruments for each client.",{"title":161,"issuer":162,"region":163,"url":164,"note":165},"Artificial Intelligence Model Risk Management (information paper)","Monetary Authority of Singapore","asia-pacific","https://www.mas.gov.sg/publications/monographs-or-information-paper/2024/artificial-intelligence-model-risk-management","Good practices observed in a 2024 MAS thematic review of banks' AI and generative AI model risk management, covering governance and oversight, risk management systems and processes, and development and deployment.",[167,168,169,170,171],"Rules engine and model inventoried with owners in compliance and the business","Version control and approval for rules, templates and prompts","Audit trail per assessment kept for the regulatory retention period","Monthly supervisory sampling with documented findings","Fairness testing of drafted rationales across client segments",[],{"howToBuild":174},"On Blits.ai the deterministic checks run as **custom functions** (custom code in an isolated\nsandbox, or REST calls to the firm's existing rules engine), orchestrated by an **agentic\nworkflow** whose **tool execution policy** limits it to reading data and running checks. An **AI\nagent** with **structured output** drafts the rationale in the approved template from the client\nprofile and rule results, with the firm's suitability policy held in a **knowledge base**.\n\nEvery draft pauses for **human in the loop** approval, and referrals route to a supervisor. The\nworkflow's **audit trail** keeps inputs, rule outcomes, drafts and decisions per run. **Guardrails**\nblock drafts that contradict a failed rule, **PII masking** protects client data, and **test\nsuites** with deterministic and LLM based grading replay reference cases after every rule or prompt change.\n**Agentic tasks** can recheck suitability when a condition such as a large drawdown is met.",[176,179,182],{"question":177,"answer":178},"Can AI decide whether an investment is suitable?","It should not make the verdict on its own. Keep hard rules in a deterministic engine, let the model explain and draft, and have the advisor confirm. ESMA expects heightened diligence on suitability when AI is used in advice.",{"question":180,"answer":181},"Is anyone doing this at scale yet?","Automated digital advice services such as Vanguard Digital Advisor already use an algorithm to build portfolios from a client's goals, time horizon and risk tolerance, and since October 2025 Morgan Stanley's advisors get AI drafted talking points that flag misalignment with a client's objectives. Public, named deployments of generative AI that write full suitability reports are still rare, so treat vendor claims with care.",{"question":183,"answer":184},"What about checking suitability after the sale?","That is where agentic monitoring helps: rerunning the checks when markets or client circumstances change and flagging portfolios for review. It links closely to drift monitoring.",[186,187,188,189,190],"goal-based-financial-planning-assistant","next-best-action-for-advisors","client-meeting-notes-and-crm-update","portfolio-drift-monitoring-and-rebalancing","wealth-advisor-knowledge-assistant","2026-09-27","2026-09-26",[194],{"date":191,"note":195},"First published","suitability-assessment-assistant",[198,229],{"title":199,"useCases":200,"organization":201,"vendors":206,"summary":209,"stage":210,"year":211,"channels":212,"languages":213,"metrics":215,"outcomeDisclosed":203,"sources":216,"verification":224,"grade":226,"id":227,"organizationSlug":228},"Vanguard: Digital Advisor goal based portfolios with automatic rebalancing",[186,189,196],{"name":202,"anonymized":203,"country":204,"region":205,"industry":17},"Vanguard",false,"US","north-america",[207],{"name":202,"role":208},"in-house","Vanguard Digital Advisor is an all digital advice service that gathers a client's goals, time horizon and risk tolerance, uses an algorithm to build a portfolio for them, and keeps it on track with ongoing monitoring. It rebalances when a portfolio drifts more than 5% from the recommended allocation and adjusts holdings when a client adds goals. Vanguard discloses limits of the automated assessment, for example that it does not assess the suitability of selling existing holdings, and it labels its projections and goal forecasts as hypothetical and educational, not guarantees. The service was live by 2020: a Vanguard page archived in December 2020 refers to Digital Advisor clients who enrolled before 1 October 2020.","production",2020,[],[214],"en",[],[217,220],{"url":218,"title":219,"publisher":202},"https://investor.vanguard.com/advice/digital-advisor","Vanguard Digital Advisor",{"url":221,"title":222,"publisher":202,"date":223},"https://web.archive.org/web/20201231135303/https://investor.vanguard.com/advice/digital-advisor","Vanguard Digital Advisor (Wayback Machine capture of 31 December 2020)","2020-12-31",{"level":225,"checkedAt":191},"source-verified","B","vanguard-digital-advisor",null,{"title":230,"useCases":231,"organization":233,"vendors":235,"summary":239,"stage":240,"year":241,"channels":242,"languages":243,"metrics":244,"outcomeDisclosed":203,"sources":245,"verification":254,"grade":255,"id":256,"organizationSlug":257},"Morgan Stanley: BlackRock Aladdin Wealth Auto Commentary in its Portfolio Risk Platform",[232,189,196],"portfolio-reporting-and-commentary",{"name":234,"anonymized":203,"country":204,"region":205,"industry":17},"Morgan Stanley",[236],{"name":237,"role":238},"BlackRock","platform","BlackRock announced on 2 October 2025 that Morgan Stanley Wealth Management's Portfolio Risk Platform would be the first to implement Auto Commentary, a generative AI feature of Aladdin Wealth, with advisors in the U.S. getting access from October. The tool combines Aladdin risk analytics, the firm's Chief Investment Office outlook and the client's holdings and investment preferences to draft concise insights for the advisor, highlighting issues such as overweights or misalignment with the client's objectives or the firm's market view. Trade press describes the output as bullet point insights inside a template, not full scripts or emails, so it supports the advisor's conversation rather than producing a finished client report. No outcome figures were published.","announced",2025,[28],[214],[],[246,250],{"url":247,"title":248,"publisher":237,"date":249},"https://www.blackrock.com/aladdin/discover/press-release/aladdin-wealth-launches-ai-enabled-commentary-tool-at-morgan-stanley","Aladdin Wealth™ Launches AI-Enabled Commentary Tool for Wealth Advisors; Morgan Stanley's Portfolio Risk Platform First to Implement","2025-10-02",{"url":251,"title":252,"publisher":253,"date":249},"https://www.investmentnews.com/alternatives/blackrock-debuts-ai-powered-commentary-tool-for-advisors-lands-morgan-stanley-as-first-client/262370","BlackRock debuts AI-powered commentary tool for advisors, lands Morgan Stanley as first client","InvestmentNews",{"level":225,"checkedAt":191},"C","morgan-stanley-aladdin-auto-commentary","morgan-stanley",0,[],{"low":261,"high":262},1000000,7500000,[264,278,304,326,340],{"slug":186,"title":265,"shortTitle":266,"definition":267,"status":9,"industries":268,"functions":269,"patterns":272,"audience":29,"autonomy":30,"adoptionStage":31,"segment":32,"evidenceCount":274,"publicEvidenceCount":274,"organizations":275,"bestGrade":226,"headline":228,"lastVerified":191,"indexable":277},"AI assistant for goal based financial planning","Goal based planning","An AI assistant that turns a client's goals into projections and what if scenarios using a rules based planning engine, explains the trade offs in plain language and prepares the plan for an advisor to validate, with every assumption disclosed and reproducible.",[17,18],[21,270,271],"customer-service","product-and-pricing",[273,25,24],"conversational-agent",2,[276,202],"CIMB Niaga",true,{"slug":187,"title":279,"shortTitle":280,"definition":281,"status":9,"industries":282,"functions":283,"patterns":286,"audience":29,"autonomy":289,"adoptionStage":290,"segment":32,"evidenceCount":291,"publicEvidenceCount":291,"organizations":292,"bestGrade":226,"headline":296,"lastVerified":191,"indexable":277},"AI next best action prompts for wealth advisors","Advisor next best action","An AI engine for wealth advisors, not customers, that scans an advisor's whole book and surfaces a short, ranked list of client specific prompts, such as idle cash, a maturing deposit, a concentration to review, a life event or an early sign of attrition, each with the reasoning and data behind it, for the advisor to act on or dismiss.",[17,18],[21,284,285],"marketing","analytics-and-reporting",[287,288,25],"recommendation-and-personalization","prediction-and-scoring","assist","early-adopters",5,[276,293,294,234,295],"Citi","JPMorgan Chase","UBS",{"kpi":297,"label":298,"unit":299,"n":300,"nUpTo":258,"kind":301,"value":71,"qualifier":302,"claimant":303,"organization":295,"vendorReported":203},"employee-adoption","Employee adoption","percent",1,"reported","exact","organization",{"slug":188,"title":305,"shortTitle":306,"definition":307,"status":9,"industries":308,"functions":309,"patterns":311,"audience":29,"autonomy":30,"adoptionStage":314,"segment":32,"evidenceCount":315,"publicEvidenceCount":315,"organizations":316,"bestGrade":226,"headline":322,"lastVerified":191,"indexable":277},"AI meeting notes and CRM update for wealth advisors","Advisor meeting notes","An AI notetaker for wealth advisors that turns a client advice meeting, recorded with the client's consent, into the file note, follow up message and CRM record the firm needs to evidence its advice; unlike a general meeting summarizer, its output becomes part of the regulated client record. It drafts a structured note with the client's goals, circumstances, decisions and action items, and writes it into the CRM once the advisor has approved it.",[17,18],[21,20,310],"operations",[312,313,24,25],"summarization","speech-analytics","mainstream",6,[317,318,234,319,320,321],"Bank of America","Commerzbank","Quilter","SEB","UniSuper",{"kpi":323,"label":324,"unit":299,"n":300,"nUpTo":258,"kind":301,"value":64,"qualifier":302,"claimant":325,"organization":320,"vendorReported":277},"productivity-gain","Productivity gain","vendor",{"slug":189,"title":327,"shortTitle":328,"definition":329,"status":9,"industries":330,"functions":331,"patterns":332,"audience":334,"autonomy":30,"adoptionStage":31,"segment":335,"evidenceCount":336,"publicEvidenceCount":337,"organizations":338,"bestGrade":226,"headline":228,"lastVerified":191,"indexable":277},"AI portfolio drift monitoring and rebalancing proposals","Drift and rebalancing","Continuous monitoring of every client portfolio against its mandate or model, which detects drift beyond agreed bands and prepares a tax aware, low turnover rebalancing proposal with its rationale for an advisor or portfolio manager to approve before any trade is placed.",[17,18],[310,22,285],[333,24,288,25],"anomaly-detection","back-office","middle-office",4,3,[234,339,202],"SimCorp",{"slug":190,"title":341,"shortTitle":342,"definition":343,"status":9,"industries":344,"functions":345,"patterns":347,"audience":29,"autonomy":289,"adoptionStage":314,"segment":32,"evidenceCount":315,"publicEvidenceCount":315,"organizations":349,"bestGrade":226,"headline":228,"lastVerified":192,"indexable":277},"AI knowledge assistant for wealth advisors and relationship managers","Advisor knowledge assistant","A conversational assistant that answers a wealth advisor's or relationship manager's questions in seconds from the firm's own research, house view, product documentation and policies, with every answer linked to the source document so the advisor can check it before using it with a client.",[17,18],[346,21,270],"knowledge-management",[348,273],"rag-knowledge-assistant",[317,293,294,234,295,350],"Yes Bank",{"indexable":277,"reasons":352},[],[354,360,365,372,379,385,392,398,403,410,417,422,429,435,441,446,453,459,465,471,477,483,489,493,498,505,512,517,522,529,535,541,547,552],{"id":142,"label":355,"issuer":356,"region":153,"url":357,"description":358,"useCases":359,"indexable":277},"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.",197,{"id":143,"label":361,"issuer":356,"region":153,"url":362,"description":363,"useCases":364,"indexable":277},"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":147,"label":366,"issuer":367,"region":368,"url":369,"description":370,"useCases":371,"indexable":277},"ISO/IEC 42001","ISO and IEC","global","https://www.iso.org/standard/81230.html","The international management system standard for AI.",110,{"id":373,"label":374,"issuer":375,"region":205,"url":376,"description":377,"useCases":378,"indexable":277},"nist-ai-rmf","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":380,"label":381,"issuer":356,"region":153,"url":382,"description":383,"useCases":384,"indexable":277},"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":386,"label":387,"issuer":388,"region":153,"url":389,"description":390,"useCases":391,"indexable":277},"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":144,"label":393,"issuer":394,"region":153,"url":395,"description":396,"useCases":397,"indexable":277},"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":145,"label":399,"issuer":162,"region":163,"url":400,"description":401,"useCases":402,"indexable":277},"MAS AI risk management guidelines","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":404,"label":405,"issuer":406,"region":163,"url":407,"description":408,"useCases":409,"indexable":277},"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":411,"label":412,"issuer":413,"region":368,"url":414,"description":415,"useCases":416,"indexable":277},"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":146,"label":418,"issuer":419,"region":205,"url":420,"description":421,"useCases":416,"indexable":277},"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":423,"label":424,"issuer":425,"region":153,"url":426,"description":427,"useCases":428,"indexable":277},"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":430,"label":431,"issuer":432,"region":368,"url":433,"description":434,"useCases":64,"indexable":277},"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":436,"label":437,"issuer":356,"region":153,"url":438,"description":439,"useCases":440,"indexable":277},"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":442,"label":443,"issuer":356,"region":153,"url":444,"description":445,"useCases":440,"indexable":277},"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":447,"label":448,"issuer":449,"region":205,"url":450,"description":451,"useCases":452,"indexable":277},"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":454,"label":455,"issuer":356,"region":153,"url":456,"description":457,"useCases":458,"indexable":277},"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":460,"label":461,"issuer":462,"region":205,"url":463,"description":464,"useCases":458,"indexable":277},"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":466,"label":467,"issuer":468,"region":368,"url":469,"description":470,"useCases":458,"indexable":277},"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":472,"label":473,"issuer":356,"region":153,"url":474,"description":475,"useCases":476,"indexable":277},"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":478,"label":479,"issuer":480,"region":205,"url":481,"description":482,"useCases":476,"indexable":277},"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":484,"label":485,"issuer":162,"region":163,"url":486,"description":487,"useCases":488,"indexable":277},"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":148,"label":490,"issuer":356,"region":153,"url":491,"description":492,"useCases":488,"indexable":277},"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":494,"label":495,"issuer":356,"region":153,"url":496,"description":497,"useCases":488,"indexable":277},"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":499,"label":500,"issuer":501,"region":153,"url":502,"description":503,"useCases":504,"indexable":277},"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":506,"label":507,"issuer":508,"region":205,"url":509,"description":510,"useCases":511,"indexable":277},"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":513,"label":514,"issuer":356,"region":153,"url":515,"description":516,"useCases":511,"indexable":277},"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":518,"label":519,"issuer":356,"region":153,"url":520,"description":521,"useCases":315,"indexable":277},"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.",{"id":523,"label":524,"issuer":525,"region":526,"url":527,"description":528,"useCases":291,"indexable":277},"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":530,"label":531,"issuer":532,"region":153,"url":533,"description":534,"useCases":336,"indexable":277},"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":536,"label":537,"issuer":538,"region":153,"url":539,"description":540,"useCases":336,"indexable":277},"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":542,"label":543,"issuer":544,"region":163,"url":545,"description":546,"useCases":337,"indexable":277},"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":548,"label":549,"issuer":356,"region":153,"url":550,"description":551,"useCases":337,"indexable":277},"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":553,"label":554,"issuer":555,"region":205,"url":556,"description":557,"useCases":337,"indexable":277},"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.",1790598297041]