Stopping Synthetic Identity Fraud with Digital History
Synthetic identity fraud costs you twice: once when a fabricated customer maxes out a credit line and disappears, and again when tighter onboarding ...
Manual fraud review: How Trust Insights shows the whole identity at a glance
Every minute an analyst spends on a flagged case is a minute of labor you pay for. At an...
Why Device Fingerprinting Alone Can't Stop Fraud (& How You Can)
Fraud teams at e-commerce merchants face an expensive contradiction. Device fingerprinting is one of the most valuable signals in the risk stack, but ...
The Dark Web and the Rise of Fraud-as-a-Service
A stolen email address sells for just $10.
Pipl Recognized for Transaction Fraud Monitoring Innovation in the 2026 Datos Insights Impact Awards
Datos Insights, one of the financial services industry's most respected research and advisory firms, has named Pipl a Silver Medalist in its 2026 ...
Why Your Fraud Model Keeps Getting Overridden & What the Trust Gap Is Costing You
You've already built what most would call a successful fraud model. It performs under pressure, adapts across regions, and holds its ground against ...
Pipl Announces Partnership with FICO to Offer Elephant Trust Products
Post Falls, Idaho – 7 April 2026 – Pipl announced today that its Elephant Trust solutions are now offered viaFICO® Marketplace, reflecting its ...
False Declines, Stale Signals, & the Hidden Cost of a Fraud System that Can't Learn
You know that digital wallets, VPNs, freight forwarding, and alternate payment methods aren't red flags anymore; they're just how legitimate users ...
Fraud Alert Fatigue: When Observability Isn't Enough
The system didn't fail, it just wasn't believed. It fired again. The same alert. The anomaly. The metric that moved outside its historical band. It ...
Fraud Model Accuracy Isn't the Problem. Model Use Is.
You've built the model. You've hardened it, validated it, and watched it outperform baseline systems across every standard metric. Fraud model ...