How to Create a Safe Shopping Experience for Customers

I never thought it would happen to me. One day, I noticed a spike in chargebacks. I knew something was wrong, but I didn’t know what. I started by investigating the types of fraud we were experiencing. From fake accounts to transaction fraud, it was overwhelming. Here’s how to detect and prevent fraud at every stage of the customer journey: Stage 1: Data Collection Data is your first line of defense. • Gather as much user data as possible. • Track device information, IP addresses, and user behavior. • Monitor changes in user activity. Understanding user patterns helps in identifying anomalies early. Stage 2: Basic Risk Scoring Identify low-hanging fruit. • Use simple rules to score transactions. • Look for mismatched billing and shipping addresses. • Flag unusual purchasing behaviors. This stage catches the most obvious fraud attempts. Stage 3: Dynamic Friction Balance security and user experience. • Implement step-up authentication for suspicious activities. • Use dynamic risk based routing • Introduce verification processes at critical points. Dynamic friction helps reduce fraud without hurting conversion rates. Stage 4: Advanced Analytics Deep dive into data for insights. • Use machine learning to detect patterns. • Analyze transaction histories and behaviors. • Integrate third-party data sources for enhanced detection. Advanced analytics provide a comprehensive view of potential threats. Stage 5: Continuous Optimization Stay ahead of evolving threats. • Regularly update your fraud detection rules. • A/B Test and refine your strategies. • Stay informed about new fraud techniques and trends. Continuous testing ensures your not two steps behind fraudsters. A comprehensive fraud strategy requires a layered approach.

How the fraud team maximises revenue (...by turning risk data into revenue opportunities): Most people think fraud teams just block bad guys. But smart fraud teams are actually revenue drivers. Here's how to use real-time risk signals to maximize sales while stopping fraud: 🔷 Dynamic journey mapping — Analyze user behavior from first click to checkout. Build trust scores that evolve throughout the session. Low-risk users get express lanes, suspicious ones get guardrails. 🔷 Intelligent friction layering — Add or remove security steps based on real-time risk levels. Known customers on trusted devices? One-click checkout. New user with suspicious patterns? Extra verification. 🔷 Smart payment routing — Match payment methods to risk profiles. Premium customers get instant access to high-value features. New accounts start with lower limits that grow with trust. 🔷 Continuous session monitoring — Track subtle risk changes during user sessions. Automatically adjust security measures up or down as behavior patterns shift. If you Implement this approach.... The results: - Reduction in customer churn - Faster checkout times = more revenue, quicker - Increase high-value transactions and customer LTV All while maintaining genuine user rates over 98% and keeping fraud rates under 1%. Want to see how to use real time device intelligence as part of a risk-based UX framework? Drop "+" below and I'll share how you can turn the fraud team into a revenue driver.

Here’s something that breaks every “UX rule.” The more secure customers FEEL, the more they spend at checkout. Even if it means extra steps. Our very own Matt Vega outlined why in a recent podcast interview with Fraudology. After studying checkout flows at 6 separate companies, he found the same mindsets. - Marketing: "Friction kills conversions" - Fraud: "Verification prevents losses" - Leadership: "Just make it work" We've been asking the wrong question entirely Matt added 'tactical friction' across multiple companies - smart verification triggers on high-value transactions ($1,000+). The results broke every assumption: ↗️ 23% increase in transaction value ↗️ 15% improvement in customer lifetime value ↗️ DECREASED churn rates That’s ROI When customers hit verification steps for big purchases, they didn't get annoyed. They got confident. Customer research revealed: 'If they're protecting my $1,000 purchase this carefully, I trust them with more.’ Checkout the Fraudology podcast to hear the whole thing!

𝗪𝗵𝗮𝘁 𝗜𝘀 𝗖𝗹𝗼𝘂𝗱 𝗧𝗼𝗸𝗲𝗻 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 (𝗖𝗧𝗙)? As payments expand, securing card-not-present (CNP) transactions across multiple devices is paramount. Visa's Cloud Token Framework (CTF) addresses this need by enhancing payment security and user experience. 𝗕𝘂𝗶𝗹𝘁 𝗼𝗻 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗧𝗼𝗸𝗲𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻 CTF builds upon Visa's existing network tokenization infrastructure. Network tokens replace PANs with tokens, reducing the risk of data breaches. CTF extends this by introducing: ▪️Device Binding → Associates a token with a specific device, ensuring that the token is only usable from that device. ▪️Cardholder Verification → Incorporates biometric or other verification methods to confirm the user's identity. This layered approach enhances security by ensuring that both the device and the user are authenticated. 𝗠𝗲𝗿𝗰𝗵𝗮𝗻𝘁 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀 🔹Reduced Fraud → Device binding and Strong Customer Authentication (SCA) significantly lower the risk of unauthorized transactions. 🔹Improved Customer Experience → Streamlines the checkout process by reducing the need for repeated authentication, leading to higher conversion rates. 🔹Enhanced Data Security → Minimizes the storage and transmission of sensitive card data, aligning with PCI DSS compliance requirements. 𝗔𝗰𝗵𝗶𝗲𝘃𝗶𝗻𝗴 𝗟𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗦𝗵𝗶𝗳𝘁 ▪️CTF enables merchants to achieve liability shift by incorporating SCA directly into the transaction process. ▪️By combining device binding with cardholder verification such as biometrics, CTF satisfies SCA requirements, resulting in liability shift from the merchant to the issuer. 𝗔𝗱𝘃𝗮𝗻𝗰𝗶𝗻𝗴 𝗣𝗮𝘆𝗺𝗲𝗻𝘁 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 🔹Multi-Device Security → Ensures consistent security across various devices, accommodating the modern consumer's shopping habits. 🔹Future-Proofing → Positions merchants to adapt to evolving security standards and consumer expectations. 🔹Trust Building → Enhances consumer confidence by providing a secure and seamless payment experience. 𝗨𝘀𝗲 𝗖𝗮𝘀𝗲: 𝗦𝗲𝗰𝘂𝗿𝗶𝗻𝗴 𝗛𝗶𝗴𝗵-𝗩𝗮𝗹𝘂𝗲 𝗧𝗿𝗮𝘃𝗲𝗹 𝗕𝗼𝗼𝗸𝗶𝗻𝗴𝘀 📌 A travel booking platform integrates CTF to safeguard large, CNP transactions: ▪️Device Binding → When a customer first books a trip using the app, a network token is provisioned and bound to the user’s device ▪️Cardholder Verification → For every booking above a certain value threshold, biometric auth is triggered, verifying the identity of the user. ▪️SCA Compliance → By combining these elements, the transaction satisfies SCA, enabling liability shift to the issuer ▪️Friction When It Matters → Users expect and accept a bit more friction for high value purchases, especially if it improves security and trust. Sources: Visa, Thales, Howard Xiao 🚨Follow Jason Heister for daily #Fintech and #Payments guides, technical breakdowns, and industry insights.