AI-generated fraud doesn't announce itself in a single transaction. It builds, across entities, channels, and time, until the damage is done. In last week's webinar, we brought together risk leaders from Bankingly, epay/Skylight (Euronet), and Brains Capital to talk about what rule-based detection misses, what behavioral signals catch earlier, and what the shift to AI agents actually requires from your governance program. Watch the full session now: buff.ly/ksV6jHH
 #entityrisk #merchantrisk #entityriskintelligence #ai #generativeai #aigeneratedfraud #fraudrisk #fraudprevention #frauddetection #payments #banking #fightfraud

For 2025, the Consumer Federation of America compared $20.8 billion in US consumer fraud losses reported to the FTC with an implied $148.2 billion in actual losses. Your own case records have the same blind spot: a scam that was never reported never becomes a case. Link analysis shows how the cases you did confirm connect to each other, and those connections can point to activity that never reached your caseload. See how in our guide, "Can You See the Network Behind Your Scam Losses?": buff.ly/MYRkUqQ #ScamPrevention #FraudPrevention #LinkAnalysis #FinancialCrime

You can only defend against the scams you can see. Your reported cases show the payment, not what sits behind it. Get the Banking Fact Sheet: buff.ly/AKlwWHc #ScamPrevention #FraudPrevention #Banking

An analyst spots one BIN pattern by hand, then has to go looking for it again tomorrow, and the day after that. Card testing spreads across merchants faster than any manual process can track, and rules tuned to catch one merchant at a time miss the pattern spreading across hundreds. Get the full session here to see what real-time, BIN-level Card Testing Detection looks like instead, catching coordinated attacks automatically instead of one query at a time: buff.ly/ks0XO2x #CardTesting #FraudPrevention #MerchantRisk #PaymentsFraud

What percentage of your confirmed scam cases were linked to another case? Every case reaches your team as one row, with no link to the others in the queue. Meanwhile, the criminal network behind it keeps its accounts, identities and devices, and can reuse them against you. The guide gives you three checks for each of five layers, so you can see where your data can answer that question and where it can't. Get the guide: buff.ly/MYRkUqQ #ScamPrevention #FraudPrevention #LinkAnalysis #MuleAccounts

Scam payments have to land somewhere. A mule account may hold the money for only minutes, but the account shows warning signs the payment does not. What is a money mule? buff.ly/EtNffMt #ScamPrevention #FraudPrevention #Banking

Your scam loss figure is accurate. It also describes only the last step of a longer chain. A reported case is one payment, one beneficiary account and one row in your data. Beneath it sit five layers: mule account intake, identity assembly, device and session reuse, money movement and cash-out, and network coordination. Our new guide, "Can You See the Network Behind Your Scam Losses?", walks through each layer with three checks you can run against your own data. Get the guide: buff.ly/MYRkUqQ #ScamPrevention #FraudPrevention #MuleAccounts #FinancialCrime

Scam losses are counted at the payment. They are stopped underneath it. Get the Banking Fact Sheet: buff.ly/AKlwWHc #ScamPrevention #FraudPrevention #Banking

Finding the right support matters. Explore the Innovator Exchange to see how we can help you implement FedNow® Service solutions and use cases. Visit our profile for more details: buff.ly/ELH7dyi #FedNowInnovatorExchange

Authorized push payment fraud has four stages. Only one of them appears in the payment record. See all four: buff.ly/gcWwrVO #ScamPrevention #FraudPrevention #Banking

We're heading to Money20/20 USA in Las Vegas, Oct 18-21. Book a time to meet with John and Kevin before, during or after the show: buff.ly/6QBf60m #Money2020 #Money2020USA #FraudPrevention #FinTech #fightfraud

Scam losses are counted at the payment. They are stopped underneath it. Get the Banking Fact Sheet: buff.ly/AKlwWHc #ScamPrevention #FraudPrevention #Banking

"The sophistication has gone up. The time and the cost has gone down." That's how FraudNet's Kevin Shine, Head of Sales, described the impact AI has had on card testing during our live webinar. Kevin and Mike Roberts, Head of Client Success, walk through what that shift means for fraud, risk, and compliance teams, and what real-time, BIN-level detection looks like in response. Watch the full conversation: buff.ly/ks0XO2x #CardTesting #PaymentsFraud #FraudPrevention #FraudNet

Enumeration counts against your VAMP ratio before a single chargeback ever posts. Most fraud stacks still catch card testing 30 to 90 days too late. In the full session, FraudNet's Kevin Shine and Mike Roberts, Head of Client Success, break down what real-time, range-level Card Testing Detection means for portfolio-level risk and compliance reporting, and why the shift from reactive to proactive fraud strategy is no longer optional under VAMP. Get the full session here: buff.ly/ks0XO2x #CardTesting #VisaVAMP #FraudPrevention #PaymentsFraud #FraudNet

136,000 fraudulent transactions identified. 344 merchants protected. 97% faster time to detection. That's what one national merchant services provider saw after replacing chargeback-triggered investigation with real-time, range-level Card Testing Detection. Watch the full session to see how AI industrialized card testing, and what real-time detection looks like in response: buff.ly/ks0XO2x #CardTesting #PaymentsFraud #VisaVAMP #FraudPrevention #FraudNet

🔴 TODAY: "How AI Industrialized Card Testing: Why You Need Real-Time Detection." Learn what it takes to catch card testing at the speed AI now runs it, from FraudNet experts Kevin Shine and Mike Roberts, live today at 11:00 AM ET. What are you waiting for? Save your spot now: buff.ly/GbUBThj
 #cardtesting #enumeration #visavamp #merchantrisk #payments #fraudprevention #frauddetection #ai #machinelearning #fightfraud #fraudnet

TOMORROW, DON'T MISS IT: "How AI Industrialized Card Testing: Why You Need Real-Time Detection." Card testing today spreads across hundreds of merchants at once, exactly the pattern most detection is built to miss. Learn what it takes to catch it, from FraudNet experts Kevin Shine and Mike Roberts. Register now: buff.ly/GbUBThj
 #cardtesting #enumeration #visavamp #merchantrisk #payments #fraudprevention #frauddetection #ai #machinelearning #fightfraud #fraudnet

2 DAYS: How AI Industrialized Card Testing: Why You Need Real-Time Detection AI turned card testing into an automated, high-volume attack, so detection has to move at the same speed. Learn how, straight from FraudNet experts Kevin Shine and Mike Roberts. What are you waiting for? Save your seat: buff.ly/GbUBThj
 #cardtesting #enumeration #visavamp #merchantrisk #payments #fraudprevention #frauddetection #ai #machinelearning #fightfraud #fraudnet

ONE WEEK LEFT until our webinar, "How AI Industrialized Card Testing: Why You Need Real-Time Detection." Grab your seat now, before next week's calendar fills in around it. We're holding real time for live Q&A, so bring your questions on card testing, fraud detection, and more: buff.ly/GbUBThj
 #cardtesting #enumeration #visavamp #merchantrisk #payments #fraudprevention #frauddetection #ai #machinelearning #fightfraud #fraudnet

Complete Protection for Modern Payments Secure transactions, protect merchants and customers, and keep your businesses thriving with real-time AI fraud and risk solutions. Protect every transaction with precision risk scoring that identifies and stops fraudulent activity in real-time. Our AI-powered fraud detection ensures safe transactions are processed, more fraud is prevented, and the customer experience is uninterrupted fraud.net/industries/payment… #AI #Payments #Commerce #Paytech

Card testing used to be done by hand, one merchant at a time. AI has since automated that process, finishing in hours instead of days, at a volume no analyst can track by hand. You need real-time, range-level detection, and you need it before it's too late. Join FraudNet's Kevin Shine and Mike Roberts live September 17 at 11am EST to see what it actually takes to catch card testing in real time: detection built to catch coordinated attacks spreading across merchants, not static rules tuned to catch one merchant at a time. Save your seat: buff.ly/zG2oqF0 #cardtesting #enumeration #visavamp #merchantrisk #payments #fraudprevention #frauddetection #ai #machinelearning #fightfraud #fraudnet