Sardine

Just dropped 👀 A comprehensive guide on chargeback reduction and mitigation, revealing some eye-opening insights: For every $100 in chargebacks, merchants face about $240 in costs. That's a 240% loss on each chargeback. The true cost of chargebacks often goes uncalculated. It includes: - Chargeback fees: $15 to $100 per chargeback - Lost merchandise - Transaction fees - Operational costs - Marketing and acquisition costs Chargebacks aren't just about money. They drain resources, erode customer trust, and can even lead to losing your ability to process card payments. The guide offers a strategic approach to tackle this issue: 1. Understand root causes of chargebacks 2. Set up clear and accessible policies 3. Choose the right fraud model 4. Empower your customer support team 5. Build a strong evidence collection process 6. Monitor and measure key metrics 🐟 Fraud Squad tip: Implement the Stoplight Method to categorize risk levels and pre-negotiate responses. It uses green, yellow, red, and orange levels to manage chargeback rates effectively. Remember, winning chargebacks isn't luck. It's a strategic process that can significantly impact your bottom line. Fascinating times for merchants and fraud prevention experts alike! Find it on the blog sardine .ai /blog

Imagine you’re a US citizen visiting family on a vacation to Cuba. When you get there, your US bank account or Fintech account freezes because you’ve entered a country under US Sanctions. Then when you return, you often have to call your institution and go through full KYC to unlock your account. The institution's situation isn’t much better. If they see an alert that a customer is out of the country, they often have to flag it manually for enhanced due diligence (EDD) and then drive a series of KYC workflows. This process always bugged me and I was dying to build a better solution. So we did. How? Here’s how. 👇 👉 Identify a user is in a Sanctioned country at onboarding or login, even if they’re using a VPN or proxy 👉 Automatically route the alert to an Enhanced Due Diligence queue for either manual review, or straight through processing 👉 If additional KYC or step-up authentication is required, trigger that automatically. The user experience gets much slicker, and the compliance teams workload gets a little better. If you’re itching to build better tools for compliance teams, we’re hiring a Senior Compliance PM. I’d love to show you what we have in mind, and get your wildest ideas for what we can build together. Drop me a DM :)

The easiest way to have no fraud is to have no transactions. The ideal balance comes from paying more attention to good users, and training AI with that data. Good users create a baseline. How they behave, how they transact and the devices they use. AI needs data. Give it more high quality data to train on, and balance that with all of your other signals. Behavior at the core of your data-driven fraud prevention is a massive unlock.

The image below is not a real person. Masking attacks became cheaper and more convincing. Open source tools can quickly edit a persons online selfie and be used to pass a KYC test. This is now a common concern we hear from clients. 🐟🐟🐟 One data point that can’t be deepfaked? Your behavior. How you swipe, type and tap the phone is intrinsic to you. That’s why behavior is becoming one of the most important fraud signals for KYC (and any user journey). It’s even more valuable when combined with 1000s of others. All risk problems are data problems.

Most organizations have at least 100x more data on good users than bad. Your results are much better if you train AI on this data set. Then, countless AI techniques combined with the fraud squad's creativity can bust much more fraud. We built Sardine to be behavior at the core, but to work with any other data set. By the fraud squad, for the fraud squad. By data engineers, for data engineers. Matt Vega Head of Fraud Strategy Novo shares more about how this works👇

Apple Pay is amazing, but it killed a tried and true fraud detection technique: The velocity check. When a card is added to Apple Pay, a "DAN" is created. This stands in the way of the "PAN" 16 digit card number that the fraud squad used to detect the velocity of transactions coming from a single card. If a card was making 10, 20 or 30 small transactions at the same merchant it could be suspicious! 🐟🐟🐟 But with Apple Pay, fraudsters can add the same card to multiple iPhone devices. This means the PAN velocity check won't work. Merchants should check with their PSP (Payment Service Provider) or fraud partner to get the "internal card number" or a permanent account number and a corresponding reference to the Apple Pay DAN. 🐟🐟🐟 This is the stuff we live and breathe every day If you're struggling with Apple Pay Come our way 👋

The innovation dividend: Once banks get to the cloud - their ability to adopt new technology increases 10x. They can run PoCs of real-time transaction monitoring, often side-by-side with their legacy solution.

Dinner with 40 people who care deeply about making our industry safer and faster at ACAMS was a blast 💥 Huge thank you to our partner Moody's. ACAMS this year has already been a huge success for us. Here's to many more fraud squad dinners...And matching jackets! Soups Ranjan Kalyani Iyer

🤖 Advanced bot detection can save you from huge downstream issues Historically bot detection was left to the Infosec team, while the fraud team looked at payments. In the middle is a chasm of opportunity for conversion optimization and fraud detection. Advanced bots can steal item descriptions and images to create counterfeit pages, spiking chargebacks. Or they might rapidly create new accounts (new account fraud or NAF).

At Sardine, we pride ourselves on building the tools we wish we had in our past lives. We save risk teams time, effort and frustration. We help payments teams convert more good customers. We help more commerce happen by obsessing over the details. If you're feeling frustrated or held back. Phone a fishy friend 🐟