Core Capabilities
  • Real-time anomaly detection for payments, logins, and account activities
  • User behavioral analytics to spot insider fraud
  • Risk scoring with AI-powered predictive models
  • Integration with AML (Anti-Money Laundering) systems
  • Fraud case management dashboards and reporting
Tech Foundation
  • Machine learning frameworks: TensorFlow, XGBoost, Scikit-learn
  • Fraud detection platforms: SAS Fraud Management, Feedzai
  • Data lakes and analytics: Hadoop, Spark, Snowflake
  • Visualization and reporting with Tableau, Power BI
Deployment
  • Data ingestion and cleansing across banking, retail, or insurance sources
  • Training of fraud detection models on historical transaction data
  • Integration with core banking, e-commerce, or ERP systems
  • Real-time monitoring with AI-assisted SOC analysts
Value
  • Reduced financial loss due to fraud and scams
  • Improved customer trust and brand reputation
  • Regulatory compliance with AML and fraud detection guidelines
  • Cost savings by reducing manual fraud investigations
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