Arva AI

“score doesn’t always tell the full story. It’s the contextual signals — the media mentions, the website intelligence, the documentation gaps — that often reveal the truth.And that’s where Arva shines.Stay Ahead of RiskArva helps compliance teams surface hidden risks faster — before they become liabilitiesBook a DemoStay Ahead of RiskArva helps compliance teams surface hidden risks faster — before they become liabilitiesBook a DemoRead our Case StudiesLarge US Bank Cuts Screening False Positives by 90% and Increases Compliance Capacity 5×How a Unicorn Fintech 5x’d Team Capacity and Cut False Positives by 84%How a Top-Tier US Bank Automated 78% of Transaction Monitoring AlertsHow Tola Stopped a Fraudulent Medical Supplier with Help from Arva AIOakNorth Bank Reduces Screening Alerts by 84% With Arva AIConstruction Firm with Fabricated Location Unravelled by TolaHow Keep Cut 60+ Hours of Manual Work with Arva AIWhen”

“Isn’t Low Risk at AllEarlier this summer, a U.S.-based fintech began onboarding what appeared to be a straightforward new customer — a design services business incorporated in Florida. On paper, everything looked legitimate. The business had an active LLC registration, a matching legal name and address, and no flags from standard incorporation, sanctions, or ownership checks. Initial risk ratings came back as low across the board.But something didn’t sit right.A member of the compliance team, using Arva during routine onboarding review, decided to dig deeper. Within moments, Arva’s platform uncovered multiple red flags that would have been easy to miss in a traditional manual review.First, Arva’s web presence analysis flagged the company’s website as suspicious. Although a landing page existed, it showed no real traffic or activity. There were no indicators of a functioning business—no team bios, no client logos, no service details beyond boilerplate buzzwords.Next came a more serious issue. Arva’s adverse media engine identified that multiple individuals listed as officers of the company had been linked to prior scam-related activity. The platform didn’t just surface generic mentions—it accurately classified the results and surfaced the”