[{"data":1,"prerenderedAt":776},["ShallowReactive",2],{"uc-conversational-money-transfer-assistant":3,"uc-regulations":563},{"useCase":4,"evidence":214,"blitsAiDeployments":432,"benchmarks":433,"indicative":453,"related":456,"indexability":561,"includeUnpublished":220},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":17,"functions":20,"patterns":23,"channels":27,"audience":32,"autonomy":33,"adoptionStage":34,"segment":35,"problem":36,"problemStats":37,"howItWorks":38,"valueDrivers":39,"kpis":44,"indicativeValue":51,"macroEstimates":85,"feasibility":86,"implementation":101,"risk":148,"blitsAi":189,"faq":191,"related":204,"datePublished":209,"dateModified":209,"lastVerified":209,"changelog":210,"slug":213},"AI assistant for money transfers and bill payments by chat or voice","Conversational transfers and bill payment","AI money transfers by voice and chat in banking","A bank's AI assistant sends money or pays a bill from a spoken or typed request. See public cases in Brazil, Azerbaijan and Malaysia, and the controls it needs.","published","A conversational money transfer assistant is an AI in a bank's app that turns a spoken or typed request into a transfer or bill payment. It works out who the money goes to from a name, a saved contact or an image, checks the amount against limits, and sends the payment over the bank's own rails under the authentication and fraud checks the bank applies in its app.",[12,13,14,15,16],"voice banking transfers","Pix by voice","conversational payments","chat banking money transfer","AI payment instruction assistant",[18,19],"banking","payments",[21,22],"customer-service","operations",[24,25,26],"conversational-agent","voice-agent","agentic-workflow",[28,29,30,31],"mobile-app","whatsapp","voice","web-chat","customer-facing","supervised-agent","early-adopters","front-office","Sending money in a banking app means finding the right menu, choosing a payee, typing an amount\nand a reference, and passing a confirmation step. Each step is a place where a customer can stall,\nand an assistant that only explains where the transfer screen is leaves the customer to do the\nwork.\n\nA new group of assistants takes the instruction itself. A customer says or types \"send 10,000 yen\nto Tanaka\", sends a voice message with a name and an amount, or photographs an invoice, and the\nassistant takes it from there. Nubank in Brazil, Bank ABB in Azerbaijan and Boost in Malaysia have\npublished versions of this, SBI Sumishin Net Bank in Japan began a beta of one in February 2026,\nand Itaú Unibanco is rolling one out in its app. The releases differ on approval: Itaú describes\nan explicit confirmation before the Pix closes, Bank ABB describes the transfer being completed\nright after the customer names the contact, and the others do not say.\n\nThis page covers the payment instruction a customer gives in the moment. The customer asks for\neach payment, and whether the bank adds a confirmation step is a design choice that the\nrecommendations below settle in favor of one. An agent that buys from merchants on its own within a spending mandate is\ncovered by the agentic payment initiation page. Routine servicing such as card blocks and\nstatements is covered by the account and card servicing page, and stopping a payment that looks\nlike a scam is covered by the scam payment interception page.",[],"1. **Understand the instruction.** The assistant reads text, a voice message or an image and\n   extracts the intent (send money, pay a bill, move money between own accounts), the amount, the\n   currency and a reference to the payee. Some assistants accept several recipients in one\n   message, and some read an invoice or a screenshot.\n2. **Resolve the payee from known data only.** The assistant matches the name against saved\n   contacts, earlier payees or the bank's own directory. Bank ABB, for example, requires the\n   mobile number to be saved in the sender's phone contacts. An unknown name or an ambiguous match\n   goes back to the customer as a question.\n3. **Show the payment before it moves.** The assistant presents the resolved payee, the amount and\n   the reference on screen. Itaú Unibanco's assistant builds a Pix from a voice command and closes\n   it only after an explicit confirmation from the customer. Bank ABB's assistant completes the\n   transfer right after the customer names the contact, so each bank decides this step for itself.\n4. **Authenticate and apply limits.** The payment goes through the same strong authentication,\n   per transaction and daily limits and fraud analysis as a payment made by hand. Nubank applies\n   its app risk analysis to Pix sent on WhatsApp, with a cap per transaction and per day during the\n   test phase.\n5. **Execute through the bank's payment API.** A service call to the payment API creates the\n   payment, with an idempotency key so a retry cannot pay twice.\n6. **Confirm, record and hand over.** The assistant reports the result, keeps the instruction, the\n   confirmation and the payment together as one record, and passes anything it cannot resolve to a\n   person or to the normal app screen.",[40,41,42,43],"customer-experience","speed","inclusion-and-access","cost-to-serve",[45,46,47,48,49,50],"processing-time-reduction","automation-rate","users-served","interactions-handled","customer-satisfaction","error-reduction",{"referenceOrg":52,"inputs":53,"formula":80,"currency":81,"period":82,"resultLabel":83,"caveat":84},"A retail bank with 2 million digitally active customers",[54,59,66,73],{"key":55,"label":56,"low":57,"high":57,"unit":55,"note":58},"customers","Digitally active customers",2000000,"The reference bank.",{"key":60,"label":61,"low":62,"high":63,"unit":64,"note":65},"assistedRequestRate","Payment requests per customer per year that today reach the phone or a branch",0.05,0.15,"requests per customer per year","Editorial assumption, replace with your own. Take the figure from your contact center and branch logs for payment related contacts.",{"key":67,"label":68,"low":69,"high":70,"unit":71,"note":72},"assistantShare","Share of those requests the assistant completes",0.2,0.5,"fraction of requests","Editorial assumption, replace with your own. No deployment on this page has published a completion rate, so no benchmark is available.",{"key":74,"label":75,"low":76,"high":77,"unit":78,"note":79},"costPerAssistedRequest","Cost of a payment request handled by a person",4,8,"USD per request","Editorial assumption, replace with your own fully loaded cost per phone or branch contact.","customers * assistedRequestRate * assistantShare * costPerAssistedRequest","USD","per year","Annual servicing cost avoided on payment requests handled by phone or branch","Counts only payment requests that today go to people. It leaves out the time customers save on payments they already make in the app, which is where Nubank reports a reduction in transaction time of up to 60%, and it leaves out build and run cost, misdirected payment losses and the cost of disputes. Customers who switch from the app screens add no saving.",[],{"complexity":87,"complexityNote":88,"dataPrerequisites":89,"integrations":94},"medium","The work sits in the bank's payment API, the payee data and the authentication step, which already exist for the app; the assistant adds speech or text understanding, a payee resolver and a confirmation screen on top. Voice and WhatsApp add their own identity and limit questions, as Nubank's separate caps for WhatsApp show.",[90,91,92,93],"Saved contacts, earlier payees and beneficiary data per customer, with names in the forms customers actually say","Per customer limits, daily totals and the authentication level each payment type needs","Transaction history and fraud signals for risk checks on the new channel","Labeled utterances for transfers and bill payments in each language, including local names and amounts spoken in words",[95,96,97,98,99,100],"Payment initiation API of the core banking or instant payment platform","Strong customer authentication (biometrics, passkeys, PIN or app confirmation)","Fraud engine and payee name check or confirmation of payee service","Messaging channel such as WhatsApp Business, or the bank's mobile app with voice input","Speech recognition and speech synthesis for voice, and image reading for invoices or screenshots","Notification service for receipts and payment alerts",{"steps":102,"guardrails":118,"humanInTheLoop":124,"kpisToInstrument":125,"failureModes":132},[103,106,109,112,115],{"title":104,"detail":105},"Start with payments the customer already makes","Begin with transfers to saved contacts and own accounts, plus bill payments to billers the customer has paid before. A short allow list of payment types keeps the first release reviewable and gives a clean baseline for error and completion rates.",{"title":107,"detail":108},"Resolve the payee with a deterministic resolver","Match names against contacts and payee history with a deterministic resolver that returns candidates with a confidence value. Below the threshold, ask the customer to pick. Never let the model supply an account number, phone number or payee identifier of its own.",{"title":110,"detail":111},"Make the confirmation screen the only way a payment starts","Show payee, amount, currency and reference as structured fields, and require the customer's explicit approval with the authentication level the amount calls for. A voice command counts as an instruction to prepare a payment, and the approval is a separate step.",{"title":113,"detail":114},"Reuse the bank's limits and fraud checks on the new channel","Send every assistant payment through the same payment API, limits and fraud scoring as the app, and set tighter caps for the first weeks on messaging and voice. Raise them as the error and fraud data comes in.",{"title":116,"detail":117},"Run a test set of awkward instructions before each release","Include similar names, amounts spoken in words, mixed languages, instructions that change mid sentence and requests to exceed a limit, and replay them on every change to the model or the resolver.",[119,120,121,122,123],"Payee identifiers come only from the customer's contacts, payee history or the bank's directory, never from model output","Explicit customer confirmation of payee, amount and currency before every payment, with strong authentication at the level the amount requires","The same limits, authentication and fraud scoring as the app, with lower caps on new channels in the first weeks","Idempotency keys and velocity limits so a retry or a repeated voice command cannot pay twice","Prompt injection and PII screening on text, images and documents the customer sends, and no card numbers or full account numbers in logs","In the recommended design the customer approves every payment. Payments and fraud teams own the allow list of payment types, the caps per channel and the confidence threshold for payee matching, review a weekly sample of conversations with corrections, and approve each new payment type before the assistant can prepare it. Anything the assistant cannot resolve goes to the standard app screens or a person.",[126,127,128,129,130,131],"Share of instructions that end in a confirmed payment, and the share abandoned at the confirmation screen","Misdirected payment rate (payee corrected or payment reported as wrong) compared with payments made by hand","Payee match rate on first attempt, split by language and channel","Time from instruction to confirmed payment, compared with the app flow","Fraud and scam losses and customer reported scams on assistant payments compared with the app","Handover rate and customer satisfaction on payment conversations",[133,136,139,142,145],{"title":134,"detail":135},"The wrong person is paid","A similar name, a nickname or a speech recognition error leads to the wrong payee. Resolve against the customer's own contacts, show the full payee name on the confirmation screen and track corrections by language.",{"title":137,"detail":138},"A voice command is treated as approval","Speech can be replayed, overheard or misheard. Keep approval as a separate authenticated step, so that the instruction alone cannot execute a payment.",{"title":140,"detail":141},"Scam victims pay faster","A fluent, quick channel removes the pauses that let a customer reconsider a coached payment. Apply the bank's scam checks and warnings to assistant payments, and add friction on new payees and unusual amounts.",{"title":143,"detail":144},"Limits differ by channel and are exploited","Caps on messaging or voice that are looser than the app invite abuse, and caps that are too tight make the assistant useless. Set them per channel from the first weeks of fraud and error data.",{"title":146,"detail":147},"Language coverage lags the launch language","A resolver tuned for one language mismatches names and amounts in others. Test each language and dialect separately before it goes live and keep a fallback to the app screen.",{"euAiAct":149,"regulations":152,"guidance":160,"controls":182,"incidents":188},{"tier":150,"basis":151},"limited","A customer facing assistant must make clear that people are dealing with AI, unless that is obvious from the context (Article 50). Preparing a payment the customer approves is not listed in Annex III. It becomes high risk if the same assistant evaluates creditworthiness, for example by deciding on an overdraft or credit line at the moment of payment (Annex III point 5(b)).",[153,154,155,156,157,158,159],"eu-ai-act","eu-psd2","gdpr","dora","uk-psr-app-reimbursement","mas-shared-responsibility-framework","uk-consumer-duty",[161,167,172,178],{"title":162,"issuer":163,"region":164,"url":165,"note":166},"Commission Delegated Regulation (EU) 2018\u002F389 on strong customer authentication and common and secure open standards of communication","European Union","europe","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg_del\u002F2018\u002F389\u002Foj","Sets the strong customer authentication requirements, including dynamic linking of the authentication to the amount and the payee, which a confirmation screen has to satisfy whether the instruction came by voice, text or image.",{"title":168,"issuer":169,"region":164,"url":170,"note":171},"APP scams","Payment Systems Regulator","https:\u002F\u002Fwww.psr.org.uk\u002Four-work\u002Fapp-scams\u002F","UK reimbursement requirement for APP scam victims paying by Faster Payments or CHAPS, which applies to payments a customer approves after an assistant prepared them.",{"title":173,"issuer":174,"region":175,"url":176,"note":177},"Guidelines on Shared Responsibility Framework","Monetary Authority of Singapore","asia-pacific","https:\u002F\u002Fwww.mas.gov.sg\u002Fregulation\u002Fguidelines\u002Fguidelines-on-shared-responsibility-framework","Covers phishing scams, where it assigns duties to financial institutions and telcos and requires payouts to victims where those duties are breached. A payment the customer authorized may fall outside it, so it applies to this use case only in part.",{"title":179,"issuer":163,"region":164,"url":180,"note":181},"Regulation (EU) 2024\u002F1689 (AI Act), Article 50: transparency obligations for providers and deployers of certain AI systems","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2024\u002F1689\u002Foj","People must be informed that they are interacting with an AI system unless this is obvious from the context.",[183,184,185,186,187],"AI disclosure at the start of the conversation and on voice calls","A record that links each instruction, the resolved payee, the confirmation and the payment","Caps, payment type allow list and payee confidence threshold approved by the payments and fraud risk owners","Monitoring of misdirected payments, corrections and scam reports on assistant payments against the app baseline","Regression tests for payee resolution, limit enforcement and injection resistance before every release",[],{"howToBuild":190},"On Blits.ai the assistant is an **agent** in a **flow** that extracts the payee reference, amount\nand currency from text or voice, with **speech to text** and **text to speech** for voice and\n**WhatsApp** or the **REST and WebSocket API channel** for the bank's own mobile app. **Custom\nfunctions** call the bank's contact, limit and payment APIs, resolve the payee against the\ncustomer's own data and create the payment, so account details never come from the model. The\nflow shows the payee and amount and waits for the customer's confirmation; where a transfer is\nstarted as an **agentic workflow**, **human in the loop confirmation** above a configurable\nthreshold holds the action until it is approved or rejected.\n\n**Guardrails** screen prompt injection, **PII masking** keeps personal data out of logs, and\ncard numbers typed in chat are detected and tokenized at the gateway. Every run has an **audit\ntrail**. **Test suites** replay awkward instructions on every change, **monitors** check the flow\non a schedule, and **analytics** break down conversations by channel. The\nplatform is model agnostic and runs in dedicated EU and UAE production environments, with Azure\nand AWS deployment paths. Strong authentication and the payment rails stay with the\nbank's own systems, which the custom functions call.",[192,195,198,201],{"question":193,"answer":194},"How is this different from a banking chatbot that explains how to transfer money?","A chatbot of the older kind tells the customer which screen to open. A conversational transfer assistant takes the instruction, finds the payee, prepares the payment and sends it after the customer confirms. Bank ABB's release describes assistants that carry out banking operations through voice commands, and Nubank's customers send a Pix by audio, text or image.",{"question":196,"answer":197},"Does the customer still confirm each payment?","The public records differ. Itaú Unibanco's assistant builds a Pix from a voice command and closes it only after an explicit confirmation. Bank ABB says that after the customer names the contact, the AI immediately completes the transaction. Nubank, Boost and SBI Sumishin Net Bank do not describe a confirmation step in their releases. We recommend treating the voice or text instruction as a request to prepare a payment, with the approval as a separate authenticated step.",{"question":199,"answer":200},"Who is running this live?","Nubank offered Pix by AI in its app and on WhatsApp from December 2024 and reports that two million customers tried the WhatsApp version. Bank ABB opened its voice assistants to all customers in March 2026, Boost customers pay bills in the Boba AI chat, SBI Sumishin Net Bank (now DOCOMO SMTB Net Bank) began a beta of its NEOBANK ai agent in February 2026, and Itaú Unibanco began a staged rollout of ia.i in July 2026. None of them has published a misdirected payment rate or a completion rate.",{"question":202,"answer":203},"Does a faster payment channel increase scam losses?","It can, because a fluent channel removes pauses in which a customer might rethink a coached payment. Nubank states that the risk analyses of its app also apply on WhatsApp. Apply your scam checks, new payee friction and warnings to assistant payments, and compare scam reports against the app.",[205,206,207,208],"agentic-payment-initiation","account-and-card-servicing-agent","scam-payment-interception","real-time-fraud-scoring","2026-10-14",[211],{"date":209,"note":212},"First published","conversational-money-transfer-assistant",[215,244,273,294,322,355,388,408],{"title":216,"useCases":217,"organization":218,"vendors":223,"summary":224,"stage":225,"year":226,"channels":227,"languages":228,"metrics":230,"outcomeDisclosed":220,"sources":231,"verification":239,"grade":241,"id":242,"organizationSlug":243},"Bank ABB: AI-khan and AI-nur voice assistants make transfers for all customers",[213],{"name":219,"anonymized":220,"country":221,"region":164,"industry":18,"wikidata":222},"Bank ABB",false,"AZ","Q4288376",[],"Bank ABB in Azerbaijan opened its conversational assistants AI-khan and AI-nur to all customers in March 2026 after a beta stage. Customers can tell the assistant to move money between their own cards and accounts or to send money to another person by saying the contact's first and last name, and the assistant completes the transfer to the mobile number saved under that name. The assistants can also block or reactivate a card and answer product questions. The bank says more banking operations will follow. No usage or outcome figures are disclosed.","production",2026,[28,30],[229],"az",[],[232,236],{"url":233,"title":234,"publisher":219,"date":235},"https:\u002F\u002Fabb-bank.az\u002Fen\u002Fxeberler\u002Fabb-nin-yeni-suni-intellekt-komekcileri-ai-nur-ve-ai-khan-artiq-hamiya-elcatandir","Bank ABB’s new AI assistants - AI-nur and AI-khan - are now available to everyone!","2026-03-10",{"url":237,"title":234,"publisher":238},"https:\u002F\u002Fwww.trend.az\u002Fbusiness\u002F4162919.html","Trend.Az",{"level":240,"checkedAt":209},"source-verified","B","bank-abb-ai-khan-ai-nur-voice-transfers",null,{"title":245,"useCases":246,"organization":247,"vendors":250,"summary":251,"stage":225,"year":226,"channels":252,"languages":253,"metrics":256,"outcomeDisclosed":265,"sources":266,"verification":271,"grade":241,"id":272,"organizationSlug":243},"Boost: Boba AI pays bills and opens accounts inside chat",[213],{"name":248,"anonymized":220,"country":249,"region":175,"industry":18},"Boost","MY",[],"Boost, the Malaysian fintech and digital bank, announced in July 2026 an upgrade of Boba AI, its agentic assistant in the Boost app and the Boost Bank app. Customers can pay bills in the same conversation, after the assistant retrieves the real time outstanding balance, and can complete onboarding with eKYC and open a Boost Bank account. A separate voice service, Boba Voice, answers the Boost Bank hotline. Boost reports more than 30,000 customers and close to 100,000 requests in Boba AI since January 2026. The figures are Boost's own, and the release gives no split between bill payments and other requests.",[28],[254,255],"en","ms",[257],{"kpi":47,"value":258,"unit":259,"qualifier":260,"period":261,"claimant":262,"quote":263,"sourceUrl":264},30000,"count","at-least","since January 2026, all Boba AI use in the Boost app","organization","Since January 2026, more than 30,000 customers have interacted with Boba AI across the Boost app, generating close to 100,000 requests as customers increasingly use AI to manage everyday financial needs.","https:\u002F\u002Fmyboost.co\u002Fnewsroom\u002Fboost-brings-agentic-ai-everyday-banking",true,[267],{"url":264,"title":268,"publisher":269,"date":270},"Boost Brings Agentic AI To Everyday Banking","Boost Newsroom","2026-07-06",{"level":240,"checkedAt":209},"boost-boba-ai-bill-payments-and-onboarding",{"title":274,"useCases":275,"organization":276,"vendors":280,"summary":281,"stage":282,"year":226,"channels":283,"languages":284,"metrics":286,"outcomeDisclosed":220,"sources":287,"verification":292,"grade":241,"id":293,"organizationSlug":243},"SBI Sumishin Net Bank: NEOBANK ai agent guides fund transfers in the banking app",[213],{"name":277,"anonymized":220,"country":278,"region":175,"industry":18,"wikidata":279},"SBI Sumishin Net Bank","JP","Q17228896",[],"In February 2026 SBI Sumishin Net Bank began a phased beta of its NEOBANK ai agent inside its mobile banking app. A customer can type or say a request such as sending 10,000 yen to a named person, name several recipients in one message, or upload a photo or screenshot of an invoice, and the agent guides the transfer and generates the matching screens. The bank says its own research as of 14 February 2026 found this to be the first AI agent offered by a Japanese bank that can execute banking transactions such as fund transfers directly in a mobile app. It is a beta, and no usage or outcome figures are disclosed.","pilot",[28,30],[285],"ja",[],[288],{"url":289,"title":290,"publisher":277,"date":291},"https:\u002F\u002Fwww.netbk.co.jp\u002Fcontents\u002Fcompany\u002Fen\u002Fpress\u002F2026\u002F0227_005169.html","SBI Sumishin Net Bank Launches Beta Test of “NEOBANK ai” Agent, Japan’s First AI-Driven Banking Service with Generative UI","2026-02-27",{"level":240,"checkedAt":209},"sbi-sumishin-net-bank-neobank-ai-agent",{"title":295,"useCases":296,"organization":298,"vendors":302,"summary":306,"stage":225,"year":226,"channels":307,"languages":308,"metrics":309,"outcomeDisclosed":220,"sources":310,"verification":319,"grade":241,"id":321,"organizationSlug":243},"Starling Bank: Starling Assistant and its smart tools for money management",[297,213],"financial-wellbeing-coach",{"name":299,"anonymized":220,"country":300,"region":164,"industry":18,"wikidata":301},"Starling Bank","GB","Q19903669",[303],{"name":304,"role":305},"Google","model-provider","Starling Assistant is an agentic AI assistant in the Starling app that responds to text and voice, analyzes spending patterns, creates savings Spaces and sets up transfers on the customer's behalf. In August 2026 Starling added \"smart tools\" to it and said new ones would follow every week for the rest of 2026 and at least monthly after that. The launch set includes a tax saver that sweeps a share of the transactions a small business picks into a Space, a Making Tax Digital guide, a spending quiz and a student budget planner. A rainy day saver, which works out with the customer how much they can realistically save and sets up transfers into a savings Space, was announced as a follow up tool. The assistant is built on Google's Gemini models. No outcome figures are disclosed.",[28],[254],[],[311,315],{"url":312,"title":313,"publisher":299,"date":314},"https:\u002F\u002Fwww.starlingbank.com\u002Fnews\u002Fstarling-to-release-weekly-smart-tools","Starling to release weekly 'smart tools' that supercharge money management for millions of Brits","2026-08-20",{"url":316,"title":317,"publisher":318},"https:\u002F\u002Fcloud.google.com\u002Ftransform\u002F101-real-world-generative-ai-use-cases-from-industry-leaders","Real-world gen AI use cases from the world's leading organizations","Google Cloud",{"level":240,"checkedAt":320},"2026-09-27","starling-assistant-agentic-financial-assistant",{"title":323,"useCases":324,"organization":325,"vendors":330,"summary":331,"stage":225,"year":332,"channels":333,"languages":334,"metrics":336,"outcomeDisclosed":265,"sources":348,"verification":353,"grade":241,"id":354,"organizationSlug":243},"Nubank: Pix transfers by voice, text or image in the app and on WhatsApp",[213],{"name":326,"anonymized":220,"country":327,"region":328,"industry":18,"wikidata":329},"Nubank","BR","latin-america","Q25422888",[],"In December 2024 Nubank expanded Pix with generative AI in its app and on WhatsApp. A customer sends a voice message, a short text or an image that contains the recipient's name and the amount, and the AI builds and completes the Pix transfer. On WhatsApp the transfer runs entirely in the chat after a one time activation in the app, with a limit of R$200 per transaction and R$2,000 a day during the test phase. Nubank reports that two million customers had tried the WhatsApp version since October 2024 and that the AI version in the app cuts transaction time by up to 60%. The same fraud analysis that protects the app applies on WhatsApp.",2024,[28,29,30],[335],"pt",[337,344],{"kpi":45,"value":338,"unit":339,"qualifier":340,"baseline":341,"claimant":262,"quote":342,"sourceUrl":343},60,"percent","up-to","Transaction time for a Pix sent the usual way in the Nubank app","Pix with AI in the Nubank app uses technology to speed up processing, reducing transaction time by up to 60%, without compromising the security ensured by the app's defense mechanisms.","https:\u002F\u002Fnu.com\u002Fen\u002Fnewsroom\u002Fconsumers\u002Fnubank-leverages-ai-to-scale-pix-operations",{"kpi":47,"value":57,"unit":259,"qualifier":345,"period":346,"claimant":262,"quote":347,"sourceUrl":343},"exact","since October 2024 (WhatsApp test phase)","On WhatsApp, the feature was tested by 2 million customers since October.",[349],{"url":343,"title":350,"publisher":351,"date":352},"Nubank leverages AI to scale Pix operations","Nubank Newsroom","2024-12-10",{"level":240,"checkedAt":209},"nubank-pix-with-ai-app-and-whatsapp",{"title":356,"useCases":357,"organization":358,"vendors":363,"summary":364,"stage":365,"year":366,"channels":367,"languages":368,"metrics":370,"outcomeDisclosed":265,"sources":376,"verification":385,"grade":241,"id":386,"organizationSlug":387},"Wells Fargo: Fargo virtual assistant passes 1 billion customer interactions",[297,213],{"name":359,"anonymized":220,"country":360,"region":361,"industry":18,"wikidata":362},"Wells Fargo","US","north-america","Q744149",[],"Wells Fargo's Fargo virtual assistant, built into the Wells Fargo mobile app since 2023, helps customers send money with Zelle, pay bills, locate routing numbers and gain insights into their spending and account balances. The bank reported that Fargo has now supported customers through more than 1 billion interactions, reached in under three years since launch, and that more than 3 million Spanish speaking customers have used it, engaging with the assistant over 160 million times.","scaled",2023,[28],[254,369],"es",[371],{"kpi":48,"value":372,"unit":259,"qualifier":260,"period":373,"claimant":262,"quote":374,"sourceUrl":375},1000000000,"since Fargo's 2023 launch, reached in under three years","Fargo has now supported customers through more than 1 billion interactions – achieved in less than three years since its launch.","https:\u002F\u002Ffinancialit.net\u002Fnews\u002Fdigital-banking\u002Fwells-fargo-reaches-major-digital-milestones",[377,382],{"url":378,"title":379,"publisher":359,"date":380,"archivedUrl":381},"https:\u002F\u002Fnewsroom.wf.com\u002Fnews-releases\u002Fnews-details\u002F2026\u002FWells-Fargo-Reaches-Major-Digital-Milestones\u002Fdefault.aspx","Wells Fargo Reaches Major Digital Milestones","2026-03-26","https:\u002F\u002Fweb.archive.org\u002Fweb\u002F20260516124222\u002Fhttps:\u002F\u002Fnewsroom.wf.com\u002Fnews-releases\u002Fnews-details\u002F2026\u002FWells-Fargo-Reaches-Major-Digital-Milestones\u002Fdefault.aspx",{"url":375,"title":379,"publisher":383,"date":384},"Financial IT (copy of the Wells Fargo release)","2026-03-30",{"level":240,"checkedAt":209},"wells-fargo-fargo-digital-milestones","wells-fargo",{"title":389,"useCases":390,"organization":391,"vendors":394,"summary":395,"stage":282,"year":226,"channels":396,"languages":397,"metrics":398,"outcomeDisclosed":220,"sources":399,"verification":405,"grade":406,"id":407,"organizationSlug":243},"Itaú Unibanco: ia.i assistant builds Pix transfers from voice commands",[213],{"name":392,"anonymized":220,"country":327,"region":328,"industry":18,"wikidata":393},"Itaú Unibanco","Q1424293",[],"Itaú Unibanco began releasing ia.i in July 2026, a floating assistant on the home screen of its app that accepts text, voice and images. It answers questions about the customer's finances, explains products and executes transactions, including a Pix assembled from a voice command that closes only after the customer gives an explicit confirmation. The release started with 300,000 customers, with the bank planning 1 million by September and the whole customer base by the end of 2026. No usage or outcome figures are disclosed.",[28,30],[335],[],[400],{"url":401,"title":402,"publisher":403,"date":404},"https:\u002F\u002Fwww.letsmoney.com.br\u002Fnoticias\u002Fitau-ia-i-assistente-app\u002F","Itaú leva assistente de IA a 100% dos clientes até 2026","Let's Money","2026-07-30",{"level":240,"checkedAt":209},"C","itau-unibanco-iai-assistant-pix-by-voice",{"title":409,"useCases":410,"organization":411,"vendors":415,"summary":416,"stage":225,"year":226,"channels":417,"languages":418,"metrics":420,"outcomeDisclosed":220,"sources":421,"verification":430,"grade":406,"id":431,"organizationSlug":243},"Warba Bank: Bdr AI agentic banking assistant in the mobile app",[205,213],{"name":412,"anonymized":220,"country":413,"region":414,"industry":18},"Warba Bank","KW","middle-east",[],"Warba Bank in Kuwait launched Bdr AI in July 2026, an agentic assistant inside its mobile banking app. Retail customers give voice or text instructions in English or Arabic, including conversational Kuwaiti Arabic, to make instant transfers through WAMD, move money between their own Warba accounts, pay saved beneficiaries and generate PayMe links. Every transaction is shown on screen and needs the customer's explicit confirmation before it runs, and the assistant is available only after secure login with biometric protection. The bank describes it as the first agentic AI system to execute banking transactions directly by voice. No usage or outcome figure is disclosed.",[28,30],[419,254],"ar",[],[422,426],{"url":423,"title":424,"publisher":425},"https:\u002F\u002Finternationalfinance.com\u002Fislamic-banking\u002Fwarba-bank-launches-agentic-ai-banking-assistant-bdr-ai-in-kuwait-exclusive\u002F","Warba Bank launches Agentic AI banking assistant Bdr AI in Kuwait","International Finance",{"url":427,"title":428,"publisher":429},"https:\u002F\u002Fwww.middleeastainews.com\u002Fp\u002Fwarba-bank-launches-voice-ai-banking","Warba Bank launches voice AI banking assistant","Middle East AI News",{"level":240,"checkedAt":209},"warba-bank-bdr-ai-agentic-assistant",0,[434,442,448],{"kpi":47,"label":435,"unit":259,"aggregate":220,"higherIsBetter":265,"n":436,"nUpTo":432,"median":437,"min":258,"max":57,"byClaimant":438,"vendorOnly":220,"points":439},"Users served",2,1015000,{"organization":436,"vendor":432,"regulator":432,"independent":432},[440,441],{"evidenceId":354,"organization":326,"value":57,"qualifier":345,"claimant":262,"grade":241,"pooled":265},{"evidenceId":272,"organization":248,"value":258,"qualifier":260,"claimant":262,"grade":241,"pooled":265},{"kpi":48,"label":443,"unit":259,"aggregate":220,"higherIsBetter":265,"n":444,"nUpTo":432,"median":372,"min":372,"max":372,"byClaimant":445,"vendorOnly":220,"points":446},"Interactions handled",1,{"organization":444,"vendor":432,"regulator":432,"independent":432},[447],{"evidenceId":386,"organization":359,"value":372,"qualifier":260,"claimant":262,"grade":241,"pooled":265},{"kpi":45,"label":449,"unit":339,"aggregate":265,"higherIsBetter":265,"n":432,"nUpTo":444,"median":243,"min":243,"max":243,"byClaimant":450,"vendorOnly":220,"points":451},"Cycle time reduction",{"organization":432,"vendor":432,"regulator":432,"independent":432},[452],{"evidenceId":354,"organization":326,"value":338,"qualifier":340,"claimant":262,"grade":241,"pooled":220},{"low":454,"high":455},80000,1200000,[457,491,519,540],{"slug":205,"title":458,"shortTitle":459,"definition":460,"status":9,"industries":461,"functions":463,"patterns":465,"audience":32,"autonomy":33,"adoptionStage":466,"segment":35,"evidenceCount":467,"publicEvidenceCount":468,"organizations":469,"bestGrade":241,"headline":485,"lastVerified":320,"indexable":265},"AI agent for payment initiation within a customer mandate","Agentic payment initiation","Agentic payment initiation is an AI agent that initiates and completes payments or purchases on a customer's behalf, within a mandate the customer set in advance. The mandate sets spending caps, allowed merchants or categories, a tokenized credential and rules for when to ask for confirmation, and the agent then confirms and reconciles every transaction it made.",[19,18,462],"retail-and-ecommerce",[21,464,22],"sales",[26,24],"emerging",18,17,[470,471,472,473,474,475,476,477,478,479,480,481,482,483,484,412],"Alipay","Banca Transilvania","Danske Bank","DBS Bank","HSBC","ING","Majid Al Futtaim","Nordea","PayPal","Razorpay","Banco Santander","Ulta Beauty","Visa Europe","Visa","Walmart",{"kpi":486,"label":487,"unit":339,"n":444,"nUpTo":432,"kind":488,"value":489,"qualifier":490,"claimant":262,"organization":484,"vendorReported":220},"conversion-rate-uplift","Conversion uplift","reported",-67,"approximately",{"slug":206,"title":492,"shortTitle":493,"definition":494,"status":9,"industries":495,"functions":496,"patterns":497,"audience":32,"autonomy":33,"adoptionStage":499,"segment":35,"evidenceCount":500,"publicEvidenceCount":501,"organizations":502,"bestGrade":241,"headline":513,"lastVerified":320,"indexable":265},"AI agent for account and card servicing","Account and card servicing","An AI account and card servicing agent is an AI agent that resolves routine banking account and card requests for customers, end to end. It handles things like balances, statements, card blocks and replacements, PIN resets and limit changes, across app, web, messaging and phone, and hands anything sensitive or unusual to a human with the full context.",[18,19],[21,22],[24,25,26,498],"rag-knowledge-assistant","mainstream",13,11,[503,504,505,506,473,507,508,509,510,511,512],"Abu Dhabi Commercial Bank (ADCB)","Abu Dhabi Islamic Bank (ADIB)","BPCE Group","Commonwealth Bank of Australia","Emirates NBD","Equity Bank Kenya","KB Kookmin Card","NatWest Group","Simple (Attijariwafa bank)","Zenith Bank",{"kpi":514,"label":515,"unit":339,"n":516,"nUpTo":432,"kind":517,"value":518,"qualifier":345,"claimant":243,"organization":243,"vendorReported":220},"containment-rate","Containment rate",3,"median",85,{"slug":207,"title":520,"shortTitle":521,"definition":522,"status":9,"industries":523,"functions":524,"patterns":526,"audience":32,"autonomy":33,"adoptionStage":34,"segment":35,"evidenceCount":528,"publicEvidenceCount":528,"organizations":529,"bestGrade":241,"headline":535,"lastVerified":539,"indexable":265},"AI scam intervention for instant payments","Scam payment interception","Scam payment interception is AI that talks to a customer who is about to authorize an instant payment that looks like a scam. It combines the payee check and the risk score, asks targeted questions about the payment in plain language, explains the specific scam pattern, and holds, delays or escalates the payment to a human specialist when the risk stays high. Unlike fraud scoring, which stops payments the customer did not make, it protects customers from payments they are being manipulated into making.",[18,19],[525,21],"fraud-prevention",[24,527,26,25],"prediction-and-scoring",7,[530,506,531,532,299,533,534],"Česká spořitelna","Mastercard","Revolut","Vodafone","Westpac",{"kpi":536,"label":537,"unit":339,"n":516,"nUpTo":432,"kind":517,"value":538,"qualifier":345,"claimant":262,"organization":243,"vendorReported":220},"fraud-loss-reduction","Fraud loss reduction",40,"2026-09-26",{"slug":208,"title":541,"shortTitle":542,"definition":543,"status":9,"industries":544,"functions":545,"patterns":546,"audience":548,"autonomy":549,"adoptionStage":499,"segment":550,"evidenceCount":551,"publicEvidenceCount":551,"organizations":552,"bestGrade":241,"headline":559,"lastVerified":320,"indexable":265},"Real time fraud scoring for card and instant payments","Real time fraud scoring","Real time fraud scoring is machine learning that decides in milliseconds how likely each card authorization and account to account payment is to be fraudulent, so a bank can act. It works without any conversation, combining behavioral, device and network signals, so the bank can approve, challenge or block a payment before the money leaves. Working the resulting alerts and talking to the customer about them are separate use cases.",[18,19],[525],[527,547],"anomaly-detection","back-office","autonomous","middle-office",12,[553,554,555,506,531,510,556,557,532,558,483],"Arab National Bank (anb)","ANZ, Commonwealth Bank, NAB, Suncorp Bank and Westpac (BioCatch Trust Australia)","Capitec Bank","OVO","Pay.UK","Stripe",{"kpi":536,"label":537,"unit":339,"n":516,"nUpTo":432,"kind":517,"value":560,"qualifier":345,"claimant":262,"organization":243,"vendorReported":220},30,{"indexable":265,"reasons":562},[],[564,568,573,581,588,595,600,606,612,619,625,631,637,644,650,656,662,668,674,680,684,689,695,701,707,712,717,723,729,734,741,745,750,756,762,767,770],{"id":153,"label":565,"issuer":163,"region":164,"url":180,"description":566,"useCases":567,"indexable":265},"EU AI Act","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.",295,{"id":155,"label":569,"issuer":163,"region":164,"url":570,"description":571,"useCases":572,"indexable":265},"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.",265,{"id":574,"label":575,"issuer":576,"region":577,"url":578,"description":579,"useCases":580,"indexable":265},"iso-42001","ISO\u002FIEC 42001","ISO and IEC","global","https:\u002F\u002Fwww.iso.org\u002Fstandard\u002F81230.html","The international management system standard for AI.",148,{"id":582,"label":583,"issuer":584,"region":361,"url":585,"description":586,"useCases":587,"indexable":265},"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.",115,{"id":589,"label":590,"issuer":591,"region":164,"url":592,"description":593,"useCases":594,"indexable":265},"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.",84,{"id":156,"label":596,"issuer":163,"region":164,"url":597,"description":598,"useCases":599,"indexable":265},"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":159,"label":601,"issuer":602,"region":164,"url":603,"description":604,"useCases":605,"indexable":265},"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":607,"label":608,"issuer":174,"region":175,"url":609,"description":610,"useCases":611,"indexable":265},"mas-ai-risk-management","MAS AI risk management guidelines","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":613,"label":614,"issuer":615,"region":175,"url":616,"description":617,"useCases":618,"indexable":265},"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":620,"label":621,"issuer":163,"region":164,"url":622,"description":623,"useCases":624,"indexable":265},"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":626,"label":627,"issuer":628,"region":577,"url":629,"description":630,"useCases":624,"indexable":265},"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":632,"label":633,"issuer":634,"region":361,"url":635,"description":636,"useCases":624,"indexable":265},"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":638,"label":639,"issuer":640,"region":361,"url":641,"description":642,"useCases":643,"indexable":265},"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.",20,{"id":645,"label":646,"issuer":647,"region":164,"url":648,"description":649,"useCases":467,"indexable":265},"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.",{"id":651,"label":652,"issuer":163,"region":164,"url":653,"description":654,"useCases":655,"indexable":265},"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":657,"label":658,"issuer":659,"region":577,"url":660,"description":661,"useCases":655,"indexable":265},"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":663,"label":664,"issuer":665,"region":361,"url":666,"description":667,"useCases":655,"indexable":265},"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":669,"label":670,"issuer":163,"region":164,"url":671,"description":672,"useCases":673,"indexable":265},"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":675,"label":676,"issuer":677,"region":361,"url":678,"description":679,"useCases":500,"indexable":265},"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":154,"label":681,"issuer":163,"region":164,"url":682,"description":683,"useCases":500,"indexable":265},"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":685,"label":686,"issuer":163,"region":164,"url":687,"description":688,"useCases":500,"indexable":265},"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":690,"label":691,"issuer":692,"region":577,"url":693,"description":694,"useCases":500,"indexable":265},"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":696,"label":697,"issuer":698,"region":361,"url":699,"description":700,"useCases":551,"indexable":265},"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":702,"label":703,"issuer":704,"region":164,"url":705,"description":706,"useCases":501,"indexable":265},"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":708,"label":709,"issuer":163,"region":164,"url":710,"description":711,"useCases":501,"indexable":265},"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":713,"label":714,"issuer":163,"region":164,"url":715,"description":716,"useCases":501,"indexable":265},"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":718,"label":719,"issuer":174,"region":175,"url":720,"description":721,"useCases":722,"indexable":265},"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.",10,{"id":724,"label":725,"issuer":726,"region":361,"url":727,"description":728,"useCases":77,"indexable":265},"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.",{"id":730,"label":731,"issuer":163,"region":164,"url":732,"description":733,"useCases":77,"indexable":265},"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":735,"label":736,"issuer":737,"region":414,"url":738,"description":739,"useCases":740,"indexable":265},"cbuae-ai-guidance","CBUAE guidance on AI and ML","Central Bank of the UAE","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":157,"label":742,"issuer":169,"region":164,"url":170,"description":743,"useCases":744,"indexable":265},"UK APP scam reimbursement rules","Mandatory reimbursement of authorised push payment scam victims by UK payment firms, which shifts scam losses onto banks.",5,{"id":746,"label":747,"issuer":163,"region":164,"url":748,"description":749,"useCases":76,"indexable":265},"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":751,"label":752,"issuer":753,"region":164,"url":754,"description":755,"useCases":76,"indexable":265},"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":757,"label":758,"issuer":759,"region":175,"url":760,"description":761,"useCases":516,"indexable":265},"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":763,"label":764,"issuer":163,"region":164,"url":765,"description":766,"useCases":516,"indexable":265},"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":158,"label":768,"issuer":174,"region":175,"url":176,"description":769,"useCases":516,"indexable":265},"MAS Shared Responsibility Framework","Singapore's framework that assigns banks and telcos duties and loss sharing for phishing scams.",{"id":771,"label":772,"issuer":773,"region":361,"url":774,"description":775,"useCases":516,"indexable":265},"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.",1792049859512]