How To Create A Secure Ecommerce Environment

If my boss asked me to "assess our risk surface area and fraud priorities", this is how I would get it done by 5PM tomorrow. Step by step process. 1 - Pull our last 90 days of fraud data. Not just the obvious stuff like chargeback rates, but the full spread: login attempts, account creation patterns, payment declines... everything. Why 90 days? Because fraudsters love to exploit seasonal patterns, and we need that context. 2 - Map out every single entry point where money moves. I'm talking checkout flows, refund processes, loyalty point redemptions... even those "small" marketing promotion codes everyone forgets about. (Fun fact: I once found a six-figure exposure in a forgotten legacy gift card system) 3 - Time for some real talk with our front-line teams. Customer service reps, payment ops folks, even the engineering team that handles our API integrations. These people see the weird edge cases before they show up in our dashboards. 4 - Create a heat map scoring each entry point on three factors: → Financial exposure (how much could we lose?) → Attack complexity (how hard is it to exploit?) → Detection capability (can we even see it happening?) 5 - Cross-reference our current fraud rules and models against this heat map. Brutal honesty required here – where are our blind spots? Which high-risk areas are we treating like low-risk ones? 6 - Pull transaction data for our top 10 riskiest areas and run scenario analysis. If fraud rates doubled tomorrow, what would break first? (It's usually not what leadership thinks) 7 - Document our current resource allocation vs. risk levels. Are we spending 80% of our time on 20% of our risk? Been there, fixed that. 8 - Draft a prioritized roadmap based on: → Quick wins (high impact, low effort) → Critical gaps (high risk, low coverage) → Strategic investments (future-proofing our defenses) 9 - Prepare three scenarios for leadership: → Minimum viable protection → Balanced approach → Fort Knox mode Because let's be real, budget conversations need options. 10 - Package it all up with clear metrics and KPIs for each priority area. Nothing gets funded without numbers to back it up. ps... Make it visual. Leadership loves a good heat map, and it makes complex risk assessments digestible. Trust me on this one

Many people think being overly stringent with upfront identity checks will reduce fraud. After a decade of building advanced fraud prevention strategies, I'm here to tell you that many people are wrong. I know it's counterintuitive, but let me explain: When institutions make their onboarding processes overly strict (i.e. requiring extensive documentation and multiple verifications), they gain a false sense of security. They assume these rigorous checks eliminate fraud risks and often let their guard down once users are onboarded. Fraudsters exploit this confidence by learning and bypassing the rules upfront, gaining access, and wreaking havoc from the inside. The better approach? ▪️ Don’t front-load all your checks. ▪️ Create the least amount of friction for each stage of risk. ▪️ Continuously monitor user behavior throughout their lifecycle. ▪️ Add step-ups as risk scores dictate. It forces you to stay vigilant, and it produces better outcomes.

Too many fraud solutions focus just on account opening. But risk evolves across the full user journey. Here's how we build the full picture at Sardine for dynamic scoring 👇 👉 When a user signs up, we create a baseline score based on identity, device, email, behavior signals 👉 As they transact, we update the score dynamically based on activity like login patterns, transaction details, behavior changes 👉 We build a holistic profile combining telco, email, device, merchant and more data into their risk score 👉 Machine learning models continuously monitor and flag anomalies to the baseline 👉 Granular data + models train on user's unique activity = precise risk scoring as they grow with your product Unlike legacy fraud tools, we don't just screen applicants. We provide ongoing monitoring across onboarding, transactions, account changes and more. This full picture reduces false positives and keeps fraud low across the user lifecycle.