[{"data":1,"prerenderedAt":690},["ShallowReactive",2],{"uc-fraud-alert-confirmation":3,"uc-regulations":486},{"useCase":4,"evidence":228,"blitsAiDeployments":388,"benchmarks":389,"indicative":404,"related":407,"indexability":484,"includeUnpublished":234},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":16,"functions":19,"patterns":22,"channels":26,"audience":31,"autonomy":32,"adoptionStage":33,"segment":34,"problem":35,"problemStats":36,"howItWorks":37,"valueDrivers":38,"kpis":43,"indicativeValue":49,"macroEstimates":107,"feasibility":108,"implementation":122,"risk":165,"blitsAi":205,"faq":207,"related":217,"datePublished":223,"dateModified":223,"lastVerified":223,"changelog":224,"slug":227},"AI agent for fraud alert confirmation with cardholders","Fraud alert confirmation","AI agents for fraud alert confirmation","An AI agent asks the cardholder to confirm a flagged card transaction, then lifts the block or freezes the card. Includes in app and verified call examples.","published","A customer facing AI agent that contacts the cardholder as soon as the fraud engine flags a card transaction, in the channel they actually respond to, verifies them, asks whether they made the transaction and acts on the answer: releasing the block so a retry succeeds, or freezing the card and starting the fraud claim.",[12,13,14,15],"suspicious transaction confirmation","transaction verification agent","fraud verification outreach","was this you alert",[17,18],"banking","payments",[20,21],"fraud-prevention","customer-service",[23,24,25],"conversational-agent","voice-agent","agentic-workflow",[27,28,29,30],"mobile-app","sms","voice","whatsapp","customer-facing","supervised-agent","emerging","front-office","A fraud model that stops a card transaction cannot be certain the cardholder did not make it. When\nthe customer did make it, the block interrupts a genuine purchase, often while they are still at\nthe checkout, and they need an answer before they give up or pay another way. If confirmation\ndepends on a person calling back, it can take longer than the customer stays at the checkout, and\na call from an unknown number asking about their card looks much like the scams customers are\nwarned about.\n\nThe confirmation step is therefore both a revenue problem (a genuine purchase that is declined is\nspend the issuer may not get back) and a security problem. Scammers send text messages that\nimpersonate legitimate businesses (the reason Commonwealth Bank gives for moving some card\nverification into its app), spoof the bank's\nphone numbers (Westpac has put 94,000 of its numbers on a Do Not Originate list) and can clone a\nvoice well enough to pass a voice identity check, as a journalist showed against Lloyds Bank's\nVoice ID in 2023. The job is to confirm quickly, in a channel the customer trusts, without\ncreating a new route for scammers.",[],"1. **Trigger from the scoring engine.** A flagged authorization or a card placed on hold starts\n   the agent, with the transaction details and the risk reason.\n2. **Pick the trusted channel.** The first choice is a push into the bank's app, where the\n   customer is already authenticated. Commonwealth Bank now asks app users to verify certain online\n   card transactions in the app instead of sending a code, because it can give clearer warnings\n   there than in a text message. Then two way messaging, then an outbound call that is branded and\n   verified (Westpac's SafeCall places calls through its app that show the reason for the call).\n3. **Verify, never collect secrets.** The agent confirms identity through the app or a strong\n   factor, never asks for a passcode, PIN or full card number, and treats the voice on the line as\n   untrusted.\n4. **Ask one clear question.** \"Did you try to pay 84.90 EUR at this merchant at 14:02?\" with the\n   merchant's clear name and location.\n5. **Act on the answer.** Yes: lift the block, allow the retry and tune the rule for this\n   customer. No: freeze the card, order a replacement and open the fraud claim. Unsure, or signs\n   that someone is guiding the customer: route to a scam specialist.\n6. **Handle silence.** No response within the set time keeps the block in place and follows the\n   bank's contact policy.\n7. **Log and learn.** Every alert, answer and action is recorded and fed back to the fraud team as\n   labelled outcomes.",[39,40,41,42],"risk-reduction","customer-experience","cost-to-serve","revenue-growth",[44,45,46,47,48],"false-positive-reduction","fraud-loss-reduction","response-time-reduction","automation-rate","customer-satisfaction",{"referenceOrg":50,"inputs":51,"formula":103,"currency":95,"period":104,"resultLabel":105,"caveat":106},"A card issuer with 1 million active cards",[52,57,64,71,78,84,90,96],{"key":53,"label":54,"low":55,"high":55,"unit":53,"note":56},"cards","Active cards",1000000,"The reference issuer.",{"key":58,"label":59,"low":60,"high":61,"unit":62,"note":63},"alertsPerCard","Fraud alerts needing customer confirmation per card per year",0.2,0.5,"alerts per card per year","Editorial assumption, replace with your own alert volume.",{"key":65,"label":66,"low":67,"high":68,"unit":69,"note":70},"agentResolvedShare","Share of alerts confirmed by the agent without a human call",0.3,0.6,"fraction of alerts","Editorial assumption; depends on app adoption and on how many alerts need a specialist.",{"key":72,"label":73,"low":74,"high":75,"unit":76,"note":77},"costPerCall","Cost of a human confirmation call",3,6,"USD per call","Editorial assumption, replace with your own fully loaded cost.",{"key":79,"label":80,"low":81,"high":82,"unit":69,"note":83},"genuineShare","Share of alerts that are genuine customer transactions",0.7,0.9,"Editorial assumption, replace with your own alert outcomes.",{"key":85,"label":86,"low":60,"high":87,"unit":88,"note":89},"recoveredShare","Share of genuine blocked spend recovered by fast confirmation",0.4,"fraction of genuine alerts","Editorial assumption.",{"key":91,"label":92,"low":93,"high":94,"unit":95,"note":89},"avgTransaction","Average value of a flagged genuine transaction",50,100,"USD",{"key":97,"label":98,"low":99,"high":100,"unit":101,"note":102},"marginRate","Issuer revenue as a share of spend",0.01,0.015,"fraction of spend","Editorial assumption covering interchange and related income.","cards * alertsPerCard * (agentResolvedShare * costPerCall + genuineShare * recoveredShare * avgTransaction * marginRate)","per year","Confirmation call cost avoided plus revenue from recovered genuine spend","Leaves out fraud losses prevented by faster freezes, the lifetime value of customers who would otherwise switch cards after a false decline, messaging and telephony costs and the cost of the AI and integration.",[],{"complexity":109,"complexityNote":110,"dataPrerequisites":111,"integrations":116},"medium","The logic is simple; the timing is not. The agent must be triggered by the scoring engine in seconds, reach the customer in a trusted channel and change the card's status through the card platform before the customer gives up at the checkout.",[112,113,114,115],"Real time alert feed with transaction and merchant details and the risk reason","Verified contact channels and app enrolment per customer","Contact policy per alert type (channels, timing, retries, quiet hours)","Labelled outcomes of past alerts to measure false positives",[117,118,119,120,121],"Fraud scoring engine and alert queue","Card management platform (release, freeze, replace, rule tuning)","App push and in app authentication","Messaging and telephony with branded or verifiable calling","Fraud claim and dispute case system",{"steps":123,"guardrails":139,"humanInTheLoop":145,"kpisToInstrument":146,"failureModes":152},[124,127,130,133,136],{"title":125,"detail":126},"Move confirmation into the app first","The app is authenticated and hard to spoof. Make an in app confirmation the default and keep other channels as fallbacks for customers without the app. Commonwealth Bank, for example, now asks app users to verify certain online card transactions in the app instead of sending a one time passcode.",{"title":128,"detail":129},"Write the no secrets rule into everything","The agent never asks for a passcode, PIN or card number and tells the customer so in every message. This protects customers from scammers copying your alert.",{"title":131,"detail":132},"Close the loop with the card platform","A yes must lift the block in seconds and a no must freeze and reissue. Test both paths end to end, including the retry at the merchant.",{"title":134,"detail":135},"Connect to scam and dispute journeys","A customer who is unsure, or who describes being guided by someone, goes to a scam specialist; a confirmed fraud goes straight into the fraud claim with the details captured.",{"title":137,"detail":138},"Measure false declines, not only fraud","Track genuine transactions recovered and customers lost after a decline, alongside fraud caught, so the fraud team tunes for both.",[140,141,142,143,144],"No collection of passcodes, PINs, full card numbers or remote access in any channel","Outbound calls are verifiable in the app or come from a registered, branded number","Voice alone is never accepted as proof of identity","Freeze and reissue actions only through the card platform's allow listed APIs","Scam signals or uncertainty route to a human specialist","Fraud specialists handle uncertain answers, suspected scams, vulnerable customers and any case where the customer disputes the agent's action. The fraud team reviews alert outcomes weekly to tune rules, and approves any change to the contact policy or the actions the agent may take.",[147,148,149,150,151],"Median time from alert to customer answer, by channel","Share of alerts resolved without a human call","Genuine transactions recovered after confirmation","Fraud losses on alerted transactions","Complaints and satisfaction after a confirmation contact",[153,156,159,162],{"title":154,"detail":155},"Your alert becomes the scammer's template","Scammers copy the wording and ask for a code. Never request secrets, say so in every alert and prefer in app confirmation.",{"title":157,"detail":158},"Slow confirmation","The answer arrives after the customer has left the checkout. Trigger in real time and prioritise the fastest trusted channel.",{"title":160,"detail":161},"Voice clone accepted as the customer","A cloned voice passes a voice check. Confirm through the app or another strong factor, not the voice.",{"title":163,"detail":164},"Silence treated as consent","No answer must never release a block. Keep it in place and follow the contact policy.",{"euAiAct":166,"regulations":169,"guidance":177,"controls":194,"incidents":200},{"tier":167,"basis":168},"limited","Confirming flagged transactions with cardholders is not listed in Annex III, and point 5(b) expressly excludes AI used to detect financial fraud from the creditworthiness category, so the system is not high risk. An agent that messages or calls customers must tell them they are dealing with AI under Article 50(1), and synthetic voice output must be marked as AI generated under Article 50(2).",[170,171,172,173,174,175,176],"eu-ai-act","gdpr","pci-dss","uk-consumer-duty","dora","eu-psd2","us-tcpa",[178,184,188],{"title":179,"issuer":180,"region":181,"url":182,"note":183},"Declaratory ruling on AI generated voices under the TCPA (FCC 24-17)","Federal Communications Commission","north-america","https://docs.fcc.gov/public/attachments/FCC-24-17A1.pdf","Confirms that AI technologies that generate human voices count as an \"artificial or prerecorded voice\" under the TCPA, so US outbound AI voice calls fall under the TCPA's consent rules unless an exemption applies.",{"title":185,"issuer":180,"region":181,"url":186,"note":187},"TCPA Omnibus Declaratory Ruling and Order (FCC 15-72)","https://docs.fcc.gov/public/attachments/FCC-15-72A1.pdf","Exempts from the TCPA's consent requirements, with conditions, certain calls and texts from financial institutions to mobile numbers about transactions that suggest a risk of fraud, provided they are free to the recipient and limited to three per event over three days.",{"title":189,"issuer":190,"region":191,"url":192,"note":193},"Annex III, high risk AI systems referred to in Article 6(2)","European Union","europe","https://artificialintelligenceact.eu/annex/3/","Point 5(b) excludes AI systems used for detecting financial fraud from the creditworthiness high risk category.",[195,196,197,198,199],"AI disclosure in every automated message and call","Documented contact policy per alert type with quiet hours and retry limits","Audit log of every alert, answer, identity check and card action","Regular tests of the alert channel against impersonation and spoofing","Monitoring of false positive rates and outcomes for vulnerable customers",[201],{"title":202,"url":203,"note":204},"How I Broke Into a Bank Account With an AI-Generated Voice","https://www.vice.com/en/article/how-i-broke-into-a-bank-account-with-an-ai-generated-voice/","In February 2023 a Vice journalist used an AI generated copy of his own voice to pass Lloyds Bank's Voice ID check and reach his account, which is why voice alone should not verify a customer in a fraud confirmation call.",{"howToBuild":206},"On Blits.ai the fraud engine triggers an **agentic workflow** through its API token when an alert\nfires, and uses **custom functions** to read the alert and to release or freeze the card through\nthe card platform's APIs. The bank's own notification service sends the push or message that\nstarts the contact. The confirmation conversation then runs in the bank's app (connected through\nthe **REST API or WebSocket API channel**), or on **WhatsApp**, **SMS** or a **voice** line when\nthe customer replies or calls in that channel. A **flow** fixes the confirmation script with an\n**authentication** step and **DTMF** input on the phone, and the **AI agent** handles free text\nanswers and questions.\n\nActions above a set threshold, such as a reissue, can require **human in the loop approval**, and\n**human handover** sends uncertain or scam cases to a specialist with the transcript. **Guardrails**\nblock any request for secrets in generated messages, and **PII masking** and card number\ntokenization keep card data out of prompts. **Monitors** check the alert path on a schedule,\n**test suites** replay confirmation scenarios on every change, and **analytics** show response\ntimes and outcomes per channel.",[208,211,214],{"question":209,"answer":210},"Should fraud confirmation use calls, SMS or the app?","The app first, because the customer is already authenticated there and it is hard to spoof. Commonwealth Bank now asks app users to verify certain online card transactions in the app instead of sending a code, because it can give clearer warnings there. Keep messaging and calls as fallbacks for customers without the app.",{"question":212,"answer":213},"Can an AI agent unblock a card on its own?","For a clear \"yes, that was me\" from an authenticated customer, releasing the block within set limits is a reasonable automated action. A freeze after a clear \"no\" can also be automated because it is reversible, while a reissue can go through human approval above a set threshold. Anything uncertain, or with signs of a scam, should go to a person.",{"question":215,"answer":216},"How do you stop scammers imitating the alert?","Never ask for passcodes or card details, say so in every alert, and move confirmation into the app or to verifiable calls. Westpac, for example, places branded calls through its app that are verified by Optus and show the reason for the call, and has put 94,000 of its numbers on a Do Not Originate list so scammers cannot display them.",[218,219,220,221,222],"real-time-fraud-scoring","fraud-alert-triage","scam-payment-interception","card-dispute-and-chargeback-intake","proactive-outbound-engagement-agent","2026-09-27",[225],{"date":223,"note":226},"First published","fraud-alert-confirmation",[229,257,311,335,364],{"title":230,"useCases":231,"organization":232,"vendors":236,"summary":239,"stage":240,"year":241,"channels":242,"languages":244,"metrics":246,"outcomeDisclosed":234,"sources":247,"verification":251,"grade":254,"id":255,"organizationSlug":256},"Capital One: Eno assistant alerts on unexpected card charges",[227,222],{"name":233,"anonymized":234,"country":235,"region":181,"industry":17},"Capital One",false,"US",[237],{"name":233,"role":238},"in-house","Eno is Capital One's virtual assistant. Capital One says it helps protect card accounts by looking out for charges that might surprise the customer, and sends insights when it spots free trials and recurring charges, through text, email and app alerts. Capital One does not publish outcome figures for Eno on this page.","production",2026,[28,243,27],"email",[245],"en",[],[248],{"url":249,"title":250,"publisher":233},"https://www.capitalone.com/digital/tools/eno/","Eno, your Capital One assistant",{"level":252,"checkedAt":253},"source-verified","2026-09-26","B","capital-one-eno-assistant",null,{"title":258,"useCases":259,"organization":260,"vendors":264,"summary":268,"stage":269,"year":270,"channels":271,"languages":273,"metrics":274,"outcomeDisclosed":296,"sources":297,"verification":308,"grade":254,"id":309,"organizationSlug":310},"Commonwealth Bank: proactive scam warnings, in app transaction verification and a fraud detection agent",[220,227,218],{"name":261,"anonymized":234,"country":262,"region":263,"industry":17},"Commonwealth Bank of Australia","AU","asia-pacific",[265],{"name":266,"role":267},"Snowflake","platform","Commonwealth Bank combines several AI controls against scams and fraud. Its fraud systems monitor more than 80 million signals a day and the CommBank app sends proactive warning alerts on payments that look risky; NameCheck and Confirmation of Payee check payee details on first time payments. From August 2025 customers are asked to verify certain online card transactions in the app, in real time, before they are authorised. In April 2026 the bank described an agentic system that spots emerging fraud patterns and proposes new detection rules, which the fraud analytics team reviews and approves before they go live. The bank reports a 76% fall in customer scam losses since their peak without attributing it to any single tool, and says its fraud detection technology played a role in cutting fraud losses by over 20% in the first half of FY26.","scaled",2025,[27,272],"api",[245],[275,284,292],{"kpi":45,"value":276,"unit":277,"qualifier":278,"period":279,"baseline":280,"claimant":281,"quote":282,"sourceUrl":283},76,"percent","exact","second half of FY25 versus first half of FY23 (the peak)","customer scam losses at their peak in the first half of FY23","organization","CommBank has seen a 76% drop in customer scam losses since peak (2H25 vs. 1H23)","https://www.commbank.com.au/articles/newsroom/2025/08/commbank-customer-scam-losses-fall-truyu.html",{"kpi":285,"value":286,"unit":287,"qualifier":288,"period":289,"claimant":281,"quote":290,"sourceUrl":291},"interactions-handled",40000,"count","at-least","per day on average, proactive warning alerts in the CommBank app","Each day, CommBank processes more than 20 million payments on average and sends more than 40,000 proactive warning alerts on average to customers via the CommBank app.","https://www.commbank.com.au/articles/newsroom/2026/04/ai-agent-spots-fraud-in-real-time.html",{"kpi":45,"value":293,"unit":277,"qualifier":288,"period":294,"claimant":281,"quote":295,"sourceUrl":291},20,"first half of FY26 versus first half of FY25","The bank’s fraud detection technology has played a role in helping to reduce fraud losses by over 20% in the first half of the 2026 financial year compared to the first half of the 2025 financial year.",true,[298,301,304],{"url":283,"title":299,"publisher":261,"date":300},"CBA sees customer scam losses fall by 76% and adds two new forms of armour to help keep customers safe","2025-08-11",{"url":291,"title":302,"publisher":261,"date":303},"CommBank develops AI agent that spots new fraud and helps build defences","2026-04-24",{"url":305,"title":306,"publisher":261,"date":307},"https://www.commbank.com.au/articles/newsroom/2025/07/scam-protection-confirmation-of-payee.html","Strengthening scam protection: Introducing Confirmation of Payee","2025-07-02",{"level":252,"checkedAt":253},"commonwealth-bank-scam-and-fraud-interventions","commonwealth-bank-of-australia",{"title":312,"useCases":313,"organization":314,"vendors":316,"summary":318,"stage":319,"year":270,"channels":320,"languages":322,"metrics":323,"outcomeDisclosed":234,"sources":324,"verification":333,"grade":254,"id":334,"organizationSlug":256},"Westpac: real time AI call assistant for scam conversations",[220,227],{"name":315,"anonymized":234,"country":262,"region":263,"industry":17},"Westpac",[317],{"name":315,"role":238},"In May 2025 Westpac announced that it was piloting an AI call assistant with its specialist scam and fraud team. It transcribes live customer calls, flags indicators that the customer may be about to pay a scammer or is being coached in the background, and suggests questions for the banker. It sits alongside SaferPay (questions before high risk payments), SafeCall (verified calls through the app to resist spoofing), Westpac Verify (payee name mismatch warnings) and inbound payment detection. The bank reports early qualitative results only.","pilot",[29,321],"agent-desktop",[245],[],[325,329],{"url":326,"title":327,"publisher":315,"date":328},"https://www.westpac.com.au/about-westpac/media/media-releases/2025/29-may/","Using AI to put scammers out of business","2025-05-29",{"url":330,"title":331,"publisher":332,"date":328},"https://www.westpac.com.au/news/making-news/2025/05/westpac-deploys-real-time-AI-to-take-on-scammers/","Westpac deploys real-time AI to take on scammers","Westpac Wire",{"level":252,"checkedAt":253},"westpac-scam-call-assistant",{"title":336,"useCases":337,"organization":338,"vendors":341,"summary":343,"stage":240,"year":344,"channels":345,"languages":346,"metrics":347,"outcomeDisclosed":296,"sources":353,"verification":362,"grade":254,"id":363,"organizationSlug":256},"Revolut: AI card scam detection with an in app intervention flow",[220,227,218],{"name":339,"anonymized":234,"country":340,"region":191,"industry":17},"Revolut","GB",[342],{"name":339,"role":238},"In February 2024 Revolut launched a machine learning feature, built by its financial crime team, that estimates whether a card payment is part of a scam. When the risk is high it declines the payment, blocks similar payments and sends the customer through an in app intervention flow that asks about the payment, checks whether someone is guiding them, shows scam stories and offers a chat with a fraud specialist.",2024,[27],[245],[348],{"kpi":45,"value":349,"unit":277,"qualifier":278,"period":350,"claimant":281,"quote":351,"sourceUrl":352},30,"since launch, fraud losses from card scams where money was sent for investment opportunities","Since the launch of the card scam detection feature, Revolut has observed a 30% reduction in the fraud losses resulting from card scams where money has been sent for investment opportunities.","https://www.revolut.com/en-US/news/revolut_launches_ai_feature_to_protect_customers_from_card_scams_and_break_the_scammers_spell/",[354,358],{"url":352,"title":355,"publisher":339,"date":356,"archivedUrl":357},"Revolut launches AI feature to protect customers from card scams and break the scammers \"spell\"","2024-02-15","https://web.archive.org/web/20250917122343/https://www.revolut.com/en-US/news/revolut_launches_ai_feature_to_protect_customers_from_card_scams_and_break_the_scammers_spell/",{"url":359,"title":360,"publisher":361,"date":356},"https://www.openbankingexpo.com/news/revolut-introduces-new-ai-powered-card-scam-detection-feature/","Revolut introduces AI-powered card scam detection feature","Open Banking Expo",{"level":252,"checkedAt":253},"revolut-card-scam-detection",{"title":365,"useCases":366,"organization":367,"vendors":369,"summary":372,"stage":240,"year":270,"channels":373,"languages":374,"metrics":375,"outcomeDisclosed":296,"sources":382,"verification":385,"grade":386,"id":387,"organizationSlug":256},"Macquarie Bank: AI fraud protection alerts and self service search",[227],{"name":368,"anonymized":234,"country":262,"region":263,"industry":17},"Macquarie Bank",[370],{"name":371,"role":267},"Google Cloud","Macquarie Bank uses Google Cloud AI for proactive fraud protection and digital self service. Google Cloud reports that the bank cut false positive alerts for client protection and that its help centre search sent more users to self service. The source does not say which channels carry the alerts.",[272],[245],[376],{"kpi":44,"value":377,"unit":277,"qualifier":278,"period":378,"claimant":379,"quote":380,"sourceUrl":381},40,"not stated","vendor","Macquarie Bank uses Google Cloud AI to enable efficient and proactive fraud protection and digital self-service capabilities — their Help Centre Search directed 38% more users towards self-service and they reduced false positive alerts for client protection by 40%.","https://cloud.google.com/transform/101-real-world-generative-ai-use-cases-from-industry-leaders",[383],{"url":381,"title":384,"publisher":371},"1,302 real-world gen AI use cases from the world's leading organizations",{"level":252,"checkedAt":253},"C","macquarie-bank-fraud-protection-and-self-service",0,[390,398],{"kpi":45,"label":391,"unit":277,"aggregate":296,"higherIsBetter":296,"n":392,"nUpTo":388,"median":393,"min":349,"max":276,"byClaimant":394,"vendorOnly":234,"points":395},"Fraud loss reduction",2,53,{"organization":392,"vendor":388,"regulator":388,"independent":388},[396,397],{"evidenceId":309,"organization":261,"value":276,"qualifier":278,"claimant":281,"grade":254,"pooled":296},{"evidenceId":363,"organization":339,"value":349,"qualifier":278,"claimant":281,"grade":254,"pooled":296},{"kpi":44,"label":399,"unit":277,"aggregate":296,"higherIsBetter":296,"n":400,"nUpTo":388,"median":377,"min":377,"max":377,"byClaimant":401,"vendorOnly":296,"points":402},"False positive reduction",1,{"organization":388,"vendor":400,"regulator":388,"independent":388},[403],{"evidenceId":387,"organization":368,"value":377,"qualifier":278,"claimant":379,"grade":386,"pooled":296},{"low":405,"high":406},193999.99999999997,2069999.9999999998,[408,431,446,461,472],{"slug":218,"title":409,"shortTitle":410,"definition":411,"status":9,"industries":412,"functions":413,"patterns":414,"audience":417,"autonomy":418,"adoptionStage":419,"segment":420,"evidenceCount":421,"publicEvidenceCount":421,"organizations":422,"bestGrade":254,"headline":429,"lastVerified":223,"indexable":296},"Real time fraud scoring for card and instant payments","Real time fraud scoring","Machine learning that decides in milliseconds, without any conversation, how likely each card authorization and account to account payment is to be fraudulent, combining behavioural, 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.",[17,18],[20],[415,416],"prediction-and-scoring","anomaly-detection","back-office","autonomous","mainstream","middle-office",9,[423,261,424,425,426,339,427,428],"ANZ, Commonwealth Bank, NAB, Suncorp Bank and Westpac (BioCatch Trust Australia)","Mastercard","NatWest Group","Pay.UK","Stripe","Visa",{"kpi":45,"label":391,"unit":277,"n":74,"nUpTo":388,"kind":430,"value":349,"qualifier":278,"claimant":281,"organization":256,"vendorReported":234},"median",{"slug":219,"title":432,"shortTitle":433,"definition":434,"status":9,"industries":435,"functions":436,"patterns":438,"audience":441,"autonomy":32,"adoptionStage":442,"segment":420,"evidenceCount":74,"publicEvidenceCount":392,"organizations":443,"bestGrade":386,"headline":256,"lastVerified":223,"indexable":296},"AI agent for fraud alert triage","Fraud alert triage","An AI agent that works the fraud alert queue behind the scenes as the analyst's first pass, without contacting the customer: it enriches each alert with customer, device and payment context, closes clear false positives under documented rules, merges duplicates, and routes genuine risk to an analyst with a drafted rationale.",[17,18],[20,437],"operations",[25,439,440,415],"classification-and-routing","summarization","employee-facing","early-adopters",[444,445],"Coast","SEB",{"slug":220,"title":447,"shortTitle":448,"definition":449,"status":9,"industries":450,"functions":451,"patterns":452,"audience":31,"autonomy":32,"adoptionStage":442,"segment":34,"evidenceCount":75,"publicEvidenceCount":75,"organizations":453,"bestGrade":254,"headline":456,"lastVerified":253,"indexable":296},"AI scam intervention for instant payments","Scam payment interception","AI that talks to the customer when they are about to authorise 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.",[17,18],[20,21],[23,415,25,24],[261,424,339,454,455,315],"Starling Bank","Vodafone",{"kpi":457,"label":458,"unit":277,"n":392,"nUpTo":388,"kind":459,"value":460,"qualifier":278,"claimant":379,"organization":454,"vendorReported":296},"detection-rate-improvement","Detection improvement","reported",300,{"slug":221,"title":462,"shortTitle":463,"definition":464,"status":9,"industries":465,"functions":466,"patterns":467,"audience":31,"autonomy":32,"adoptionStage":442,"segment":34,"evidenceCount":469,"publicEvidenceCount":74,"organizations":470,"bestGrade":254,"headline":256,"lastVerified":223,"indexable":296},"AI agent for card dispute intake","Card dispute intake","A customer facing AI agent that handles the \"I do not recognise this charge\" moment: it finds the transaction, separates suspected fraud from merchant disputes and simple confusion, explains the customer's rights and timelines, collects the details and evidence the rules require, and opens a correctly classified dispute case for the operations team.",[17,18],[21,20,437],[23,24,439,468,25],"document-processing",4,[261,471,428],"Klarna",{"slug":222,"title":473,"shortTitle":474,"definition":475,"status":9,"industries":476,"functions":477,"patterns":480,"audience":31,"autonomy":32,"adoptionStage":33,"segment":34,"evidenceCount":74,"publicEvidenceCount":74,"organizations":482,"bestGrade":254,"headline":256,"lastVerified":223,"indexable":296},"AI agent for proactive customer outreach, activation and retention","Proactive outreach and activation","An AI agent that holds the conversation when a bank reaches out first to change something about the customer's account or products, triggered by an event or a campaign: low balance and fee avoidance alerts, payment and renewal reminders, card activation, dormant account reactivation and offers the customer already qualifies for, over messaging or voice, while the bank's own systems decide who is contacted and why. Reminders about appointments and deliveries the customer booked, and the in app coach the customer opens, are separate use cases.",[17,18],[478,479,21],"marketing","sales",[23,24,25,481],"recommendation-and-personalization",[483,233,261],"Bank of America",{"indexable":296,"reasons":485},[],[487,492,497,505,512,517,524,530,537,544,549,555,562,569,575,580,587,593,599,605,611,615,621,626,630,636,643,648,653,661,667,673,679,684],{"id":170,"label":488,"issuer":190,"region":191,"url":489,"description":490,"useCases":491,"indexable":296},"EU AI Act","https://eur-lex.europa.eu/eli/reg/2024/1689/oj","Regulation (EU) 2024/1689: risk based rules for AI systems, with obligations for high risk systems listed in Annex III and transparency duties under Article 50.",197,{"id":171,"label":493,"issuer":190,"region":191,"url":494,"description":495,"useCases":496,"indexable":296},"GDPR","https://eur-lex.europa.eu/eli/reg/2016/679/oj","General Data Protection Regulation, including Article 22 on decisions based solely on automated processing.",180,{"id":498,"label":499,"issuer":500,"region":501,"url":502,"description":503,"useCases":504,"indexable":296},"iso-42001","ISO/IEC 42001","ISO and IEC","global","https://www.iso.org/standard/81230.html","The international management system standard for AI.",110,{"id":506,"label":507,"issuer":508,"region":181,"url":509,"description":510,"useCases":511,"indexable":296},"nist-ai-rmf","NIST AI Risk Management Framework","NIST","https://www.nist.gov/itl/ai-risk-management-framework","Voluntary US framework to map, measure, manage and govern AI risk, with a generative AI profile.",83,{"id":174,"label":513,"issuer":190,"region":191,"url":514,"description":515,"useCases":516,"indexable":296},"DORA","https://eur-lex.europa.eu/eli/reg/2022/2554/oj","Digital Operational Resilience Act for financial entities: ICT risk, incident reporting and third party risk, including AI providers.",66,{"id":518,"label":519,"issuer":520,"region":191,"url":521,"description":522,"useCases":523,"indexable":296},"uk-gdpr","UK GDPR","Information Commissioner's Office","https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/","The UK's version of the GDPR, including rules on solely automated decisions.",64,{"id":173,"label":525,"issuer":526,"region":191,"url":527,"description":528,"useCases":529,"indexable":296},"FCA Consumer Duty","Financial Conduct Authority","https://www.fca.org.uk/firms/consumer-duty","UK rules that require firms to deliver good outcomes for retail customers, including through automated channels.",47,{"id":531,"label":532,"issuer":533,"region":263,"url":534,"description":535,"useCases":536,"indexable":296},"mas-ai-risk-management","MAS AI risk management guidelines","Monetary Authority of Singapore","https://www.mas.gov.sg/news/media-releases/2025/mas-guidelines-for-artificial-intelligence-risk-management","Singapore's supervisory expectations for AI risk management at financial institutions, building on the FEAT principles.",36,{"id":538,"label":539,"issuer":540,"region":263,"url":541,"description":542,"useCases":543,"indexable":296},"apra-cps-230","APRA CPS 230","Australian Prudential Regulation Authority","https://www.apra.gov.au/operational-risk-management","Australian operational risk standard covering critical operations and material service providers.",25,{"id":172,"label":545,"issuer":546,"region":501,"url":547,"description":548,"useCases":293,"indexable":296},"PCI DSS","PCI Security Standards Council","https://www.pcisecuritystandards.org/","Security standard for any system that stores, processes or transmits cardholder data.",{"id":550,"label":551,"issuer":552,"region":181,"url":553,"description":554,"useCases":293,"indexable":296},"us-sr-11-7","SR 11-7 model risk management","Federal Reserve and OCC","https://www.federalreserve.gov/boarddocs/srletters/2011/sr1107.htm","US supervisory guidance on model risk management, applied by banks to AI and machine learning models.",{"id":556,"label":557,"issuer":558,"region":191,"url":559,"description":560,"useCases":561,"indexable":296},"uk-atrs","UK Algorithmic Transparency Recording Standard","UK Government","https://www.gov.uk/government/collections/algorithmic-transparency-recording-standard-hub","Mandatory transparency records for algorithmic tools used by UK central government.",16,{"id":563,"label":564,"issuer":565,"region":501,"url":566,"description":567,"useCases":568,"indexable":296},"fatf-recommendations","FATF Recommendations","Financial Action Task Force","https://www.fatf-gafi.org/en/publications/Fatfrecommendations/Fatf-recommendations.html","Global standards for anti money laundering and counter terrorist financing that national rules implement.",15,{"id":570,"label":571,"issuer":190,"region":191,"url":572,"description":573,"useCases":574,"indexable":296},"eu-amlr","EU Anti Money Laundering Regulation","https://eur-lex.europa.eu/eli/reg/2024/1624/oj","Regulation (EU) 2024/1624: the single EU rulebook for customer due diligence, beneficial ownership and suspicious transaction reporting.",14,{"id":576,"label":577,"issuer":190,"region":191,"url":578,"description":579,"useCases":574,"indexable":296},"nis2","NIS2 Directive","https://eur-lex.europa.eu/eli/dir/2022/2555/oj","Directive (EU) 2022/2555 on cybersecurity for essential and important entities, including telecom networks, energy and public administration.",{"id":581,"label":582,"issuer":583,"region":181,"url":584,"description":585,"useCases":586,"indexable":296},"us-bsa","Bank Secrecy Act","FinCEN","https://www.fincen.gov/resources/statutes-and-regulations/bank-secrecy-act","US anti money laundering law: customer due diligence, suspicious activity reports and record keeping.",13,{"id":588,"label":589,"issuer":190,"region":191,"url":590,"description":591,"useCases":592,"indexable":296},"eu-accessibility-act","European Accessibility Act","https://eur-lex.europa.eu/eli/dir/2019/882/oj","Directive (EU) 2019/882: accessibility requirements for banking services, ecommerce and other digital services, applicable since June 2025.",12,{"id":594,"label":595,"issuer":596,"region":181,"url":597,"description":598,"useCases":592,"indexable":296},"hipaa","HIPAA","US Department of Health and Human Services","https://www.hhs.gov/hipaa/index.html","US rules for the privacy and security of protected health information.",{"id":600,"label":601,"issuer":602,"region":501,"url":603,"description":604,"useCases":592,"indexable":296},"telecom-consumer-rules","Telecom consumer protection rules","National telecom regulators","https://www.berec.europa.eu/","National rules on telecom contracts, switching, billing disputes and marketing consent.",{"id":606,"label":607,"issuer":190,"region":191,"url":608,"description":609,"useCases":610,"indexable":296},"eecc","European Electronic Communications Code","https://eur-lex.europa.eu/eli/dir/2018/1972/oj","Directive (EU) 2018/1972: consumer protection, contract, switching and security rules for telecom operators.",11,{"id":176,"label":612,"issuer":180,"region":181,"url":613,"description":614,"useCases":610,"indexable":296},"Telephone Consumer Protection Act","https://www.fcc.gov/consumers/guides/stop-unwanted-robocalls-and-texts","US consent rules for automated and prerecorded calls and texts; the FCC has confirmed AI generated voices count as artificial voices.",{"id":616,"label":617,"issuer":533,"region":263,"url":618,"description":619,"useCases":620,"indexable":296},"mas-notice-626","MAS Notice 626","https://www.mas.gov.sg/regulation/notices/notice-626","Singapore's anti money laundering and counter terrorism financing requirements for banks.",10,{"id":622,"label":623,"issuer":190,"region":191,"url":624,"description":625,"useCases":620,"indexable":296},"mifid-ii","MiFID II","https://eur-lex.europa.eu/eli/dir/2014/65/oj","Directive 2014/65/EU on markets in financial instruments: suitability and appropriateness of advice, record keeping and product governance.",{"id":175,"label":627,"issuer":190,"region":191,"url":628,"description":629,"useCases":620,"indexable":296},"PSD2","https://eur-lex.europa.eu/eli/dir/2015/2366/oj","Payment Services Directive 2: strong customer authentication, transaction risk analysis exemptions and open banking access.",{"id":631,"label":632,"issuer":633,"region":191,"url":634,"description":635,"useCases":421,"indexable":296},"eba-loan-origination","EBA Guidelines on loan origination and monitoring","European Banking Authority","https://www.eba.europa.eu/regulation-and-policy/credit-risk/guidelines-on-loan-origination-and-monitoring","Expectations for credit decisioning, including the use of automated models.",{"id":637,"label":638,"issuer":639,"region":181,"url":640,"description":641,"useCases":642,"indexable":296},"us-ecoa-reg-b","ECOA and Regulation B","Consumer Financial Protection Bureau","https://www.consumerfinance.gov/rules-policy/regulations/1002/9/","US fair lending rules, including specific reasons in adverse action notices, which also apply when credit decisions use AI models.",8,{"id":644,"label":645,"issuer":190,"region":191,"url":646,"description":647,"useCases":642,"indexable":296},"solvency-ii","Solvency II","https://eur-lex.europa.eu/eli/dir/2009/138/oj","Directive 2009/138/EC: risk based capital, governance and model requirements for insurers.",{"id":649,"label":650,"issuer":190,"region":191,"url":651,"description":652,"useCases":75,"indexable":296},"eu-idd","Insurance Distribution Directive","https://eur-lex.europa.eu/eli/dir/2016/97/oj","Directive (EU) 2016/97: conduct rules for selling insurance, including demands and needs testing and advice.",{"id":654,"label":655,"issuer":656,"region":657,"url":658,"description":659,"useCases":660,"indexable":296},"cbuae-ai-guidance","CBUAE guidance on AI and ML","Central Bank of the UAE","middle-east","https://www.centralbank.ae/","UAE central bank expectations for the enabling technologies, AI and machine learning used by licensed financial institutions.",5,{"id":662,"label":663,"issuer":664,"region":191,"url":665,"description":666,"useCases":469,"indexable":296},"pra-ss1-23","PRA SS1/23 model risk management","Prudential Regulation Authority","https://www.bankofengland.co.uk/prudential-regulation/publication/2023/may/model-risk-management-principles-for-banks-ss","UK model risk management principles for banks, covering AI and machine learning models.",{"id":668,"label":669,"issuer":670,"region":191,"url":671,"description":672,"useCases":469,"indexable":296},"uk-psr-app-reimbursement","UK APP scam reimbursement rules","Payment Systems Regulator","https://www.psr.org.uk/our-work/app-scams/","Mandatory reimbursement of authorised push payment scam victims by UK payment firms, which shifts scam losses onto banks.",{"id":674,"label":675,"issuer":676,"region":263,"url":677,"description":678,"useCases":74,"indexable":296},"au-scams-prevention-framework","Australian Scams Prevention Framework","Australian Treasury","https://treasury.gov.au/consultation/c2024-573813","Economy wide obligations for banks, telcos and digital platforms to prevent, detect, disrupt and respond to scams.",{"id":680,"label":681,"issuer":190,"region":191,"url":682,"description":683,"useCases":74,"indexable":296},"eu-mar","EU Market Abuse Regulation","https://eur-lex.europa.eu/eli/reg/2014/596/oj","Regulation (EU) 596/2014: insider dealing and market manipulation, including the duty to detect and report suspicious orders and transactions.",{"id":685,"label":686,"issuer":687,"region":181,"url":688,"description":689,"useCases":74,"indexable":296},"us-fcra","Fair Credit Reporting Act","Federal Trade Commission","https://www.ftc.gov/legal-library/browse/statutes/fair-credit-reporting-act","US rules on consumer reports, their accuracy and permissible use, relevant to credit scoring and screening.",1790598294938]