[{"data":1,"prerenderedAt":596},["ShallowReactive",2],{"uc-contract-obligation-tracking-agent":3,"uc-regulations":380},{"useCase":4,"evidence":202,"blitsAiDeployments":272,"benchmarks":273,"indicative":274,"related":277,"indexability":378,"includeUnpublished":208},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":17,"functions":22,"patterns":26,"channels":31,"audience":34,"autonomy":35,"adoptionStage":36,"problem":37,"problemStats":38,"howItWorks":39,"valueDrivers":40,"kpis":45,"indicativeValue":49,"macroEstimates":90,"feasibility":91,"implementation":104,"risk":150,"blitsAi":179,"faq":181,"related":194,"datePublished":197,"dateModified":197,"lastVerified":197,"changelog":198,"slug":201},"AI agent for contract obligation tracking and compliance","Contract obligation tracking","AI contract obligation tracking agent","AI extracts renewal dates and terms from signed contracts and reminds the owner ahead of a deadline. LinkSquares customers Haynes International and ADARx use it.","published","Contract obligation tracking uses AI to extract commitments and deadlines from signed contracts, keep them in one register and alert the owner before a deadline is missed. The commitments include service levels, renewal and notice dates, price escalators, audit rights and delivery milestones.",[12,13,14,15,16],"contract obligation management AI","renewal and milestone tracking AI","post signature contract monitoring","obligation extraction and alerts","contract compliance tracking assistant",[18,19,20,21],"cross-industry","technology","professional-services","manufacturing",[23,24,25],"procurement","legal","finance-and-accounting",[27,28,29,30],"document-processing","rag-knowledge-assistant","agentic-workflow","summarization",[32,33],"internal-tools","email","back-office","supervised-agent","emerging","A signed contract carries a list of commitments someone has to act on, often years later.\nService levels, renewal notice windows, price escalators, audit rights, delivery milestones and\nexit terms all need an owner, and the people who negotiated the deal have often moved to other\nwork by the time a date comes due. In a large portfolio an obligation buried deep in one\nagreement is easy to overlook.\n\nA contract repository that only stores documents does not solve this, because someone still has\nto read every agreement to know what is owed and when.\n\nLinkSquares describes customers using AI this way. At Haynes International, a US alloy maker,\nthe AI extracts data from digitized contracts and the team keeps track of termination and\nrenewal dates with timely alerts. At ADARx Pharmaceuticals, a US biotechnology company,\nautomated reminders of upcoming renewals and expirations help avoid accidental renewals. OmniTRAX,\na US railroad operator, used LinkSquares to extract terms, dates and figures from its signed\nagreements to track its obligations; its case study does not describe alerts.",[],"1. **Ingest signed contracts and amendments.** Executed agreements are loaded from the contract\n   repository, signature platform or email, linked to their amendments so the effective terms are used rather than only the original text.\n2. **Extract every ongoing obligation.** The assistant pulls out renewal and notice dates, service\n   levels, price changes, audit and reporting rights, delivery milestones and exit terms into a\n   structured record, citing the clause each one came from.\n3. **Build the portfolio register.** Every obligation gets an owner, a due date and a status, kept\n   in one place instead of scattered across individual contract files.\n4. **Alert ahead of the deadline.** The assistant reminds the accountable owner ahead of\n   a renewal notice window, an SLA reporting date or a milestone, with enough lead time to act,\n   and escalates when a reminder goes unanswered.\n5. **Report on the whole portfolio.** Compliance, procurement and legal get a live view of\n   obligations by status, contract or business unit, instead of a manual sweep before an audit.",[41,42,43,44],"risk-reduction","compliance","cost-to-serve","employee-productivity",[46,47,48],"processing-time-reduction","quality-score-uplift","automation-rate",{"referenceOrg":50,"inputs":51,"formula":85,"currency":86,"period":87,"resultLabel":88,"caveat":89},"An organization managing 3,000 active supplier and customer contracts",[52,57,64,71,78],{"key":53,"label":54,"low":55,"high":55,"unit":53,"note":56},"contracts","Active contracts in the portfolio",3000,"The reference organization. Replace with your own contract count.",{"key":58,"label":59,"low":60,"high":61,"unit":62,"note":63},"obligationsPerContract","Tracked obligations per contract",5,15,"obligations per contract","Editorial assumption; complex commercial or outsourcing contracts carry many more than a simple purchase agreement.",{"key":65,"label":66,"low":67,"high":68,"unit":69,"note":70},"missedObligationRate","Share of obligations missed or actioned late without automated tracking",0.02,0.05,"fraction of obligations","Editorial assumption, replace with your own experience. Assumes a fully manual process, without structured extraction or a portfolio wide register, misses or acts late on a small but real share of obligations.",{"key":72,"label":73,"low":74,"high":75,"unit":76,"note":77},"shareOfMissesAvoided","Share of currently missed obligations the tool catches",0.3,0.6,"fraction of misses avoided","Editorial assumption, replace with your own; assumes the tool catches a meaningful share of the currently missed obligations but not all of them. Do not model this as 1.0: no cited evidence shows any deployment avoiding every missed obligation.",{"key":79,"label":80,"low":81,"high":82,"unit":83,"note":84},"costPerMissedObligation","Average cost of a missed obligation (penalty, lost rebate, SLA credit, renegotiation)",500,5000,"USD per missed obligation","Editorial assumption. Replace with your own exposure per missed obligation.","contracts * obligationsPerContract * missedObligationRate * shareOfMissesAvoided * costPerMissedObligation","USD","per year","Estimated exposure from missed contractual obligations avoided","A rough exposure estimate, not a guaranteed saving; it depends heavily on the missed obligation rate, the share of misses the tool actually catches, and the cost per miss you put in. It leaves out the cost of loading and clause tagging the existing contract estate, the platform cost, and obligations whose impact cannot be priced, such as reputational or relationship harm.",[],{"complexity":92,"complexityNote":93,"dataPrerequisites":94,"integrations":99},"medium","Extraction from clean digital contracts is well understood. Amendments have to be linked to their master agreement so the tracked obligation reflects the current terms, and procurement, legal, finance and the business have to agree who owns each obligation.",[95,96,97,98],"A contract repository with executed agreements and their amendments in one place","An owner assigned to each contract or obligation category","The list of obligation types the organization wants tracked (SLAs, renewals, price terms, audit rights, milestones)","Past examples of missed obligations, if available, to calibrate what is worth tracking",[100,101,102,103],"Contract lifecycle management or document management system","ERP or finance system, for price escalators, invoicing and revenue recognition dates","Email and calendar for reminders and escalations","Electronic signature platform, to pick up newly executed agreements automatically",{"steps":105,"guardrails":124,"humanInTheLoop":130,"kpisToInstrument":131,"failureModes":137},[106,109,112,115,118,121],{"title":107,"detail":108},"Start with the obligations that cost the most when missed","Renewal and notice dates and SLA reporting obligations are usually the highest value place to start, because missing them has a clear, often contractual, financial consequence.",{"title":110,"detail":111},"Extract with a citation, then have an owner confirm","Extract each obligation with a link back to the clause it came from, and have the assigned owner confirm it once, rather than trusting extraction silently on the full back book.",{"title":113,"detail":114},"Link amendments to their master agreement","An obligation extracted from the original contract but changed by a later amendment is wrong. Track amendments against their master so the tracked terms are the effective ones.",{"title":116,"detail":117},"Assign an owner to each obligation","A contract owner is not always the right person to act on a specific obligation. Assign owners at the obligation level so reminders reach someone who can actually do something.",{"title":119,"detail":120},"Alert with enough lead time to act","Always alert against the renewal notice or reporting window the specific contract states; alert ahead of the deadline, and escalate automatically if the first reminder goes unanswered.",{"title":122,"detail":123},"Report status across the whole portfolio","Give compliance and procurement leadership a live view of obligation status across the whole portfolio, so a register is already in place when an audit asks for one.",[125,126,127,128,129],"Every extracted obligation cites the clause and, where relevant, the amendment it came from","A named owner confirms newly extracted obligations before they drive automated reminders","The assistant does not renegotiate, waive or accept a change to an obligation; it tracks and alerts only","Escalation rules are explicit, so an unanswered reminder always reaches a second person","Contract data stays in region and is not used to train external models","Contract and obligation owners confirm what the assistant extracts and decide what to do about every alert. Legal or procurement leadership review missed or late obligations periodically to find patterns, such as a clause type that is consistently missed, and fix the process rather than only the individual case.",[132,133,134,135,136],"Obligations tracked and confirmed by an owner, as a share of the contract estate","Obligation compliance rate: obligations actioned on time divided by all obligations due","Renewal notice windows missed, before and after","Time from contract execution to the obligations being live in the register","Escalations triggered and time to resolution",[138,141,144,147],{"title":139,"detail":140},"Amendments ignored","The assistant extracts from the master agreement and misses a later amendment that changed a date or a term. Link every amendment to its master and extract the effective terms.",{"title":142,"detail":143},"Alerts nobody owns","A reminder goes to a mailbox nobody checks, or to whoever negotiated the deal and has since left the role. Assign and keep current an owner per obligation, not per contract.",{"title":145,"detail":146},"Confident extraction from bad scans","Poor OCR on older contracts yields a wrong date that looks authoritative. Flag low confidence fields and route them to a person before they drive an alert.",{"title":148,"detail":149},"A register that only compliance ever opens","The obligation register becomes a compliance artifact nobody in the business consults. Put the alerts in the tools owners already use (email, chat) rather than only a dashboard.",{"euAiAct":151,"regulations":154,"guidance":160,"controls":173,"incidents":178},{"tier":152,"basis":153},"minimal","Tracking contractual obligations and sending reminders is not among the Annex III high risk uses; an internal tool that extracts terms and alerts an owner makes no decision about a natural person's access to a service, employment or credit, so it is minimal risk under the EU AI Act, with the Article 4 duty to give staff who operate it appropriate AI literacy. The DORA and APRA CPS 230 entries below apply only when the deploying organization is itself a regulated bank, insurer or other financial entity; for other industries they do not apply.",[155,156,157,158,159],"dora","apra-cps-230","gdpr","eu-ai-act","iso-42001",[161,167],{"title":162,"issuer":163,"region":164,"url":165,"note":166},"Digital Operational Resilience Act (Regulation (EU) 2022\u002F2554), Articles 28(3) and 30","European Union","europe","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2022\u002F2554\u002Foj","Article 28(3) requires financial entities to keep and update a register of information on their ICT third party contractual arrangements, and Article 30 sets the key contractual provisions those arrangements must include; an obligation tracker should hold both as structured data.",{"title":168,"issuer":169,"region":170,"url":171,"note":172},"Operational risk management (CPS 230)","Australian Prudential Regulation Authority","asia-pacific","https:\u002F\u002Fwww.apra.gov.au\u002Foperational-risk-management","Requires APRA regulated entities (authorised deposit taking institutions, superannuation trustees and insurers) to submit a register of material service provider arrangements under CPS 230 paragraph 51; the CPS 230 standard itself, not this landing page, sets out the required content of the underlying formal agreements.",[174,175,176,177],"Inventory entry for the assistant with an accountable owner in legal or procurement","Sampled accuracy checks on extracted obligations, kept as evidence","Access control on contract data by business unit and sensitivity","Escalation policy for unanswered alerts, reviewed periodically",[],{"howToBuild":180},"On Blits.ai this is an **AI agent** with a **knowledge base** holding the contract estate,\ningested through document upload or **incoming email as a knowledge source**, with document\ningestion reading PDF, DOCX and image contracts. An **agentic workflow** extracts obligations\nwith **structured output**, links amendments to their master agreement, and writes the\nobligation register through **custom functions** (REST calls) or connectors from the\n**integration catalog** (for example SAP or Oracle); a contract lifecycle management system is\nreached through custom functions, and **DocuSign** is a listed connector for picking up newly\nexecuted agreements.\n\nA scheduled **agentic workflow** (or an **agentic task** with scheduled rechecks) runs the\nreminder and escalation logic, notifying owners through **email** or **Microsoft Teams**, with\nunanswered alerts escalating to a second owner. **Guardrails** provide input and output checks\non the assistant's interactions, including a platform default that blocks prompt injection\nattempts, **automatic PII masking at the gateway** limits personal data exposure in those\ninteractions, and **run history with a full audit trail** keeps every extraction, confirmation\nand alert. **Test suites** check\nextraction accuracy on a reference set of contracts and amendments after every change. The\nplatform is model agnostic and offers EU and UAE data residency.",[182,185,188,191],{"question":183,"answer":184},"How is this different from AI contract review?","Contract review happens before signature: it extracts terms from a proposed contract and flags deviations from a playbook so a buyer or lawyer can negotiate. Obligation tracking happens after signature: it keeps the commitments already agreed to in a live register and alerts the owner before a deadline is missed. Many organizations eventually want both, often from the same contract data.",{"question":186,"answer":187},"What results have organizations reported?","No measured outcome such as a percentage or a dollar figure yet. Three named organizations are recorded, all through LinkSquares case studies. LinkSquares says Haynes International, an alloy maker, can keep track of termination and renewal dates with timely alerts, and that ADARx Pharmaceuticals, a biotechnology company, avoids accidental renewals with automated reminders of upcoming renewals and expirations. OmniTRAX, a railroad operator, extracts terms, dates and figures from its signed agreements to track its obligations; its case study does not describe alerts. None of the three states a before and after number, so none is recorded on this page.",{"question":189,"answer":190},"Does the AI decide what to do about a missed obligation?","No. It extracts, tracks and alerts; the assigned owner decides what to do, whether that is exercising a renewal right, escalating a service level breach, or renegotiating a term. The assistant does not renegotiate, waive or accept changes on the organization's behalf.",{"question":192,"answer":193},"Why do banks and insurers care about this beyond cost control?","Rules such as DORA in the EU and CPS 230 in Australia, which apply only to regulated financial entities, require a register of arrangements with material or ICT third party service providers, with specific information the supervisor can request. An obligation tracker that already holds structured, current data on those arrangements makes that register easier to produce and keep accurate.",[195,196],"procurement-contract-review","lease-abstraction","2026-10-13",[199],{"date":197,"note":200},"First published","contract-obligation-tracking-agent",[203,233,252],{"title":204,"useCases":205,"organization":206,"vendors":212,"summary":216,"stage":217,"year":218,"channels":219,"languages":220,"metrics":222,"outcomeDisclosed":223,"sources":224,"verification":228,"grade":230,"id":231,"organizationSlug":232},"Haynes International: LinkSquares tracks renewal dates with timely alerts",[201],{"name":207,"anonymized":208,"country":209,"region":210,"industry":21,"wikidata":211},"Haynes International",false,"US","north-america","Q1591976",[213],{"name":214,"role":215},"LinkSquares","platform","Haynes International, a US maker of corrosion resistant and high temperature alloys, uses LinkSquares to scan, analyze and organize its signed contracts with AI. According to LinkSquares, the AI extracts data from the digitized files so the entire portfolio can be searched and tracked in seconds, and the team can keep track of termination and renewal dates with timely alerts.","production",2025,[32],[221],"en",[],true,[225],{"url":226,"title":227,"publisher":214},"https:\u002F\u002Fwww.linksquares.com\u002Fcustomers\u002Fhaynes-international\u002F","How Haynes International Uses LinkSquares",{"level":229,"checkedAt":197},"source-verified","C","haynes-international-linksquares-renewal-tracking",null,{"title":234,"useCases":235,"organization":236,"vendors":239,"summary":241,"stage":217,"year":242,"channels":243,"languages":244,"metrics":245,"outcomeDisclosed":223,"sources":246,"verification":250,"grade":230,"id":251,"organizationSlug":232},"ADARx: LinkSquares extracts contract data and sends automated renewal reminders",[201],{"name":237,"anonymized":208,"country":209,"region":210,"industry":238},"ADARx Pharmaceuticals","pharma-and-life-sciences",[240],{"name":214,"role":215},"ADARx Pharmaceuticals, a San Diego biotechnology company designing RNA targeting therapeutics, uses LinkSquares Analyze for its signed contracts. According to LinkSquares, the AI powered data extraction lets the company run key reports across its whole portfolio and avoid costly, accidental renewals through automated reminders of all upcoming renewals and expirations.",2022,[32],[221],[],[247],{"url":248,"title":249,"publisher":214},"https:\u002F\u002Fwww.linksquares.com\u002Fcustomers\u002Fadarx\u002F","ADARx Uses LinkSquares to Successfully Scale Their Legal Function",{"level":229,"checkedAt":197},"adarx-linksquares-automated-renewal-reminders",{"title":253,"useCases":254,"organization":255,"vendors":259,"summary":261,"stage":217,"year":262,"channels":263,"languages":264,"metrics":265,"outcomeDisclosed":223,"sources":266,"verification":270,"grade":230,"id":271,"organizationSlug":232},"OmniTRAX: LinkSquares extracts contract metadata for compliance and expiry tracking",[201],{"name":256,"anonymized":208,"country":209,"region":210,"industry":257,"wikidata":258},"OmniTRAX","logistics-and-transportation","Q2023477",[260],{"name":214,"role":215},"OmniTRAX, a US short line railroad and transportation management company that contracts with government entities, from large federal agencies to small county governments, under various compliance standards, adopted LinkSquares in November 2021 to replace a manual process for tracking its contractual obligations and the quarterly financial reports many of those agencies require. LinkSquares automatically identifies and extracts more than one hundred pieces of metadata, including terms, dates and figures, from thousands of signed agreements, some dating back to the 1940s, and its reporting capabilities let the team identify various compliance requirements.",2021,[32],[221],[],[267],{"url":268,"title":269,"publisher":214},"https:\u002F\u002Fwww.linksquares.com\u002Fcustomers\u002Fomnitrax\u002F","OmniTRAX Leverages LinkSquares to Accelerate Their Drafting and Compliance Processes",{"level":229,"checkedAt":197},"omnitrax-linksquares-compliance-metadata-extraction",0,[],{"low":275,"high":276},45000,6750000,[278,305,336,352],{"slug":195,"title":279,"shortTitle":280,"definition":281,"status":9,"industries":282,"functions":286,"patterns":287,"audience":289,"autonomy":290,"adoptionStage":291,"evidenceCount":292,"publicEvidenceCount":293,"organizations":294,"bestGrade":303,"headline":232,"lastVerified":304,"indexable":223},"AI assistant for procurement and supplier contract review","Procurement and contract review","Procurement and contract review is an assistant that reads supplier contracts and proposals, for procurement and vendor management teams. It extracts the key terms, flags deviations from the organization's standard positions, drafts requests for proposal and evaluation matrices, and prepares negotiation positions, with a procurement or legal owner approving every conclusion.",[18,283,284,285,21],"banking","government","retail-and-ecommerce",[23,24,25],[27,28,288,29],"content-generation","employee-facing","copilot","early-adopters",10,9,[295,296,297,298,299,300,301,302],"Bridgewater Associates","General Services Administration","Administration for Children and Families","Internal Revenue Service","Pension Benefit Guaranty Corporation","Pacific Northwest National Laboratory","Technology Common Services Center","Walmart","B","2026-09-27",{"slug":196,"title":306,"shortTitle":307,"definition":308,"status":9,"industries":309,"functions":311,"patterns":313,"audience":289,"autonomy":35,"adoptionStage":291,"segment":314,"evidenceCount":292,"publicEvidenceCount":292,"organizations":315,"bestGrade":230,"headline":326,"lastVerified":335,"indexable":223},"AI lease abstraction for commercial real estate","Lease abstraction","AI lease abstraction reads a commercial lease, amendment or letter of intent and pulls out the key terms into structured data for property owners, occupiers and brokerages. The terms include parties, dates, rent, escalations, options and renewal notices, so nobody has to retype every clause by hand into the lease administration and portfolio systems.",[310],"real-estate",[312,24],"operations",[27,29,28],"lease-administration",[316,317,318,319,320,321,322,323,324,325],"American Dream","Bradken","Claroty","Continental Realty Corporation","Cushman & Wakefield","Derwent London","JLL (Jones Lang LaSalle)","Spear Street Capital","Taboola","Urban Renaissance Group",{"kpi":327,"label":328,"unit":329,"n":330,"nUpTo":272,"kind":331,"value":332,"qualifier":333,"claimant":334,"organization":318,"vendorReported":223},"productivity-gain","Productivity gain","percent",2,"reported",90,"exact","vendor","2026-09-28",{"slug":337,"title":338,"shortTitle":339,"definition":340,"status":9,"industries":341,"functions":343,"patterns":345,"audience":34,"autonomy":35,"adoptionStage":291,"evidenceCount":347,"publicEvidenceCount":347,"organizations":348,"bestGrade":303,"headline":232,"lastVerified":304,"indexable":223},"procurement-spend-classification","AI spend classification and spend analytics for procurement","Spend classification","Spend classification is AI that reads purchase orders, invoices, card transactions and contracts and assigns each line of spend to a category, for procurement teams. It assigns spend to the organization's taxonomy and to the right supplier, so procurement can see what is bought, from whom and where to consolidate or negotiate.",[18,284,21,342],"healthcare",[23,25,344],"analytics-and-reporting",[346,27,30],"classification-and-routing",4,[349,298,350,351],"U.S. General Services Administration","U.S. Department of Agriculture","Veterans Health Administration",{"slug":353,"title":354,"shortTitle":355,"definition":356,"status":9,"industries":357,"functions":360,"patterns":362,"audience":289,"autonomy":290,"adoptionStage":291,"segment":364,"evidenceCount":365,"publicEvidenceCount":366,"organizations":367,"bestGrade":303,"headline":374,"lastVerified":304,"indexable":223},"deal-sourcing-and-due-diligence-assistant","AI assistant for deal sourcing and M&A due diligence","Deal sourcing and due diligence","AI deal sourcing and due diligence is an AI assistant that screens the market for acquisition or investment targets and speeds up due diligence for a deal team. It builds company profiles, reads data room documents, extracts key terms and risks, and drafts the investment or diligence memo, for the team to verify and decide.",[358,359,20],"capital-markets","wealth-and-asset-management",[344,24,361],"risk-management",[27,30,28,29,363],"prediction-and-scoring","front-office",7,6,[368,369,370,371,372,373],"Datasite","EQT","Freshfields","Ice Miller","Orrick","Rogo",{"kpi":327,"label":328,"unit":329,"n":272,"nUpTo":375,"kind":331,"value":376,"qualifier":377,"claimant":334,"organization":368,"vendorReported":223},1,80,"up-to",{"indexable":223,"reasons":379},[],[381,386,391,398,405,412,416,423,430,434,441,447,453,460,467,473,479,485,492,497,502,509,515,522,527,532,537,542,549,554,561,566,572,578,585,590],{"id":158,"label":382,"issuer":163,"region":164,"url":383,"description":384,"useCases":385,"indexable":223},"EU AI Act","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2024\u002F1689\u002Foj","Regulation (EU) 2024\u002F1689: risk based rules for AI systems, with obligations for high risk systems listed in Annex III and transparency duties under Article 50.",275,{"id":157,"label":387,"issuer":163,"region":164,"url":388,"description":389,"useCases":390,"indexable":223},"GDPR","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2016\u002F679\u002Foj","General Data Protection Regulation, including Article 22 on decisions based solely on automated processing.",246,{"id":159,"label":392,"issuer":393,"region":394,"url":395,"description":396,"useCases":397,"indexable":223},"ISO\u002FIEC 42001","ISO and IEC","global","https:\u002F\u002Fwww.iso.org\u002Fstandard\u002F81230.html","The international management system standard for AI.",143,{"id":399,"label":400,"issuer":401,"region":210,"url":402,"description":403,"useCases":404,"indexable":223},"nist-ai-rmf","NIST AI Risk Management Framework","NIST","https:\u002F\u002Fwww.nist.gov\u002Fitl\u002Fai-risk-management-framework","Voluntary US framework to map, measure, manage and govern AI risk, with a generative AI profile.",110,{"id":406,"label":407,"issuer":408,"region":164,"url":409,"description":410,"useCases":411,"indexable":223},"uk-gdpr","UK GDPR","Information Commissioner's Office","https:\u002F\u002Fico.org.uk\u002Ffor-organisations\u002Fuk-gdpr-guidance-and-resources\u002F","The UK's version of the GDPR, including rules on solely automated decisions.",81,{"id":155,"label":413,"issuer":163,"region":164,"url":165,"description":414,"useCases":415,"indexable":223},"DORA","Digital Operational Resilience Act for financial entities: ICT risk, incident reporting and third party risk, including AI providers.",72,{"id":417,"label":418,"issuer":419,"region":164,"url":420,"description":421,"useCases":422,"indexable":223},"uk-consumer-duty","FCA Consumer Duty","Financial Conduct Authority","https:\u002F\u002Fwww.fca.org.uk\u002Ffirms\u002Fconsumer-duty","UK rules that require firms to deliver good outcomes for retail customers, including through automated channels.",51,{"id":424,"label":425,"issuer":426,"region":170,"url":427,"description":428,"useCases":429,"indexable":223},"mas-ai-risk-management","MAS AI risk management guidelines","Monetary Authority of Singapore","https:\u002F\u002Fwww.mas.gov.sg\u002Fnews\u002Fmedia-releases\u002F2025\u002Fmas-guidelines-for-artificial-intelligence-risk-management","Singapore's supervisory expectations for AI risk management at financial institutions, building on the FEAT principles.",37,{"id":156,"label":431,"issuer":169,"region":170,"url":171,"description":432,"useCases":433,"indexable":223},"APRA CPS 230","Australian operational risk standard covering critical operations and material service providers.",26,{"id":435,"label":436,"issuer":437,"region":210,"url":438,"description":439,"useCases":440,"indexable":223},"us-sr-11-7","SR 11-7 model risk management","Federal Reserve and OCC","https:\u002F\u002Fwww.federalreserve.gov\u002Fboarddocs\u002Fsrletters\u002F2011\u002Fsr1107.htm","US supervisory guidance on model risk management, applied by banks to AI and machine learning models.",23,{"id":442,"label":443,"issuer":163,"region":164,"url":444,"description":445,"useCases":446,"indexable":223},"nis2","NIS2 Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2022\u002F2555\u002Foj","Directive (EU) 2022\u002F2555 on cybersecurity for essential and important entities, including telecom networks, energy and public administration.",22,{"id":448,"label":449,"issuer":450,"region":394,"url":451,"description":452,"useCases":446,"indexable":223},"pci-dss","PCI DSS","PCI Security Standards Council","https:\u002F\u002Fwww.pcisecuritystandards.org\u002F","Security standard for any system that stores, processes or transmits cardholder data.",{"id":454,"label":455,"issuer":456,"region":164,"url":457,"description":458,"useCases":459,"indexable":223},"uk-atrs","UK Algorithmic Transparency Recording Standard","UK Government","https:\u002F\u002Fwww.gov.uk\u002Fgovernment\u002Fcollections\u002Falgorithmic-transparency-recording-standard-hub","Mandatory transparency records for algorithmic tools used by UK central government.",18,{"id":461,"label":462,"issuer":463,"region":210,"url":464,"description":465,"useCases":466,"indexable":223},"hipaa","HIPAA","US Department of Health and Human Services","https:\u002F\u002Fwww.hhs.gov\u002Fhipaa\u002Findex.html","US rules for the privacy and security of protected health information.",17,{"id":468,"label":469,"issuer":470,"region":394,"url":471,"description":472,"useCases":61,"indexable":223},"fatf-recommendations","FATF Recommendations","Financial Action Task Force","https:\u002F\u002Fwww.fatf-gafi.org\u002Fen\u002Fpublications\u002FFatfrecommendations\u002FFatf-recommendations.html","Global standards for anti money laundering and counter terrorist financing that national rules implement.",{"id":474,"label":475,"issuer":163,"region":164,"url":476,"description":477,"useCases":478,"indexable":223},"eu-amlr","EU Anti Money Laundering Regulation","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2024\u002F1624\u002Foj","Regulation (EU) 2024\u002F1624: the single EU rulebook for customer due diligence, beneficial ownership and suspicious transaction reporting.",14,{"id":480,"label":481,"issuer":482,"region":210,"url":483,"description":484,"useCases":478,"indexable":223},"us-tcpa","Telephone Consumer Protection Act","Federal Communications Commission","https:\u002F\u002Fwww.fcc.gov\u002Fconsumers\u002Fguides\u002Fstop-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":486,"label":487,"issuer":488,"region":210,"url":489,"description":490,"useCases":491,"indexable":223},"us-bsa","Bank Secrecy Act","FinCEN","https:\u002F\u002Fwww.fincen.gov\u002Fresources\u002Fstatutes-and-regulations\u002Fbank-secrecy-act","US anti money laundering law: customer due diligence, suspicious activity reports and record keeping.",13,{"id":493,"label":494,"issuer":163,"region":164,"url":495,"description":496,"useCases":491,"indexable":223},"eu-accessibility-act","European Accessibility Act","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2019\u002F882\u002Foj","Directive (EU) 2019\u002F882: accessibility requirements for banking services, ecommerce and other digital services, applicable since June 2025.",{"id":498,"label":499,"issuer":163,"region":164,"url":500,"description":501,"useCases":491,"indexable":223},"solvency-ii","Solvency II","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2009\u002F138\u002Foj","Directive 2009\u002F138\u002FEC: risk based capital, governance and model requirements for insurers.",{"id":503,"label":504,"issuer":505,"region":210,"url":506,"description":507,"useCases":508,"indexable":223},"us-ecoa-reg-b","ECOA and Regulation B","Consumer Financial Protection Bureau","https:\u002F\u002Fwww.consumerfinance.gov\u002Frules-policy\u002Fregulations\u002F1002\u002F9\u002F","US fair lending rules, including specific reasons in adverse action notices, which also apply when credit decisions use AI models.",12,{"id":510,"label":511,"issuer":512,"region":394,"url":513,"description":514,"useCases":508,"indexable":223},"telecom-consumer-rules","Telecom consumer protection rules","National telecom regulators","https:\u002F\u002Fwww.berec.europa.eu\u002F","National rules on telecom contracts, switching, billing disputes and marketing consent.",{"id":516,"label":517,"issuer":518,"region":164,"url":519,"description":520,"useCases":521,"indexable":223},"eba-loan-origination","EBA Guidelines on loan origination and monitoring","European Banking Authority","https:\u002F\u002Fwww.eba.europa.eu\u002Fregulation-and-policy\u002Fcredit-risk\u002Fguidelines-on-loan-origination-and-monitoring","Expectations for credit decisioning, including the use of automated models.",11,{"id":523,"label":524,"issuer":163,"region":164,"url":525,"description":526,"useCases":521,"indexable":223},"eecc","European Electronic Communications Code","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2018\u002F1972\u002Foj","Directive (EU) 2018\u002F1972: consumer protection, contract, switching and security rules for telecom operators.",{"id":528,"label":529,"issuer":163,"region":164,"url":530,"description":531,"useCases":521,"indexable":223},"eu-psd2","PSD2","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2015\u002F2366\u002Foj","Payment Services Directive 2: strong customer authentication, transaction risk analysis exemptions and open banking access.",{"id":533,"label":534,"issuer":426,"region":170,"url":535,"description":536,"useCases":292,"indexable":223},"mas-notice-626","MAS Notice 626","https:\u002F\u002Fwww.mas.gov.sg\u002Fregulation\u002Fnotices\u002Fnotice-626","Singapore's anti money laundering and counter terrorism financing requirements for banks.",{"id":538,"label":539,"issuer":163,"region":164,"url":540,"description":541,"useCases":292,"indexable":223},"mifid-ii","MiFID II","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2014\u002F65\u002Foj","Directive 2014\u002F65\u002FEU on markets in financial instruments: suitability and appropriateness of advice, record keeping and product governance.",{"id":543,"label":544,"issuer":545,"region":210,"url":546,"description":547,"useCases":548,"indexable":223},"us-fcra","Fair Credit Reporting Act","Federal Trade Commission","https:\u002F\u002Fwww.ftc.gov\u002Flegal-library\u002Fbrowse\u002Fstatutes\u002Ffair-credit-reporting-act","US rules on consumer reports, their accuracy and permissible use, relevant to credit scoring and screening.",8,{"id":550,"label":551,"issuer":163,"region":164,"url":552,"description":553,"useCases":365,"indexable":223},"eu-idd","Insurance Distribution Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2016\u002F97\u002Foj","Directive (EU) 2016\u002F97: conduct rules for selling insurance, including demands and needs testing and advice.",{"id":555,"label":556,"issuer":557,"region":558,"url":559,"description":560,"useCases":60,"indexable":223},"cbuae-ai-guidance","CBUAE guidance on AI and ML","Central Bank of the UAE","middle-east","https:\u002F\u002Fwww.centralbank.ae\u002F","UAE central bank expectations for the enabling technologies, AI and machine learning used by licensed financial institutions.",{"id":562,"label":563,"issuer":163,"region":164,"url":564,"description":565,"useCases":347,"indexable":223},"eu-mortgage-credit-directive","EU Mortgage Credit Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2014\u002F17\u002Foj","Directive 2014\u002F17\u002FEU: creditworthiness assessment, disclosure and advice rules for residential mortgage lending.",{"id":567,"label":568,"issuer":569,"region":164,"url":570,"description":571,"useCases":347,"indexable":223},"pra-ss1-23","PRA SS1\u002F23 model risk management","Prudential Regulation Authority","https:\u002F\u002Fwww.bankofengland.co.uk\u002Fprudential-regulation\u002Fpublication\u002F2023\u002Fmay\u002Fmodel-risk-management-principles-for-banks-ss","UK model risk management principles for banks, covering AI and machine learning models.",{"id":573,"label":574,"issuer":575,"region":164,"url":576,"description":577,"useCases":347,"indexable":223},"uk-psr-app-reimbursement","UK APP scam reimbursement rules","Payment Systems Regulator","https:\u002F\u002Fwww.psr.org.uk\u002Four-work\u002Fapp-scams\u002F","Mandatory reimbursement of authorised push payment scam victims by UK payment firms, which shifts scam losses onto banks.",{"id":579,"label":580,"issuer":581,"region":170,"url":582,"description":583,"useCases":584,"indexable":223},"au-scams-prevention-framework","Australian Scams Prevention Framework","Australian Treasury","https:\u002F\u002Ftreasury.gov.au\u002Fconsultation\u002Fc2024-573813","Economy wide obligations for banks, telcos and digital platforms to prevent, detect, disrupt and respond to scams.",3,{"id":586,"label":587,"issuer":163,"region":164,"url":588,"description":589,"useCases":584,"indexable":223},"eu-mar","EU Market Abuse Regulation","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2014\u002F596\u002Foj","Regulation (EU) 596\u002F2014: insider dealing and market manipulation, including the duty to detect and report suspicious orders and transactions.",{"id":591,"label":592,"issuer":593,"region":210,"url":594,"description":595,"useCases":584,"indexable":223},"nyc-local-law-144","NYC Local Law 144","New York City","https:\u002F\u002Fwww.nyc.gov\u002Fsite\u002Fdca\u002Fabout\u002Fautomated-employment-decision-tools.page","Bias audits and notices for automated employment decision tools used in hiring and promotion in New York City.",1791904353434]