IFDS
AI-Powered Fraud Detection Platform
A financial services organization handling large-scale digital transactions faced increasing fraud risks due to evolving attack patterns and limitations in rule-based detection systems.
To address this, they partnered with Cylix Solutions to implement an AI-powered fraud detection platform that leverages machine learning for real-time anomaly detection, adaptive risk scoring, and continuous model improvement. The goal was to move from static, rule-based systems → intelligent, adaptive fraud prevention.
Solution Implemented
Problem Statement
Rule-based fraud detection systems are generating high false positives while failing to identify new and evolving fraud patterns. Fraud detection is further hindered by delays caused by batch processing, preventing timely intervention. This leads to a poor customer experience, with legitimate transactions often being declined. Additionally, there is no real-time risk scoring capability to assess transactions dynamically, and data remains fragmented across multiple systems, limiting visibility and actionable insights.
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