[{"data":1,"prerenderedAt":555},["ShallowReactive",2],{"uc-portfolio-drift-monitoring-and-rebalancing":3,"uc-regulations":350},{"useCase":4,"evidence":193,"blitsAiDeployments":277,"benchmarks":278,"indicative":279,"related":282,"indexability":348,"includeUnpublished":199},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":16,"functions":19,"patterns":23,"channels":28,"audience":31,"autonomy":32,"adoptionStage":33,"segment":34,"problem":35,"problemStats":36,"howItWorks":37,"valueDrivers":38,"kpis":43,"indicativeValue":49,"macroEstimates":82,"feasibility":83,"implementation":96,"risk":139,"blitsAi":171,"faq":173,"related":183,"datePublished":188,"dateModified":188,"lastVerified":188,"changelog":189,"slug":192},"AI portfolio drift monitoring and rebalancing proposals","Drift and rebalancing","AI portfolio drift monitoring and rebalancing","AI flags portfolios that drift outside their bands and drafts rebalancing proposals for approval. SimCorp's Wealth Lens scores portfolios from 0.00 to 1.00.","published","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.",[12,13,14,15],"portfolio drift alerts","automated rebalancing proposals","mandate monitoring","model portfolio drift detection",[17,18],"wealth-and-asset-management","banking",[20,21,22],"operations","risk-management","analytics-and-reporting",[24,25,26,27],"anomaly-detection","agentic-workflow","prediction-and-scoring","content-generation",[29,30],"internal-tools","email","back-office","copilot","emerging","middle-office","Portfolios drift as markets move, cash comes in and clients make their own trades. After a strong\nrun in equities, a balanced mandate can hold more equity than its model allows, and a single stock\ncan grow into a concentration the client never agreed to. Where drift is checked on a calendar,\nquarterly or annually, portfolios can move outside their bands between reviews.\n\nA calendar check also spends time on portfolios that did not need attention. A sound proposal has to\naccount for taxes, costs, restrictions and client preferences, which takes time when it is done by\nhand for each account, and supervisors need a record of why a trade was or was not made.",[],"1. **Monitor continuously.** Holdings are compared daily with each portfolio's mandate or model,\n   restrictions and tolerance bands; breaches and near breaches are scored by size and urgency.\n2. **Prioritize.** Portfolios are ranked for attention, for example by a rebalancing score, so the\n   team sees the few that matter first.\n3. **Propose.** An optimizer builds a rebalancing proposal that respects taxes, costs, restrictions\n   and minimum trade sizes; the model writes a short rationale explaining the drift and the trades.\n4. **Approve.** The advisor or portfolio manager reviews, adjusts and approves the proposal; for\n   advisory accounts the client's consent is obtained before execution.\n5. **Execute and record.** Approved trades go to order management, and the trigger, proposal,\n   approval and executed trades are logged against the mandate.",[39,40,41,42],"risk-reduction","employee-productivity","compliance","customer-experience",[44,45,46,47,48],"time-saved-per-task","hours-saved","processing-time-reduction","cycle-time-days","error-reduction",{"referenceOrg":50,"inputs":51,"formula":77,"currency":78,"period":79,"resultLabel":80,"caveat":81},"A wealth manager with 20,000 managed or advised portfolios",[52,57,63,70],{"key":53,"label":54,"low":55,"high":55,"unit":53,"note":56},"portfolios","Portfolios monitored against a mandate or model",20000,"The reference firm.",{"key":58,"label":59,"low":60,"high":60,"unit":61,"note":62},"reviewsPerYear","Manual drift reviews per portfolio per year today",4,"reviews per year","Quarterly calendar review, an editorial assumption.",{"key":64,"label":65,"low":66,"high":67,"unit":68,"note":69},"minutesSaved","Minutes saved per review",10,20,"minutes per review","Editorial assumption, replace with your own. No public source on this page states a time saving.",{"key":71,"label":72,"low":73,"high":74,"unit":75,"note":76},"hourlyCost","Fully loaded cost per hour of portfolio managers and support staff",60,120,"USD per hour","Editorial assumption, replace with your own fully loaded cost.","portfolios * reviewsPerYear * minutesSaved / 60 * hourlyCost","USD","per year","Value of staff time released from manual drift reviews","Productivity only. It leaves out the effect on client outcomes (risk kept within mandate, tax savings), which depends on markets and is not measured by any source on this page, and the cost of the monitoring and optimization tools.",[],{"complexity":84,"complexityNote":85,"dataPrerequisites":86,"integrations":91},"medium","Monitoring against models is mature and often rules based already. Adding proposals needs clean tax lot data, restrictions and preferences per account, an optimizer, and an approval path into order management.",[87,88,89,90],"Daily holdings and cash per portfolio, with tax lots where relevant","Mandates, model portfolios, tolerance bands and restrictions per account","Client preferences such as exclusions and tax sensitivity","Cost and minimum trade size parameters",[92,93,94,95],"Portfolio management and accounting systems","Optimization or rebalancing engine","Order management system for approved trades","CRM for client communication and consent on advisory accounts",{"steps":97,"guardrails":113,"humanInTheLoop":119,"kpisToInstrument":120,"failureModes":126},[98,101,104,107,110],{"title":99,"detail":100},"Agree the bands and triggers","Define tolerance bands per mandate type and what counts as a breach, a near breach and an exception, with investment committee sign off.",{"title":102,"detail":103},"Monitor before you propose","Run daily drift detection and prioritization first; measure how many portfolios breach and how quickly they are handled.",{"title":105,"detail":106},"Add proposals with a rationale","Connect an optimizer for trades and use the language model only to explain the drift and the proposed trades in plain language for the approver and, where needed, the client.",{"title":108,"detail":109},"Keep execution behind approval","Route every proposal to a named approver with limits; for advisory accounts capture client consent. Automatic execution, if ever allowed, stays within narrow discretionary limits.",{"title":111,"detail":112},"Log for supervision","Store the trigger, proposal, approval, overrides and executed trades per portfolio so reviewers can see that each portfolio stayed within its mandate.",[114,115,116,117,118],"No trade without approval by an authorized person, and client consent on advisory accounts","Trades generated by the optimizer, not by the language model","Restrictions, exclusions and tax preferences enforced as hard constraints","Limits on turnover and trade size per proposal","Full log of trigger, proposal, approval and execution","Advisors or portfolio managers approve every proposal and can override it with a recorded reason; the investment committee owns models and bands; supervisors review exceptions and overrides.",[121,122,123,124,125],"Share of portfolios outside tolerance bands and median days to resolution","Proposals approved, modified or rejected, with reasons","Turnover and realized tax impact of approved rebalances","Time spent per review before and after","Mandate breaches found in supervisory review",[127,130,133,136],{"title":128,"detail":129},"Alert floods","Tight bands trigger constant alerts and staff start ignoring them. Tune bands and prioritize by size and urgency.",{"title":131,"detail":132},"Tax blind proposals","Rebalancing realizes gains the client did not need to. Use tax lot data and constraints in the optimizer.",{"title":134,"detail":135},"Rationale that does not match the trades","The narrative explains a different trade than the optimizer produced. Generate the text from the proposal data and check it.",{"title":137,"detail":138},"Silent execution creep","Approval becomes a click through. Monitor approval times and override rates and sample proposals.",{"euAiAct":140,"regulations":143,"guidance":151,"controls":164,"incidents":170},{"tier":141,"basis":142},"context-dependent","Monitoring portfolios and proposing trades for human approval is not listed in Annex III and is not a prohibited practice under Article 5, so the tier turns on the firm's role under Article 50. A firm that builds or brands the rationale writer in house is a provider under Article 50(2) and must mark the generated text in a machine readable format: drafting a rationale for the drift and the proposed trades goes beyond the exemption for an assistive function for standard editing, so for that firm the tier is limited. Article 50(1) also applies once the rationale reaches the client, as this page's own implementation step allows. A firm that only deploys a third party feature for internal approver use has no Article 50 duty, and for that firm the tier is minimal. Investment conduct rules such as MiFID II suitability and best execution still apply to the resulting trades.",[144,145,146,147,148,149,150],"eu-ai-act","gdpr","dora","mas-ai-risk-management","apra-cps-230","iso-42001","mifid-ii",[152,158],{"title":153,"issuer":154,"region":155,"url":156,"note":157},"ESMA public statement on the use of AI in the provision of retail investment services","European Securities and Markets Authority","europe","https://www.esma.europa.eu/sites/default/files/2024-05/ESMA35-335435667-5924__Public_Statement_on_AI_and_investment_services.pdf","Covers AI used to manage and rebalance client portfolios and expects heightened diligence on suitability in portfolio management.",{"title":159,"issuer":160,"region":161,"url":162,"note":163},"Artificial Intelligence (AI) 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 for AI and generative AI model risk management observed in a 2024 thematic review of banks, covering governance and oversight, key risk management systems and processes, and the development and deployment of AI.",[165,166,167,168,169],"Tolerance bands and models approved and version controlled by the investment committee","Monitoring and optimization tools inventoried with owners and validation","Approval limits per role and client consent capture for advisory accounts","Audit trail from trigger to executed trade per portfolio","Periodic review of overrides and exceptions",[],{"howToBuild":172},"On Blits.ai monitoring runs as **agentic tasks**: condition triggered checks (\"when a portfolio\ndrifts beyond its band\") with scheduled rechecks, calling the firm's portfolio and optimization\nsystems through **custom functions** (REST or SQL) or a **SQL knowledge base**. An **agentic\nworkflow** then collects the optimizer's proposal and an **AI agent** writes the rationale with\n**structured output** tied to the proposed trades.\n\nEvery proposal pauses for **human in the loop** approval before anything reaches order management\n(the configurable confirmation threshold is set so that no proposal skips it), and the **tool\nexecution policy** keeps order placement outside the agent's allowed tools unless explicitly\npermitted. The workflow's **audit trail** records each trigger, proposal and decision, notices go\nto approvers by **email** or **Microsoft Teams**, and **monitors** run scheduled health checks on\nthe agents and alert the team when they fail.",[174,177,180],{"question":175,"answer":176},"Is this already automated today?","Rules based rebalancing is already automated in digital advice: Vanguard Digital Advisor, for example, rebalances when a portfolio drifts more than 5% from its recommended allocation. The AI steps in the evidence here sit on top of that: ranking large books for attention (SimCorp's Wealth Lens tool scores each portfolio from 0.00 to 1.00 for rebalancing) and drafting plain language talking points, as BlackRock announced its Aladdin Wealth Auto Commentary would do for Morgan Stanley advisors to help them identify issues such as portfolio overweights.",{"question":178,"answer":179},"Should the AI place trades on its own?","In advisory books, no: trades need advisor approval and client consent. Even in discretionary mandates, keep execution behind an authorized approver or narrow limits and log every decision.",{"question":181,"answer":182},"What about claims of extra returns or tax savings?","Measure them on your own books against a control before relying on them; no source on this page publishes an independent figure for extra returns or tax savings. What you can measure directly is the share of portfolios outside their bands, the time to resolve a breach and the completeness of the record from trigger to trade.",[184,185,186,187],"portfolio-reporting-and-commentary","suitability-assessment-assistant","next-best-action-for-advisors","goal-based-financial-planning-assistant","2026-09-27",[190],{"date":188,"note":191},"First published","portfolio-drift-monitoring-and-rebalancing",[194,225,253],{"title":195,"useCases":196,"organization":197,"vendors":202,"summary":205,"stage":206,"year":207,"channels":208,"languages":209,"metrics":211,"outcomeDisclosed":199,"sources":212,"verification":220,"grade":222,"id":223,"organizationSlug":224},"Vanguard: Digital Advisor goal based portfolios with automatic rebalancing",[187,192,185],{"name":198,"anonymized":199,"country":200,"region":201,"industry":17},"Vanguard",false,"US","north-america",[203],{"name":198,"role":204},"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,[],[210],"en",[],[213,216],{"url":214,"title":215,"publisher":198},"https://investor.vanguard.com/advice/digital-advisor","Vanguard Digital Advisor",{"url":217,"title":218,"publisher":198,"date":219},"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":221,"checkedAt":188},"source-verified","B","vanguard-digital-advisor",null,{"title":226,"useCases":227,"organization":228,"vendors":230,"summary":234,"stage":235,"year":236,"channels":237,"languages":238,"metrics":239,"outcomeDisclosed":199,"sources":240,"verification":249,"grade":250,"id":251,"organizationSlug":252},"Morgan Stanley: BlackRock Aladdin Wealth Auto Commentary in its Portfolio Risk Platform",[184,192,185],{"name":229,"anonymized":199,"country":200,"region":201,"industry":17},"Morgan Stanley",[231],{"name":232,"role":233},"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,[29],[210],[],[241,245],{"url":242,"title":243,"publisher":232,"date":244},"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":246,"title":247,"publisher":248,"date":244},"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":221,"checkedAt":188},"C","morgan-stanley-aladdin-auto-commentary","morgan-stanley",{"title":254,"useCases":255,"organization":256,"vendors":260,"summary":263,"stage":235,"year":264,"channels":265,"languages":266,"metrics":267,"outcomeDisclosed":199,"sources":268,"verification":274,"grade":275,"id":276,"organizationSlug":224},"SimCorp: Wealth Vision and Wealth Lens rebalancing scores",[192],{"name":257,"anonymized":199,"country":258,"region":155,"industry":259},"SimCorp","DK","technology",[261],{"name":262,"role":233},"Microsoft","SimCorp, an investment management software provider that uses Azure Machine Learning as its main AI platform and Semantic Kernel to build its AI solutions, describes Wealth Vision: it gives a portfolio manager a list of portfolios to rebalance, and its Wealth Lens tool scores each portfolio between 0.00 and 1.00, where 1.00 marks a prime candidate for rebalancing. This is a vendor product description on a Microsoft blog; no named client deployment or outcome is published.",2024,[29],[210],[],[269],{"url":270,"title":271,"publisher":272,"date":273},"https://devblogs.microsoft.com/semantic-kernel/customer-case-study-simcorps-ai-journey-with-semantic-kernel/","Customer Case Study: SimCorp's AI Journey with Semantic Kernel","Microsoft Developer Blogs","2024-07-24",{"level":221,"checkedAt":188},"D","simcorp-wealth-lens-rebalancing",1,[],{"low":280,"high":281},800000,3200000,[283,299,313,338],{"slug":184,"title":284,"shortTitle":285,"definition":286,"status":9,"industries":287,"functions":288,"patterns":290,"audience":31,"autonomy":32,"adoptionStage":293,"segment":34,"evidenceCount":294,"publicEvidenceCount":295,"organizations":296,"bestGrade":250,"headline":224,"lastVerified":188,"indexable":298},"AI generated client portfolio reports and commentary","Portfolio commentary","AI that drafts each client's periodic portfolio commentary and report narrative (performance, attribution, what drove returns, positioning and outlook) in plain language and in the client's language, where every figure comes from the portfolio system of record and a reviewer approves the text before delivery.",[17,18],[22,289,20],"customer-service",[27,291,292],"summarization","translation","early-adopters",3,2,[229,297],"Quilter",true,{"slug":185,"title":300,"shortTitle":301,"definition":302,"status":9,"industries":303,"functions":304,"patterns":307,"audience":309,"autonomy":32,"adoptionStage":33,"segment":310,"evidenceCount":295,"publicEvidenceCount":295,"organizations":311,"bestGrade":222,"headline":224,"lastVerified":312,"indexable":298},"AI assistant for investment suitability assessment and reports","Suitability assessment","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.",[17,18],[305,306,21],"regulatory-compliance","sales",[25,27,308],"classification-and-routing","employee-facing","front-office",[229,198],"2026-09-26",{"slug":186,"title":314,"shortTitle":315,"definition":316,"status":9,"industries":317,"functions":318,"patterns":320,"audience":309,"autonomy":322,"adoptionStage":293,"segment":310,"evidenceCount":323,"publicEvidenceCount":323,"organizations":324,"bestGrade":222,"headline":329,"lastVerified":188,"indexable":298},"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],[306,319,22],"marketing",[321,26,27],"recommendation-and-personalization","assist",5,[325,326,327,229,328],"CIMB Niaga","Citi","JPMorgan Chase","UBS",{"kpi":330,"label":331,"unit":332,"n":277,"nUpTo":333,"kind":334,"value":335,"qualifier":336,"claimant":337,"organization":328,"vendorReported":199},"employee-adoption","Employee adoption","percent",0,"reported",80,"exact","organization",{"slug":187,"title":339,"shortTitle":340,"definition":341,"status":9,"industries":342,"functions":343,"patterns":345,"audience":309,"autonomy":32,"adoptionStage":33,"segment":310,"evidenceCount":295,"publicEvidenceCount":295,"organizations":347,"bestGrade":222,"headline":224,"lastVerified":188,"indexable":298},"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],[306,289,344],"product-and-pricing",[346,27,25],"conversational-agent",[325,198],{"indexable":298,"reasons":349},[],[351,357,362,369,376,381,388,395,400,406,412,418,425,432,438,443,450,456,462,468,474,480,485,489,494,501,508,513,519,526,532,538,544,549],{"id":144,"label":352,"issuer":353,"region":155,"url":354,"description":355,"useCases":356,"indexable":298},"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":145,"label":358,"issuer":353,"region":155,"url":359,"description":360,"useCases":361,"indexable":298},"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":149,"label":363,"issuer":364,"region":365,"url":366,"description":367,"useCases":368,"indexable":298},"ISO/IEC 42001","ISO and IEC","global","https://www.iso.org/standard/81230.html","The international management system standard for AI.",110,{"id":370,"label":371,"issuer":372,"region":201,"url":373,"description":374,"useCases":375,"indexable":298},"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":146,"label":377,"issuer":353,"region":155,"url":378,"description":379,"useCases":380,"indexable":298},"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":382,"label":383,"issuer":384,"region":155,"url":385,"description":386,"useCases":387,"indexable":298},"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":389,"label":390,"issuer":391,"region":155,"url":392,"description":393,"useCases":394,"indexable":298},"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":147,"label":396,"issuer":160,"region":161,"url":397,"description":398,"useCases":399,"indexable":298},"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":148,"label":401,"issuer":402,"region":161,"url":403,"description":404,"useCases":405,"indexable":298},"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":407,"label":408,"issuer":409,"region":365,"url":410,"description":411,"useCases":67,"indexable":298},"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":413,"label":414,"issuer":415,"region":201,"url":416,"description":417,"useCases":67,"indexable":298},"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":419,"label":420,"issuer":421,"region":155,"url":422,"description":423,"useCases":424,"indexable":298},"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":426,"label":427,"issuer":428,"region":365,"url":429,"description":430,"useCases":431,"indexable":298},"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":353,"region":155,"url":435,"description":436,"useCases":437,"indexable":298},"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":353,"region":155,"url":441,"description":442,"useCases":437,"indexable":298},"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":444,"label":445,"issuer":446,"region":201,"url":447,"description":448,"useCases":449,"indexable":298},"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":451,"label":452,"issuer":353,"region":155,"url":453,"description":454,"useCases":455,"indexable":298},"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":457,"label":458,"issuer":459,"region":201,"url":460,"description":461,"useCases":455,"indexable":298},"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":463,"label":464,"issuer":465,"region":365,"url":466,"description":467,"useCases":455,"indexable":298},"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":469,"label":470,"issuer":353,"region":155,"url":471,"description":472,"useCases":473,"indexable":298},"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":475,"label":476,"issuer":477,"region":201,"url":478,"description":479,"useCases":473,"indexable":298},"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":481,"label":482,"issuer":160,"region":161,"url":483,"description":484,"useCases":66,"indexable":298},"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":150,"label":486,"issuer":353,"region":155,"url":487,"description":488,"useCases":66,"indexable":298},"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":490,"label":491,"issuer":353,"region":155,"url":492,"description":493,"useCases":66,"indexable":298},"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":495,"label":496,"issuer":497,"region":155,"url":498,"description":499,"useCases":500,"indexable":298},"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":502,"label":503,"issuer":504,"region":201,"url":505,"description":506,"useCases":507,"indexable":298},"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":509,"label":510,"issuer":353,"region":155,"url":511,"description":512,"useCases":507,"indexable":298},"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":514,"label":515,"issuer":353,"region":155,"url":516,"description":517,"useCases":518,"indexable":298},"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":520,"label":521,"issuer":522,"region":523,"url":524,"description":525,"useCases":323,"indexable":298},"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":527,"label":528,"issuer":529,"region":155,"url":530,"description":531,"useCases":60,"indexable":298},"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":533,"label":534,"issuer":535,"region":155,"url":536,"description":537,"useCases":60,"indexable":298},"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":539,"label":540,"issuer":541,"region":161,"url":542,"description":543,"useCases":294,"indexable":298},"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":545,"label":546,"issuer":353,"region":155,"url":547,"description":548,"useCases":294,"indexable":298},"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":550,"label":551,"issuer":552,"region":201,"url":553,"description":554,"useCases":294,"indexable":298},"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.",1790598303065]