AI fraud detection & profitability prediction
An AI engine that catches fraudulent traffic in real time and forecasts campaign profitability — so every marketing decision is backed by data, not guesswork.
What AuditIQ does
AuditIQ is built for marketing operations that move fast and can't afford blind spots. It watches traffic and transactions in real time, learns what fraud looks like, and turns clean data into profitability forecasts.
Three hard problems — fraudulent traffic, unpredictable profitability and scattered data — handled by one system instead of three.
AI-based fraud detection
Three layers work together — watching in real time, learning from data, and adapting as fraud tactics evolve.
Analyzes user behavior, transactions and patterns to flag suspicious activity as it happens.
Trained on massive datasets to detect anomalies and fraudulent patterns humans would miss.
Continuously learns from new data, adapting to evolving fraud tactics without manual retraining.
Fraud signals we watch
Beyond simple rules, AuditIQ scores each signal with AI so genuine users pass and fraud gets stopped.
Identifies proxies and VPNs used to disguise fraudulent activity.
Watches transaction frequency, amounts and account activity for anomalies.
Flags suspicious transactions with predefined rules and AI models combined.
ETL for data integration
Every source is extracted, transformed, enriched and loaded into one warehouse — so the models always run on complete, consistent data.
Customer databases, transaction logs and external market data.
Standardizes and cleans data from every incoming source.
Adds external market insights and demographic signals.
One enriched warehouse feeding fraud and profitability models.
Profitability prediction
Operational benefits
Significantly fewer fraudulent transactions, minimizing financial losses.
Better resource allocation through real-time, actionable insights.
A secure, trusted environment that protects the customer experience.
From pilot to production
The solution goes live with full monitoring systems in place from day one.
Key metrics are tracked and system effectiveness is measured against targets.
AI models are updated as new data and emerging fraud trends appear.