OVERVIEW OF FRAUD DETECTION SYSTEMS AND PERFORMANCE KPI DEVELOPMENT

In this article overview was provided on several fraud detection systems, analysis result of common scheme and development of KPIs to detect performance degradation or improvement from business logic point of view. Four different systems were reviewed. Following FMS were developed by Gigamon and Argyle Data cooperation, AWS, Subex, Cvidya Amdocs. Solution developed by Gigamon and Argyle Data consists of Gigamon fabric for information collection/filtering/enrichment and Argyle Data Fraud detection system, which is based on Hadoop technology to store collected data and analysis results by application. AWS Fraud Detection collects NRTRDE flow and process it by using ML technics provided by AWS. Subex fraud management system provides flexible ETL for data collection from different sources with adjustable detection rules and ML for suspicious behavior learning. FraudView by Cvidya Amdocs collects information from varying points like OSS/BSS, CRM customer details, Prepaid platforms, HLR, Switch CDRs, Probe (SS7, VoIP, IP) and process it by different detection engines. Simplified processing FMS processing scheme and KPIs based on different timestamps were made. Following conclusions were