Global Identity Coverage
Global expansion takes massive investment in time, money, and resources. So why let it break at the last step when it’s time to approve new customers? Legacy systems rely on localized and surface-level signals to assess trust, and often misread real users as risk. Elephant helps you immediately recognize good customers in unfamiliar markets before false declines rob your growth.
When identity signals are missing or misunderstood, your systems start making the wrong calls. Real customers get flagged. Legitimate purchases don’t go through. And what looked like fraud prevention becomes false declines, broken trust, and blocked growth.
Most decision engines rely on isolated signals like basic device data, unverified emails, or weak phone metadata. Without deeper context or signal correlation, real customers look risky and get declined.
VPNs, shared devices, and geo mismatches are common in many regions. But when those signals are misinterpreted as risk, customers you could be trusting get blocked for something they consider normal.
Fraud rules built for one region rarely work in another. When your logic can’t flex to accommodate new buying patterns, good customers get caught in filters that were designed for someone else.
Juggling multiple identity vendors mean inconsistent signals, uneven coverage, and endless exceptions. Teams get stuck in edge cases and manual reviews instead of enabling frictionless transactions.
Most identity solutions are designed to block fraud, not recognize trust. They rely on static rules, shallow signals, or domestic benchmarks that don’t translate when behavior shifts. But good customers don’t always match familiar patterns, and that’s where rigid rules fall apart. A trust-first approach rethinks how identity is evaluated, connecting signals in context to reveal what others miss.
When your signals work everywhere, your decisions do, too. No more market-by-market logic or policy drift. You get consistent, high-confidence outcomes, without sacrificing speed or approval rates.
Customers who once looked suspicious are now confidently approved. You approve more of the right people, decline fewer real ones, and unlock growth in markets that used to feel untouchable.
Fewer vendors, fewer custom rules, and reduced exceptions. Your team stops firefighting edge cases and starts optimizing for expansion. What used to be a tradeoff between risk and revenue is now just progress.
Noisy signals, brittle integrations, and privacy pressure have made identity decisions harder than they should be. We’ve created two flexible solutions that are fast to integrate, privacy-native by design, and built to fit your workflow, not force a new one.
Plug real-time trust scores and signal intelligence directly into your decision logic, so you can automate approvals, reduce fraud, and skip the rework.
A visual tool for fraud analysts to spot risk fast. Surface identity signals and connections at a glance, ideal for confident manual reviews and edge-case decisions.