[{"data":1,"prerenderedAt":624},["ShallowReactive",2],{"uc-autonomous-supplier-negotiation-agent":3,"uc-regulations":392},{"useCase":4,"evidence":176,"blitsAiDeployments":280,"benchmarks":281,"indicative":288,"related":291,"indexability":390,"includeUnpublished":182},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":17,"functions":22,"patterns":24,"channels":27,"audience":30,"autonomy":31,"adoptionStage":32,"problem":33,"problemStats":34,"howItWorks":35,"valueDrivers":36,"kpis":40,"indicativeValue":45,"macroEstimates":74,"feasibility":75,"implementation":88,"risk":134,"blitsAi":155,"faq":157,"related":167,"datePublished":171,"dateModified":171,"lastVerified":171,"changelog":172,"slug":175},"AI agent for autonomous supplier negotiation","Supplier negotiation agent","AI agent for supplier negotiation","An AI agent negotiates prices and payment terms with suppliers inside limits the buyer sets. Pactum reports over 2,500 autonomous negotiations at Honeywell.","published","An AI agent for supplier negotiation contacts suppliers the organization already buys from, usually in the long tail of spend, and negotiates price, payment terms or rebates with them within limits the buyer has set. Agreed terms flow back into the procurement system, and buyers handle the exceptions.",[12,13,14,15,16],"autonomous negotiation","AI procurement negotiation bot","supplier terms negotiation agent","payment terms negotiation agent","tail spend negotiation agent",[18,19,20,21],"cross-industry","retail-and-ecommerce","manufacturing","energy-and-utilities",[23],"procurement",[25,26],"agentic-workflow","conversational-agent",[28,29],"web-chat","internal-tools","back-office","supervised-agent","early-adopters","Most large buyers negotiate with their strategic suppliers and leave the rest on standard terms.\nAn HBR article co written by Walmart International's sourcing leaders reported that around 20% of\nWalmart's suppliers had signed standard terms that were often not negotiated, because buyers\nlacked the time. Pactum's Honeywell story describes hundreds of supplier contracts that were too\ntime consuming to negotiate by hand, and SUEZ recycling and recovery UK says its program reached\nsuppliers beyond its Tier 1 strategic partners.\n\nA tool that only recommends still leaves a person to write to each supplier, wait for the answer\nand key the result into the system. An agent holds the conversation itself, inside a mandate the\nbuyer writes, and records the outcome. That mandate sets what the agent may offer, what it may\nnever concede and which suppliers it may not contact.",[],"1. **Select the opportunity.** Procurement picks a supplier group and a lever, for example\n   standardizing payment terms, a flat rebate or an item level discount, using spend and\n   contract data.\n2. **Set the mandate.** The buyer writes down targets, walk away values, tradable terms and the\n   suppliers or categories that are excluded. Anything outside the mandate stops the agent.\n3. **Open the conversation.** The agent contacts each supplier through a chat interface\n   and explains the proposal.\n4. **Negotiate within limits.** The agent weighs the supplier's counter offers against the\n   mandate, offers trade offs the buyer allows (for example faster payment for a discount) and\n   closes when terms fall inside the range.\n5. **Write the result back.** Agreed terms go to the contract or payment system, and exceptions\n   or refused offers go to a buyer with the conversation attached.\n6. **Keep a record.** Every message and concession is logged, so a buyer or auditor can read\n   exactly how a deal was reached.",[37,38,39],"cost-to-serve","employee-productivity","speed",[41,42,43,44],"cost-savings","interactions-handled","processing-time-reduction","automation-rate",{"referenceOrg":46,"inputs":47,"formula":69,"currency":70,"period":71,"resultLabel":72,"caveat":73},"A manufacturer with 40 million USD a year of long tail supplier spend",[48,54,62],{"key":49,"label":50,"low":51,"high":51,"unit":52,"note":53},"tailSpend","Annual spend with suppliers that buyers do not negotiate today",40000000,"USD per year","The reference organization. Replace with your own spend cube.",{"key":55,"label":56,"low":57,"high":58,"unit":59,"note":60,"sourceUrl":61},"shareNegotiated","Share of that spend on which the agent agrees new terms in a year",0.2,0.5,"share as a fraction","Editorial assumption. Pactum reports that 80% of suppliers contacted at Honeywell engaged, and Walmart International's sourcing leaders reported in HBR that the chatbot closed agreements with 68% of suppliers approached, but those rates cover suppliers selected for the program, so the range is set well below them.","https:\u002F\u002Fpactum.com\u002Ftestimonial\u002Fhoneywell",{"key":63,"label":64,"low":65,"high":66,"unit":59,"note":67,"sourceUrl":68},"termGain","Average gain on the negotiated spend",0.01,0.03,"Editorial assumption set at the low end of the 1 to 7% range that Pactum states for its customers on its clients page. SUEZ recycling and recovery UK reports 2.5% average potential savings from targeted discounts. Vendor and customer claims, so the range is conservative.","https:\u002F\u002Fpactum.com\u002Fclients","tailSpend * shareNegotiated * termGain","USD","per year","Annual gain on long tail supplier spend","Gross gain on negotiated terms only. It leaves out the license and integration cost, the value of payment term changes counted as cash rather than price, supplier relationship effects and the buyer time still spent on exceptions.",[],{"complexity":76,"complexityNote":77,"dataPrerequisites":78,"integrations":83},"medium","A pilot needs a clean spend and contract extract for one category, a purchasing system that can take the agreed terms back, and a written mandate signed off by the category owner and legal. Rolling out across categories needs a supplier master with reliable contact data and a process for suppliers who want to talk to a person.",[79,80,81,82],"Spend data by supplier and category, with current prices and payment terms","Contract register with renewal dates and any exclusivity or notice clauses","Supplier master with named contacts and language preferences","Written negotiation mandate per category: targets, walk away values, allowed trade offs",[84,85,86,87],"Procurement or source to pay platform (for example Coupa or SAP Ariba)","ERP for payment terms and contract updates","Email or a hosted chat page for supplier contact","Contract lifecycle management system for the agreed terms",{"steps":89,"guardrails":105,"humanInTheLoop":111,"kpisToInstrument":112,"failureModes":118},[90,93,96,99,102],{"title":91,"detail":92},"Start with indirect spend and a single lever","Pick one category with many small suppliers and one lever, such as standard payment terms. Pactum's Honeywell story says that program began with an indirect spend pilot, and Ahold Delhaize USA runs its pilot in its Indirect Center of Excellence with select suppliers.",{"title":94,"detail":95},"Write the mandate before the agent","Agree the targets, the limits you will not cross, the terms you can trade and the exclusions with the category owner and legal. The agent reads this mandate, so ambiguity in it becomes ambiguity in the deals.",{"title":97,"detail":98},"Run supervised first","Let buyers read every conversation at the start. Ahold Delhaize USA says it keeps full oversight of each negotiation and interaction today, and that the level of review can evolve as confidence builds and governance matures.",{"title":100,"detail":101},"Write results back to the system of record","Connect the agent to the purchasing or contract system so agreed terms are updated by the workflow, not retyped.",{"title":103,"detail":104},"Widen by category and supplier tier","Add categories only after the sampled review shows deals landing inside the mandate.",[106,107,108,109,110],"The agent can only offer terms inside the written mandate and stops on anything outside it","Strategic suppliers and suppliers in dispute are excluded from contact","The agent states that it is an AI system and a person can be requested at any point","Every message and concession is logged and attached to the supplier record","Contract changes above a value threshold need a named human approval","A buyer owns each category mandate and reviews exceptions, refused offers and a monthly sample of closed deals. Suppliers can ask for a person at any time, and a negotiation the agent cannot close within the mandate goes to the buyer with the full conversation.",[113,114,115,116,117],"Share of approached suppliers who reply, agree and decline","Average gain per closed negotiation against the stated baseline terms","Share of negotiations closed with no buyer touch","Days from first contact to agreed terms","Supplier satisfaction after the conversation",[119,122,125,128,131],{"title":120,"detail":121},"Mandate too loose","The agent concedes a term the buyer would have refused. Keep the tradable terms short, test the mandate on a small group first and review closed deals each month.",{"title":123,"detail":124},"Supplier relationship damage","A supplier feels pushed by a bot. Exclude strategic suppliers, offer a person on request and read supplier replies for friction.",{"title":126,"detail":127},"Savings counted twice","A payment term gain and a price gain are both booked as savings. Agree with finance how each term converts to value before the first deal closes.",{"title":129,"detail":130},"Bluffing or false statements","To win a concession the agent states something false, such as an invented competing offer, which creates contract law exposure. Allow approved claims only and run test suites that catch false statements.",{"title":132,"detail":133},"Unchanged systems","Agreed terms sit in chat logs and never reach the contract or payment system. Make write back part of the pilot scope.",{"euAiAct":135,"regulations":138,"guidance":142,"controls":149,"incidents":154},{"tier":136,"basis":137},"limited","Article 50(1): suppliers who talk to the agent must be told they are dealing with an AI system unless that is obvious. Negotiating commercial terms between companies is not an Annex III high risk use. Check the design if the agent assigns or evaluates the work of individual contractors (Annex III, point 4).",[139,140,141],"eu-ai-act","gdpr","iso-42001",[143],{"title":144,"issuer":145,"region":146,"url":147,"note":148},"AI Risk Management Framework","National Institute of Standards and Technology","north-america","https:\u002F\u002Fwww.nist.gov\u002Fitl\u002Fai-risk-management-framework","Voluntary framework, with a generative AI profile, for governing and measuring the risks of an AI system such as an agent that commits the organization to supplier terms.",[150,151,152,153],"Inventory entry for the agent with an accountable head of category","Version controlled mandates with approval by procurement and legal","Sampled review of closed negotiations, logged with the result","Access control and retention rules for supplier contact data",[],{"howToBuild":156},"On Blits.ai this is an **agentic workflow** that runs one negotiation per supplier. A\n**knowledge base** holds the negotiation policy and the explanations the agent gives suppliers,\nretrieved with hybrid search. **Custom functions** (REST calls) read spend, contract and\nsupplier data from the procurement system or ERP, check every offer against the mandate limits\nbefore it is sent and write the agreed terms back, so the walk away values never sit in the\nagent's prompt. Suppliers reach the agent through **web chat**, and the\nsupplier can ask for **human handover** to a buyer at any point.\n\nOffers above a value threshold are set to require **human in the loop approval** before they\nare sent or closed. **Guardrails** block prompt injection from supplier messages, **PII masking** protects contact data, and **run history\nwith a full audit trail** keeps every concession. **Test suites** replay reference\nnegotiations, including hostile counter offers, after each mandate change. The platform is\nmodel agnostic. Run Blits.ai in our cloud in the EU, Qatar, Singapore, the UAE, the US or\nAustralia, in your private cloud, or fully on premises.",[158,161,164],{"question":159,"answer":160},"Is this an agent or a recommendation tool?","It is an agent when it contacts the supplier and closes terms itself. Jim Rahill of Pactum, the vendor, put it this way at DPW New York: the agent has to go out and do the work within the defined guardrails, then update the source systems. Ahold Delhaize USA, speaking in the same session, is still piloting and keeps full oversight of each negotiation and interaction.",{"question":162,"answer":163},"What results have buyers reported?","SUEZ recycling and recovery UK says on its own website that the platform contacted 2,000 additional suppliers within two months, and that Pactum's model delivered 2.5% average potential savings through targeted discounts and 15% cost reductions via a competitive purchasing environment; the page does not say what the 15% is measured against. Pactum reports more than 2,500 autonomous negotiations at Honeywell, and Walmart International's sourcing leaders reported in HBR in 2022 that the chatbot had closed agreements with 68% of suppliers approached. None of these figures is audited, and every deployment on this page runs on Pactum.",{"question":165,"answer":166},"Which spend suits it?","Indirect spend and the long tail, where many small suppliers sit on standard terms and no buyer has time. Strategic suppliers stay with people. Pactum's Honeywell story says the program began with an indirect spend pilot, and the Ahold Delhaize USA pilot runs in its Indirect Center of Excellence.",[168,169,170],"autonomous-rfq-and-tail-spend-sourcing","procurement-contract-review","procurement-spend-classification","2026-11-11",[173],{"date":171,"note":174},"First published","autonomous-supplier-negotiation-agent",[177,206,233,255],{"title":178,"useCases":179,"organization":180,"vendors":185,"summary":189,"stage":190,"year":191,"channels":192,"languages":193,"metrics":195,"outcomeDisclosed":196,"sources":197,"verification":201,"grade":203,"id":204,"organizationSlug":205},"SUEZ recycling and recovery UK: Pactum negotiates with suppliers by chatbot",[175],{"name":181,"anonymized":182,"country":183,"region":184,"industry":21},"SUEZ recycling and recovery UK",false,"GB","europe",[186],{"name":187,"role":188},"Pactum","platform","SUEZ recycling and recovery UK uses Pactum's negotiation platform, built into its procurement system, to negotiate prices and payment terms with suppliers through a chatbot interface. SUEZ says the platform reached suppliers beyond its Tier 1 strategic partners, contacted 2,000 additional suppliers within two months and secured discounts through early payment incentives. It reports 2.5% average potential savings through targeted discounts and 15% cost reductions through a competitive purchasing environment. The page is published by SUEZ itself, with a quote from its Head of Procurement.","production",2025,[28,29],[194],"en",[],true,[198],{"url":199,"title":200,"publisher":181},"https:\u002F\u002Fwww.suez.co.uk\u002Fen-gb\u002Four-offering\u002Fsuccess-stories\u002Four-references\u002Fpactum-ai","SUEZ strengthens procurement with AI-powered negotiation",{"level":202,"checkedAt":171},"source-verified","B","suez-uk-pactum-supplier-negotiation",null,{"title":207,"useCases":208,"organization":209,"vendors":214,"summary":216,"stage":190,"year":217,"channels":218,"languages":219,"metrics":220,"outcomeDisclosed":196,"sources":221,"verification":229,"grade":203,"id":231,"organizationSlug":232},"Walmart: autonomous negotiation of supplier terms with tail end suppliers",[169,175],{"name":210,"anonymized":182,"country":211,"region":212,"industry":19,"wikidata":213},"Walmart","US","global","Q483551",[215],{"name":187,"role":188},"Walmart uses a chatbot from Pactum to negotiate payment terms and price discounts with tail end suppliers, where buyers lack time to negotiate and around 20% of suppliers had signed standard terms that are often not negotiated. The HBR article describing it is co written by two sourcing leaders at Walmart International and two University of Arkansas professors. Walmart decides the acceptable negotiation trade offs and the bot negotiates and closes agreements within them; the article advises starting in indirect spend categories with pre approved suppliers and scaling by geography, category and use case. The authors report that, so far, the chatbot has closed agreements with 68% of suppliers approached. Pactum, the vendor, reports a 3% average gain across negotiations while extending payment terms by an average of 35 days. The first is a supplier agreement rate and the second a commercial gain on negotiated terms; neither measures how much of the process runs without human touch or what procurement costs to run.",2022,[28,29],[194],[],[222,227],{"url":223,"title":224,"publisher":225,"date":226},"https:\u002F\u002Fhbr.org\u002F2022\u002F11\u002Fhow-walmart-automated-supplier-negotiations","How Walmart Automated Supplier Negotiations","Harvard Business Review","2022-11-08",{"url":68,"title":228,"publisher":187},"Clients",{"level":202,"checkedAt":230},"2026-09-27","walmart-autonomous-supplier-negotiation","walmart",{"title":234,"useCases":235,"organization":236,"vendors":238,"summary":240,"stage":241,"year":242,"channels":243,"languages":244,"metrics":245,"outcomeDisclosed":182,"sources":246,"verification":252,"grade":253,"id":254,"organizationSlug":205},"Ahold Delhaize USA: pilot of AI supported supplier negotiations with Pactum",[175],{"name":237,"anonymized":182,"country":211,"region":146,"industry":19},"Ahold Delhaize USA",[239],{"name":187,"role":188},"Ahold Delhaize USA's Indirect Center of Excellence is piloting autonomous supplier negotiations with Pactum, with the aim of cost savings. At DPW New York its Director said the team is piloting with select suppliers and keeps full oversight of each negotiation. No figures were disclosed. Recorded as a pilot: it shows the cautious, supervised way a large buyer starts.","pilot",2026,[29],[194],[],[247],{"url":248,"title":249,"publisher":250,"date":251},"https:\u002F\u002Fcpostrategy.media\u002Fblog\u002F2026\u002F07\u002F22\u002Fhow-ahold-delhaize-usa-and-pactum-are-bringing-agentic-ai-into-supplier-negotiations\u002F","How Ahold Delhaize USA and Pactum are bringing agentic AI into supplier negotiations","CPOstrategy","2026-07-22",{"level":202,"checkedAt":171},"C","ahold-delhaize-usa-pactum-supplier-negotiation-pilot",{"title":256,"useCases":257,"organization":258,"vendors":261,"summary":263,"stage":264,"year":191,"channels":265,"languages":266,"metrics":267,"outcomeDisclosed":196,"sources":275,"verification":278,"grade":253,"id":279,"organizationSlug":205},"Honeywell: Pactum agents negotiate supplier terms at enterprise scale",[175],{"name":259,"anonymized":182,"country":211,"region":146,"industry":20,"wikidata":260},"Honeywell","Q898208",[262],{"name":187,"role":188},"Honeywell started with an indirect spend pilot of Pactum's negotiation agents and then made them its standard route for negotiating with a large supplier base, covering payment term standardization, rebates and item level discounts. Pactum's customer story reports more than 2,500 autonomous negotiations and that 80% of suppliers contacted engaged. The story is written and published by the vendor, with a quote from Honeywell's Chief Procurement Officer.","scaled",[28,29],[194],[268],{"kpi":42,"value":269,"unit":270,"qualifier":271,"period":272,"claimant":273,"quote":274,"sourceUrl":61},2500,"count","at-least","to date, undated story","vendor","They built it into how they operate, deploying nearly half a billion dollars in spend through Pactum AI and concluding more than 2,500 autonomous negotiations to date.",[276],{"url":61,"title":277,"publisher":187},"How Honeywell is Running Autonomous Procurement at Enterprise Scale",{"level":202,"checkedAt":171},"honeywell-pactum-autonomous-negotiation",0,[282],{"kpi":42,"label":283,"unit":270,"aggregate":182,"higherIsBetter":196,"n":284,"nUpTo":280,"median":269,"min":269,"max":269,"byClaimant":285,"vendorOnly":196,"points":286},"Interactions handled",1,{"organization":280,"vendor":284,"regulator":280,"independent":280},[287],{"evidenceId":279,"organization":259,"value":269,"qualifier":271,"claimant":273,"grade":253,"pooled":196},{"low":289,"high":290},80000,600000,[292,318,348,363],{"slug":168,"title":293,"shortTitle":294,"definition":295,"status":9,"industries":296,"functions":299,"patterns":301,"audience":30,"autonomy":31,"adoptionStage":32,"evidenceCount":304,"publicEvidenceCount":304,"organizations":305,"bestGrade":253,"headline":310,"lastVerified":317,"indexable":196},"AI agent for autonomous RFQ and tail spend sourcing","RFQ and tail spend sourcing","Autonomous RFQ sourcing is AI that sends requests for quotation to suppliers, compares the bids and recommends or makes the award for small purchases, within rules a buyer sets. It covers the tail of spend, the many low value or repeat requests that buyers rarely have time to compete, and hands complex or high value events to a person.",[18,21,297,298],"technology","logistics-and-transportation",[23,300],"operations",[25,302,303],"document-processing","content-generation",4,[306,307,308,309],"bp","G42","Massachusetts Bay Transportation Authority (MBTA)","Snowflake",{"kpi":43,"label":311,"unit":312,"n":313,"nUpTo":280,"kind":314,"value":315,"qualifier":316,"claimant":273,"organization":307,"vendorReported":196},"Cycle time reduction","percent",2,"reported",75,"exact","2026-10-13",{"slug":169,"title":319,"shortTitle":320,"definition":321,"status":9,"industries":322,"functions":325,"patterns":328,"audience":330,"autonomy":331,"adoptionStage":32,"evidenceCount":332,"publicEvidenceCount":333,"organizations":334,"bestGrade":203,"headline":345,"lastVerified":230,"indexable":196},"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.",[18,323,324,19,20],"banking","government",[23,326,327],"legal","finance-and-accounting",[302,329,303,25],"rag-knowledge-assistant","employee-facing","copilot",13,12,[335,336,337,338,339,340,341,342,343,210,344],"Bridgewater Associates","CompSource Mutual Insurance Company","General Services Administration","Administration for Children and Families","Internal Revenue Service","Authority for Public Projects and Tenders and Local Content","Pension Benefit Guaranty Corporation","Pacific Northwest National Laboratory","Technology Common Services Center","Western Union",{"kpi":43,"label":311,"unit":312,"n":313,"nUpTo":280,"kind":314,"value":346,"qualifier":347,"claimant":273,"organization":336,"vendorReported":196},95,"approximately",{"slug":170,"title":349,"shortTitle":350,"definition":351,"status":9,"industries":352,"functions":354,"patterns":356,"audience":30,"autonomy":31,"adoptionStage":32,"evidenceCount":304,"publicEvidenceCount":304,"organizations":359,"bestGrade":203,"headline":205,"lastVerified":230,"indexable":196},"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.",[18,324,20,353],"healthcare",[23,327,355],"analytics-and-reporting",[357,302,358],"classification-and-routing","summarization",[360,339,361,362],"U.S. General Services Administration","U.S. Department of Agriculture","Veterans Health Administration",{"slug":364,"title":365,"shortTitle":366,"definition":367,"status":9,"industries":368,"functions":369,"patterns":370,"audience":30,"autonomy":31,"adoptionStage":372,"segment":30,"evidenceCount":373,"publicEvidenceCount":374,"organizations":375,"bestGrade":203,"headline":386,"lastVerified":230,"indexable":196},"supplier-invoice-processing","AI for supplier invoice processing in accounts payable","Supplier invoice processing","AI supplier invoice processing is AI that captures supplier invoices in any format and extracts the header and line data. It matches invoices to purchase orders and goods receipts, proposes tax and cost center coding, flags duplicates and suspected fraud, and routes them for approval and posting, leaving only exceptions to accounts payable staff.",[18,323,324,19,21],[327,23],[302,25,371,357],"anomaly-detection","mainstream",11,10,[376,377,378,379,380,381,382,383,384,385],"Adyen","Charter Hall","E.ON","Federal Deposit Insurance Corporation","Fugro","Georgetown University","Kingfisher","Octopus Energy","U.S. Immigration and Customs Enforcement","Veolia",{"kpi":44,"label":387,"unit":312,"n":304,"nUpTo":280,"kind":388,"value":389,"qualifier":316,"claimant":205,"organization":205,"vendorReported":182},"Automation rate","median",70,{"indexable":196,"reasons":391},[],[393,399,404,410,416,423,429,436,444,451,457,463,469,476,483,490,496,502,508,514,520,525,530,536,541,547,552,557,564,569,577,583,589,595,600,606,612,618],{"id":139,"label":394,"issuer":395,"region":184,"url":396,"description":397,"useCases":398,"indexable":196},"EU AI Act","European Union","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.",306,{"id":140,"label":400,"issuer":395,"region":184,"url":401,"description":402,"useCases":403,"indexable":196},"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.",276,{"id":141,"label":405,"issuer":406,"region":212,"url":407,"description":408,"useCases":409,"indexable":196},"ISO\u002FIEC 42001","ISO and IEC","https:\u002F\u002Fwww.iso.org\u002Fstandard\u002F81230.html","The international management system standard for AI.",150,{"id":411,"label":412,"issuer":413,"region":146,"url":147,"description":414,"useCases":415,"indexable":196},"nist-ai-rmf","NIST AI Risk Management Framework","NIST","Voluntary US framework to map, measure, manage and govern AI risk, with a generative AI profile.",115,{"id":417,"label":418,"issuer":419,"region":184,"url":420,"description":421,"useCases":422,"indexable":196},"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.",86,{"id":424,"label":425,"issuer":395,"region":184,"url":426,"description":427,"useCases":428,"indexable":196},"dora","DORA","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2022\u002F2554\u002Foj","Digital Operational Resilience Act for financial entities: ICT risk, incident reporting and third party risk, including AI providers.",73,{"id":430,"label":431,"issuer":432,"region":184,"url":433,"description":434,"useCases":435,"indexable":196},"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.",53,{"id":437,"label":438,"issuer":439,"region":440,"url":441,"description":442,"useCases":443,"indexable":196},"mas-ai-risk-management","MAS AI risk management guidelines","Monetary Authority of Singapore","asia-pacific","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":445,"label":446,"issuer":447,"region":440,"url":448,"description":449,"useCases":450,"indexable":196},"apra-cps-230","APRA CPS 230","Australian Prudential Regulation Authority","https:\u002F\u002Fwww.apra.gov.au\u002Foperational-risk-management","Australian operational risk standard covering critical operations and material service providers.",26,{"id":452,"label":453,"issuer":395,"region":184,"url":454,"description":455,"useCases":456,"indexable":196},"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.",23,{"id":458,"label":459,"issuer":460,"region":212,"url":461,"description":462,"useCases":456,"indexable":196},"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":464,"label":465,"issuer":466,"region":146,"url":467,"description":468,"useCases":456,"indexable":196},"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.",{"id":470,"label":471,"issuer":472,"region":146,"url":473,"description":474,"useCases":475,"indexable":196},"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.",21,{"id":477,"label":478,"issuer":479,"region":184,"url":480,"description":481,"useCases":482,"indexable":196},"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":484,"label":485,"issuer":486,"region":146,"url":487,"description":488,"useCases":489,"indexable":196},"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.",17,{"id":491,"label":492,"issuer":395,"region":184,"url":493,"description":494,"useCases":495,"indexable":196},"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.",15,{"id":497,"label":498,"issuer":499,"region":212,"url":500,"description":501,"useCases":495,"indexable":196},"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":503,"label":504,"issuer":395,"region":184,"url":505,"description":506,"useCases":507,"indexable":196},"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":509,"label":510,"issuer":511,"region":212,"url":512,"description":513,"useCases":507,"indexable":196},"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":515,"label":516,"issuer":517,"region":146,"url":518,"description":519,"useCases":332,"indexable":196},"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.",{"id":521,"label":522,"issuer":395,"region":184,"url":523,"description":524,"useCases":332,"indexable":196},"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":526,"label":527,"issuer":395,"region":184,"url":528,"description":529,"useCases":332,"indexable":196},"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":531,"label":532,"issuer":533,"region":146,"url":534,"description":535,"useCases":333,"indexable":196},"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.",{"id":537,"label":538,"issuer":395,"region":184,"url":539,"description":540,"useCases":333,"indexable":196},"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":542,"label":543,"issuer":544,"region":184,"url":545,"description":546,"useCases":373,"indexable":196},"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.",{"id":548,"label":549,"issuer":395,"region":184,"url":550,"description":551,"useCases":373,"indexable":196},"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":553,"label":554,"issuer":439,"region":440,"url":555,"description":556,"useCases":374,"indexable":196},"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":558,"label":559,"issuer":560,"region":146,"url":561,"description":562,"useCases":563,"indexable":196},"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":565,"label":566,"issuer":395,"region":184,"url":567,"description":568,"useCases":563,"indexable":196},"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":570,"label":571,"issuer":572,"region":573,"url":574,"description":575,"useCases":576,"indexable":196},"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.",6,{"id":578,"label":579,"issuer":395,"region":184,"url":580,"description":581,"useCases":582,"indexable":196},"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.",5,{"id":584,"label":585,"issuer":586,"region":184,"url":587,"description":588,"useCases":582,"indexable":196},"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":590,"label":591,"issuer":592,"region":440,"url":593,"description":594,"useCases":304,"indexable":196},"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.",{"id":596,"label":597,"issuer":439,"region":440,"url":598,"description":599,"useCases":304,"indexable":196},"mas-shared-responsibility-framework","MAS Shared Responsibility Framework","https:\u002F\u002Fwww.mas.gov.sg\u002Fregulation\u002Fguidelines\u002Fguidelines-on-shared-responsibility-framework","Singapore's framework that assigns banks and telcos duties and loss sharing for phishing scams.",{"id":601,"label":602,"issuer":603,"region":184,"url":604,"description":605,"useCases":304,"indexable":196},"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":607,"label":608,"issuer":395,"region":184,"url":609,"description":610,"useCases":611,"indexable":196},"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.",3,{"id":613,"label":614,"issuer":615,"region":146,"url":616,"description":617,"useCases":611,"indexable":196},"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.",{"id":619,"label":620,"issuer":621,"region":573,"url":622,"description":623,"useCases":611,"indexable":196},"sdaia-ai-ethics","SDAIA AI ethics principles","Saudi Data and AI Authority","https:\u002F\u002Fsdaia.gov.sa\u002Fen\u002FSDAIA\u002Fabout\u002FDocuments\u002Fai-principles.pdf","Saudi Arabia's national AI ethics principles, applied across sectors including finance and government.",1794496879864]