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Virtual Event Fraud Detection Engine

Virtual Event Fraud Detection Engine

Overview

For 99 Virtual Race, keeping the competition fair and trustworthy is a top priority. With thousands of runners uploading their race results online, the platform needed a smart way to make sure every entry was honest. To help with this, Teman Data built an AI-powered system that checks for unusual activity during submissions—like results that don’t match normal running patterns. The system works fast and accurately, spotting anything suspicious before it affects the leaderboard. This not only helps the platform stay fair as it grows, but also builds confidence among runners, knowing that every result is verified and every race is played straight.
 

Challenge

The issue wasn’t just the number of entries — it was trust. With manual checks, the team could only review a small slice of submissions, and even then, suspicious results often slipped through. Some runners posted impossible finish times, others tampered with GPS data, and duplicate entries became harder to spot as the races grew. Each unchecked case quietly damaged the platform’s reputation. The team understood that if participants started questioning the fairness of the races, the entire business could be at risk.
 

Solution

Teman Data built a smart fraud detection system that watches race submissions in real time. It checks for warning signs like impossible finish times, odd GPS data, repeated uploads, and patterns that don’t match real runners. The system doesn’t just copy what people used to do manually — it learns from past cheating attempts to catch tricks that often go unnoticed.

The impact was instant. What used to take hours now happens in seconds. Suspicious entries are flagged or blocked before they reach the leaderboard. The operations team can spend less time chasing cheaters and more time improving the race experience. Most importantly, runners feel reassured — knowing every result is verified and every race is fair.

By replacing a slow, manual process with smart automation, 99 Virtual Race cut down on fraud, built trust in its brand, scaled up without extra staff, and delivered the fairness its community expects.
 

Output

  • Trained anomaly detection models based on participant behavior 
  • Applied personalized thresholds per user profile 
  • Scaled system to support different event types (e.g., rides, walks)
     

Impact

  • Increased fraud detection accuracy by 30% 
  • Scaled from 1,000 to 50,000 validated records/minute
  • Enabled rapid onboarding of new virtual events
     

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