Real-Time Risk Assessment Strategies for 3DS2 Payments

3‑D Secure Can Save Merchants Millions…If They Use It Correctly Card‑not‑present fraud will steal $28.8 billion from merchants this year alone. Yet many payment leaders still call 3‑D Secure (3DS) a “conversion killer.” However, the data tells a different story: - 93% of UK merchants and 76% of US merchants report cart abandonment rates below 15% when 3DS is triggered. - 64% of transactions are authenticated frictionlessly, never requiring the shopper to lift a finger. - Liability‑shift moves fraud chargebacks from the merchant to the issuer, saving roughly 0.4 – 1 % of GMV for high‑risk verticals (IXOPAY benchmark). So why do some merchants still bleed revenue after turning on 3DS? Because HOW you deploy it matters more than IF you deploy it. Let me explain... Having been on both sides of the implementation debate when working on acquiring and issuing projects with Visa and Mastercard for over a decade, I have developed a unique understanding of what motivates Merchants/Acquirers and Issuers regarding how and when to apply 3DS. Because of that, my advice to merchants is primarily practical and very data-driven. Here is my playbook for properly leveraging 3DS. 1. Use Risk‑based routing, not blanket challenges By sending only high‑risk or mandated transactions via 3DS. Wherever the rules allow, apply SCA exemptions (TRA, low‑value, whitelisting, etc.). 2. Feed the issuer better data Pass >100 data points, including device information, account tenure, prior‑auth history, etc., to maximize frictionless approvals. 3DS2 rewards rich context. 3. A/B‑test challenge flows Track abandonment and approval deltas by BIN, issuer, and market. Kill any flow that underperforms the control. 4. Build smart fail‑over If a transaction soft‑declines after a 3DS attempt, automatically retry through another acquirer, payment method, or token format. Don’t leave good orders stranded. 5. Let your orchestrator do the heavy lifting Platforms like IXOPAY let you codify these rules per country, payment method, and even hour of the day, without fresh code deployments. Result? Sub‑1% fraud loss AND higher net conversion. That’s money back to the P&L instead of to fraudsters or lost shoppers. How are you ensuring that your merchants are properly balancing fraud protection and conversion today? Drop your tactics (or horror stories) in the comments. P.S. If you want a more in-depth guide on how to utilize 3-DS, Orchestration, and other tactics, subscribe to my newsletter, the Payments Strategy Breakdown, as I will be sharing them soon https://buff.ly/s32OfBn

🚨 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

🔒 𝗧𝗼𝗱𝗮𝘆'𝘀 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗗𝗲𝗲𝗽-𝗗𝗶𝘃𝗲: 𝗧𝗵𝗲 𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗼𝗳 𝟯𝗗 𝗦𝗲𝗰𝘂𝗿𝗲 𝗔𝘂𝘁𝗵𝗲𝗻𝘁𝗶𝗰𝗮𝘁𝗶𝗼𝗻 Let's look at how 3D Secure 2.0 (3DS 2.0) is revolutionizing payment authentication, with a focus on the technical implementation. 𝗧𝗵𝗲 𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 -- Originally developed in 1999, 3DS was built on a three-domain model: • Acquirer Domain (merchant/bank receiving payment) • Issuer Domain (cardholder's bank) • Interoperability Domain (supporting infrastructure) 🔧 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 - 𝟯𝗗𝗦 𝟮.𝟬 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗙𝗹𝗼𝘄 1. Customer initiates checkout 2. Merchant sends transaction to fraud vendor including data like:   • Device fingerprinting   • Geolocation data   • Transaction history   • Behavioral biometrics 3. Real-time risk assessment from fraud vendor -- Is the transaction risky? 4.From here, the transaction takes one of two possible paths:   a) Frictionless: Background authentication for low-risk transactions   b) Challenge: Biometric or one-time code for high-risk cases 🛠️ 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁𝘀 𝗼𝘃𝗲𝗿 𝟯𝗗𝗦 𝟭.𝟬 1. Authentication Methods: • SDK integration for native mobile apps • Browser fingerprinting • Device binding • Biometric authentication • One-time passcodes 2. Data Exchange: • Minimum 20 data points required • Up to 100 data points supported • Real-time risk scoring • Device-specific information • Transaction history analysis 3. Protocol Enhancements: • Native app support • Out-of-band authentication • Decoupled authentication flows • Exemption handling • Delegated authentication support 💡 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀: 1. Superior Risk Assessment • 10x more data compared to 3DS 1.0 • Real-time device data collection • Enhanced fraud prevention capabilities • Intelligent risk-based authentication 2. Modern Authentication Methods • Biometric integration • Auto-filling OTP capabilities • Mobile banking app authentication • Device-optimized challenges 3. Enhanced Liability Protection • Fraud chargeback liability shift to issuers • Protection even when issuers don't participate • Reduced merchant risk exposure 4. Seamless Integration • Native SDK support for iOS/Android • Optimized iFrame for browsers • Embedded checkout experience • Device-responsive design 5. Improved Acceptance Rates • Reduced acceptance gap between POS and CNP • Enhanced issuer confidence • Better transaction success rates What are your thoughts on 3DS? 💬 Sources: ACI Worldwide, inai (YC S21), Worldpay #Payments #FinTech #3DS2 #FraudPrevention #Authentication