Global Payment Company Rings Up Major Savings on SMS Fraud Costs With Arkose Labs Collaboration

See how a global payments leader saves $3.7M annually while blocking 99.9% of SMS toll fraud attacks. Download the case study to learn its strategy!

What You’ll Learn

• How a global payments leader uncovered hidden SMS toll fraud draining operational budgets
  

  How attackers exploited OTP flows through colluding carriers and premium-rate numbers, resulting in illegitimate SMS charges that blended in with normal traffic.

  
  
• Why basic bot mitigation and downstream controls failed to stop the problem
  

  How traditional tools either blocked legitimate sign-ups or allowed fraudulent ones through due to limited visibility into device, behavior, and telecom-level manipulation.

  
  
• How Arkose Bot Manager provided real-time intelligence to distinguish legitimate users from SMS fraud operations
  

  How deep device fingerprinting, behavioral anomaly detection, and adaptive challenge-response workflows helped surface attackers hiding within OTP verification flows.

  
  
• How Arkose Labs dynamically escalated defenses as attackers changed tactics
  

  How the platform neutralized automated bots, then machine-learning-based solvers, then human fraud farms—adapting challenge complexity to outpace each new wave.

  
  
• How holistic, early-stage mitigation restored trust and stabilized registration systems
  

  How cutting fraudulent OTP activity at the source improved onboarding integrity and protected operational budgets across multiple countries.

  
  

FAQ

Why was SMS toll fraud so difficult for the payments company to detect?

The fraud was hidden inside legitimate-looking OTP requests. Attackers used premium-rate numbers and colluding carriers to trigger expensive SMS charges. Because the activity resembled normal customer behavior, it went unnoticed until registration abandonment and operational costs began to rise sharply.

How did Arkose Labs expose and stop the fraud?

Arkose Bot Manager monitored more than 225 behavioral and device signals, identifying anomalies consistent with automated bots, ML-driven solvers, and human fraud farms. As shown in the attack-profile graph on page 2, attacks dropped immediately after Arkose activation and remained suppressed through adaptive challenge escalation.

How did the attackers try to adapt—and how did Arkose respond?

Attackers first used basic automation, then shifted to machine-learning-enhanced solving, and finally relied on human fraud farms. Arkose escalated challenge complexity at each stage. According to the timeline on page 3, every pivot by the attackers was quickly neutralized, ultimately leaving both automation and human solving ineffective.

What business value did the company gain by deploying Arkose Labs?

The platform quickly reduced fraudulent SMS volume, protected OTP-related operational costs, improved onboarding integrity, and delivered a positive ROI. By eliminating hidden fraud pressure and improving visibility, Arkose Labs helped the company stabilize global registration flows and strengthen customer trust.