About the course

This course introduces participants to the inner workings of in-session and transactional anti-fraud systems, fraud detection technologies, and the evolving tactics of cybercriminals. Through real-world examples and practical exercises, participants will gain a foundational understanding of modern fraud prevention techniques, user/device profiling, and fraud scheme investigation.

Key topics covered:

  • Fraud types, trends, and prevention strategies
  • Session-based and transactional anti-fraud system architectures
  • Device fingerprinting, global profiling, behavioral biometrics
  • GEO profiling and contextual risk scoring
  • Detection and analysis of ATO, APP fraud, malware, phishing, laundering
  • Basic fraud analytics using graphs and investigation tools
  • Rule-based detection systems: rule creation, management, and feedback
  • API integration, adaptive authentication, and call center collaboration

Skills acquired:

  • Understand and categorize key fraud types and emerging techniques
  • Use advanced user and device identification technologies
  • Detect and investigate suspicious activity using rule-based platforms
  • Build and manage detection rules and fraud prevention lists
  • Integrate fraud systems with business infrastructure using API and feedback loops
  • Support fraud response coordination with digital channels and call centers
  • Apply knowledge to support the implementation of enterprise-wide anti-fraud ecosystems

Target participants:

  • Cyberthreat monitoring specialists
  • IT and InfoSec department heads
  • Technical specialists with basic InfoSec knowledge
  • Managers of client-facing digital service channels

Requirements:

  • A basic understanding of information security concepts
  • Familiarity with cybersecurity terminology and business workflows
  • (Recommended) Prior exposure to fraud detection platforms or banking/financial security environments

Day 1

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Theory of Fraud and Systematic Prevention

  • Types and trends in fraud
  • Evolution of anti-fraud platforms
  • Overview of session- and transaction-based systems

End-User Identification Technologies

  • Device ID and fingerprinting
  • Global and cloud profiling (Global ID, Cloud ID)
  • Behavioral analysis (ML-based user profiles)
  • GEO profiling techniques

Basic Fraud Analytics

  • Fraud categorization
  • Investigation flow and graph-based analysis
  • Use of analytic tools in real-world scenarios

Day 2

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TTPs of Fraudulent Activity

  • Account Takeover (ATO)
  • Authorized Push Payment (APP) fraud
  • Malware and trojans
  • Phishing and anonymization
  • Drops, mules, laundering tactics

Fraud Protection Toolset

  • Using widgets, dashboards, and rule feedback
  • Working with detection rules and list management
  • Real-time decisioning based on user behavior

Fraud System Integration and Implementation

  • Push and Pull APIs for system integration
  • Adaptive authentication strategies
  • Fraud system coordination with call centers
  • Designing your fraud prevention ecosystem