Sardine

Modern fraud leaves a trail, but it’s rarely all within the same institution. Instead it jumps across channels, payment networks, and fintechs, leaving risk teams with an incomplete view of risk. To truly see the full picture, leveraging cross-industry shared intelligence is critical. After all, the fraudsters are collaborating. We should be too. Dive into this topic with us at the Financial Times Global Banking Summit in London on 2 December. Ravi Loganathan will lead a conversation about how consortium data fills in the gaps to reveal hidden entity risks, mule networks, and coordinated fraud. Check the link in the comments to learn more:

We had the honor of exhibiting at the first ever Fintech NerdCon where our very own Matt Vega, gave a presentation on Scam Typologies. Cheers to Simon Taylor and Colton Pond for putting on an incredible event!

Our very own Matt Vega, will be a panelist and roundtable leader at "Agentic Commerce: Going Beyond the Hype to Build Secure, Effective Solutions for all Parties Involved," hosted by VGS and Vertex Ventures US on December 8th from 5 - 7 pm in San Francisco, CA! https://lnkd.in/g8by4dnA

The Sardine team is heading out to the first-ever Fintech NerdCon in a couple of weeks, and we’d love to jam with you in person. Simon Taylor and the NerdCon team have truly put together THE event for operators who love building, scaling, and tackling the industry's biggest challenges. So we’re going to be hosting interactive sessions all day where you can: - See live demos of modern fraud attacks in action - Learn about what’s happening on the dark web - Workshop your toughest challenges with risk experts - And tinker with AI agents build for fraud & compliance Our very own Matt Vega, 3CI, SIP, ECFE will also be presenting on stage about the latest scams, how they work, and what banks & fintechs can do to stop them. If these topics are top of mind for you, grab some time with our team! https://lnkd.in/eCjwyG9P

AI is breaking financial crime defenses faster than risk teams can fix them. We’re seeing these attacks daily: - AI agents spinning up hundreds of mule accounts - Deepfakes bypassing KYC & live biometric checks - Incorporation docs that are 100% AI-generated - Automated attacks that create endless alerts Legacy FRAML systems just weren’t built for this, and cannot keep up. We’re hosting a live session on Nov 18th with PwC, Nium, and ACAMS to dig into the latest AI-driven threats, and what risk teams can do to stop them. Speakers include: Michael D Jackson, Director of FinCrime Technology at PwC Francisco Mainez, Global Head of Financial Crime Strategy at Nium Kimberly Darpel, CAFS, Sr. Manager of Anti-Financial Crime at ACAMS Glenn Fratangelo, Head of Product Marketing at Sardine Register here: https://lnkd.in/eJecJE6C

Why is it that most UK/EEA banks and fintechs combine fraud and fincrime teams into one team, whereas the two teams are separate in the US? This was a key topic we discussed during our Money2020 Chatham House roundtable. This question was prompted by a conversation I had with Conor Walsh, Monzo US CEO, when we realized that both Revolut and Monzo Bank were similar in combining these two teams. Whereas this is still not widely adopted in the US. When the two teams are separate, it often leads to: - Loss in operational efficiency and - Data and investigations being siloed between the two teams Why is this the case in the UK/EEA region? - Fundamentally fraud rates have been lower in the UK/EEA region due to 3DSecure being highly prevalent in card payments. Hence, bank scams (Authorized Push Payment scams) and financial crime (money laundering, terrorist financing) take much more of a front seat in their operations. - When it comes to AML, the UK/EEA area has had to be much ahead of other regions in deploying more innovative AML typologies esp. around cross border money movement, just given that there are dozens of EEA region currencies unlike the US. - In short, lower fraud but higher AML risk has forced fintechs/banks in Europe to more quickly adopt data science and thereby build a layered defense. You’ll very commonly hear terms like “First line of defense” and “Second line of defense”.  “First line of defense” is more data science heavy and is usually led by data science leaders (kind of like my previous role at Revolut). “Second line of defense” is then led by Heads of Regulatory compliance or MLROs who bring a regulator's lens of view and perform an audit of the procedures from the first line. However, we are increasingly seeing many fintechs and banks in the US also adopt a similar mindset into merging these teams. What are some other reasons that might explain this dichotomy? And most importantly, curious to hear about exceptions to the norm – UK/EEA fintechs/banks that kept these teams separate or US fintechs/banks that are merging them?

AI is breaking financial crime defenses faster than risk teams can fix them. We’re seeing these attacks daily: - AI agents spinning up hundreds of mule accounts - Deepfakes bypassing KYC & live biometric checks - Incorporation docs that are 100% AI-generated - Automated attacks that create endless alerts Legacy FRAML systems just weren’t built for this, and cannot keep up. We’re hosting a live session on Nov 18th with PwC, Nium, and ACAMS to dig into the latest AI-driven threats, and what risk teams can do to stop them. Speakers include: Michael D Jackson, Director of FinCrime Technology at PwC Francisco Mainez, Global Head of Financial Crime Strategy at Nium Kimberly Darpel, CAFS, Sr. Manager of Anti-Financial Crime at ACAMS Glenn Fratangelo, Head of Product Marketing at Sardine Register here: https://lnkd.in/eJecJE6C

How do you know for sure if that user during onboarding is risky? What about that payment that looks legit? What we’re seeing is that modern financial crime is happening across many different payment rails and platforms, much of which are outside the traditional banking system. If you don’t have visibility into what that user is doing at other fintechs, merchants, or crypto platforms, you can miss critical signs that the user may have: - History of fraud at multiple retailers - Tied to a fraud ring or mule network - High-risk activity on sports betting platforms - Buying large stock positions on margin But these are things you can identify with cross-industry consortium data. On Nov. 12th, we’re hosting a live webinar with Ravi Loganathan and Glenn Fratangelo to explore how consortiums such as Sonar help uncover hidden risks and detect earlier signs of financial crime. If you work in fraud, AML, or credit underwriting, this is a session you don’t want to miss. Register here: https://lnkd.in/eX7vqKCD

Excited to share some of the results from our work with bunq’s fraud team this year: 📉 82% reduction in fraud 🎯 4× fewer false positives 🙌 95% fewer fraud victims When we first connected, Bunq’s fraud prevention team was running a strong program, but updating their rules was a slow and manual process. Each new pattern required specs, engineering time, and prioritization across teams. All of which made it tough to move as fast as new fraud trends. With Sardine, that process now looks very different. When a new pattern shows up, Bunq can investigate and act in real-time. They use Sardine’s rules engine to create, test, and deploy rules in minutes (all without engineering resources). And our device and behavior signals have helped them uncover hidden relationships between accounts, which has been a gamechanger for stopping coordinated attacks before they spread. It’s a pleasure partnering with them to continue to raise the bar for fraud detection. Excited to see the results we achieve together next year 🙌 You can read more about our work with them here: https://lnkd.in/esB_BumD