How To Develop A Comprehensive Fraud Prevention Strategy

"We need more data to catch fraud" is usually wrong. You need better questions. I once inherited a fraud team drowning in data: • 100+ insights per transaction • 6 different risk tools • Terabytes of historical data Their chargeback rate was 1.5%+ Six months later, with the same data but different questions, we hit 0.6%. Instead of asking "Is this transaction fraudulent?" We asked "Why would a fraudster choose us?" That revealed a lot.... • We had instant payouts (fraudster candy) • Our refund process was automated (easy to exploit) • New account benefits were stackable (hello, farming) The framework that cut fraud 75%: 1. Map your honeypots    What makes your business attractive to fraud?    List your top 10 fraudster benefits.     2. Price the exploit    Calculate the ROI for each attack vector.    Fraudsters are ROI-driven. Make their math not work.     3. Break the economics    Don't block the fraud. Make it unprofitable.    Add delays. Require deposits. Limit stacking. Example: We had fraudsters creating 50+ accounts for new user promos. Instead of better detection, we made promo codes single-use per payment method. Simple. But effective. Fraud farms started to disappear. You already have the data. You're just asking it the wrong questions. BD²¹

🚨 ALERT: $1.6 Mn Stolen Through Payment Gateway Manipulation - Is Your Fintech Vulnerable? 🚨 A recent case involving Navi Technologies highlights the critical need for robust fraud prevention measures. The company was defrauded of ₹14.26 crore due to a loophole in a third-party payment gateway, which allowed users to edit transaction amounts post-payment. This incident underscores the importance of both technical and operational safeguards. How can such frauds be prevented? 🔍 Technical Measures: 👉 Implement anomaly detection systems to flag unusual transaction patterns in real-time. 👉 Enforce immutable transaction records to prevent unauthorized edits. 👉 Regularly audit and test payment gateways for vulnerabilities. 🛡️ Operational Measures: 👉 Establish multi-layered approval processes for high-risk transactions. 👉 Conduct employee and customer awareness programs to identify and report suspicious activities. 👉 Collaborate with law enforcement and cybersecurity experts to stay ahead of emerging threats. Fraud prevention is not just a technical challenge but also an operational one. By combining advanced technology with the right processes, businesses can safeguard themselves against such incidents. Let's learn from this and build a more secure digital ecosystem! 💡 #FraudPrevention #CyberSecurity #AnomalyDetection #BusinessResilience https://lnkd.in/dW96ejyR

🚨 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐢𝐧 𝐌𝐨𝐭𝐢𝐨𝐧 — 𝐅𝐫𝐚𝐮𝐝 𝐏𝐫𝐞𝐯𝐞𝐧𝐭𝐢𝐨𝐧 by DEUNA Traditional, static fraud rules often fall short — tightening controls so much that they block good customers, or leaving gaps that allow fraud to slip through. Agentic intelligence changes this paradigm. By leveraging historic transaction data and strategic signals (PSPs, payment methods, geographies, behavioral trends), it dynamically recommends risk controls tailored to each scenario. — 𝐃𝐞𝐞𝐩 𝐃𝐚𝐭𝐚 𝐂𝐨𝐧𝐭𝐞𝐱𝐭 Historic transaction patterns and behavioral signals are integrated with granular specifics like BIN, card franchise, and geography. This allows the system to distinguish between legitimate customers and potential fraud with precision. → The Walt Disney Company leverages historical subscription behavior data to differentiate genuine recurring payments from suspicious account takeovers, reducing false declines. — 𝐋𝐨𝐰 𝐑𝐢𝐬𝐤 𝐯𝐬 𝐇𝐢𝐠𝐡 𝐑𝐢𝐬𝐤 𝐓𝐫𝐚𝐧𝐬𝐚𝐜𝐭𝐢𝐨𝐧𝐬 Low-risk transactions flow seamlessly with minimal friction, boosting conversion and improving customer satisfaction. High-risk transactions are dynamically routed through targeted fraud prevention layers — activating the most relevant PSPs and antifraud providers at the right moment. → Uber adapts fraud checks by geography, applying stronger measures in regions with high fraud incidence while keeping repeat riders’ payments frictionless. — 𝐏𝐫𝐨𝐯𝐢𝐝𝐞𝐫 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐅𝐫𝐚𝐮𝐝 𝐂𝐨𝐧𝐭𝐞𝐱𝐭 Risk scoring is factored into provider and PSP selection to balance approval rates, cost efficiency, and security. → Airbnb leverages intelligence to dynamically adjust fraud controls by market and traveler profile — applying stronger authentication in high-risk regions or for first-time guests, while allowing frictionless payments for trusted, repeat customers. — 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞𝐝 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐚𝐭 𝐒𝐜𝐚𝐥𝐞 Fraud tools are embedded directly into the orchestration layer, enabling smarter allocation: fraud detection where it is most impactful, and seamless flows where customers have already proven trustworthy. → Worldline merchants leverage adaptive authentication, activating 3DS selectively when intelligence identifies elevated risk — enabling smoother experiences for low-risk customers. — The Result → Intelligent Growth with Protection ✅ Higher approval rates without compromising safety ✅ Smarter allocation of fraud tools where they matter most ✅ Frictionless checkout experiences for trusted customers — This is proactive fraud prevention in motion — moving beyond rigid rules into an era of intelligent orchestration, where every payment decision optimizes both security and customer satisfaction at scale. — Source: DEUNA ► Subscribe to The Payments Brews: https://lnkd.in/g5cDhnjC ► Connecting the dots in payments... | Marcel van Oost