AI-powered SMS fraud detection
Context-aware NLP fraud detection on a high-volume messaging platform—replacing brittle keyword rules with embeddings, closed-loop review, and stack integration.
In production
Embedded in trust & ops workflows
Challenge
A messaging platform handling billions of monthly texts faced evolving SMS fraud and abuse—creating regulatory risk, eroding user trust, and raising carrier-level exposure. Rule-based systems needed constant tuning, adapted slowly to new patterns, and produced too many false positives to operate sustainably.
What we did
FocusKPI built an ML-native, context-aware text classification system using embeddings to catch semantic patterns beyond keywords or static rules, with a closed-loop feedback process as new fraud patterns emerged. The system integrated into the existing analytics and trust stack with product, engineering, and operations partners.
Results
Precision, recall, and F1 exceeded internal expectations, letting the team focus on ambiguous cases. The work established a foundation for real-time detection and expansion into broader abuse signals.
“FocusKPI delivered an exceptional solution that improved our intelligence and fully integrated into our process so that we can tackle abuse efficiently and effectively on behalf of our customers. We couldn’t be more pleased with the partnership.”
Why it worked
NLP specialization was delivered inside the platform’s existing tooling and workflows—operational from day one, not a research prototype needing a second build.
Discuss a similar engagement
We typically start with a scoped proof of concept before production deployment.