Enterprise Fraud Management System (EFMS)

Course schedule

Classroom Training:
DateVenueDurationPrice
15 - 19 Jul 2024London5 days£4,250
9 - 13 Sep 2024London5 days£4,250
16 - 20 Dec 2024London5 days£4,250

Please note: prices shown above are exclusive of VAT (20%).

Course Overview

Discover how to implement and manage an EFMS. This course covers the technology, processes, and strategies required to detect and prevent fraud across an enterprise.

Who Should Attend

This course is designed for professionals involved in fraud prevention and detection, risk management specialists, IT and security professionals, and business executives and managers responsible for implementing EFMS in organizations. It also caters to individuals interested in gaining expertise in fraud management and understanding how EFMS can be leveraged to protect organizations from various fraud risks.

  • Fraud prevention and detection professionals
  • Risk management specialists
  • IT and security professionals
  • Business executives and managers responsible for fraud prevention
  • Individuals interested in implementing EFMS in organizations

Course Outcomes

By the end of this course, participants will be able to:

  • Understand the concepts and importance of Enterprise Fraud Management Systems (EFMS)
  • Identify common fraud risks and vulnerabilities across various industries
  • Implement an EFMS framework tailored to their organization’s needs
  • Utilize data analytics and machine learning in fraud detection and prevention
  • Comprehend the legal and ethical considerations in fraud management

Course Topics

Introduction to Enterprise Fraud Management

  • The role of EFMS in fraud prevention
  • Types of fraud and fraud schemes
  • Historical fraud incidents and their impact
  • Building a business case for EFMS

 

Fraud Risk Assessment and Mitigation

  • Identifying fraud risks and vulnerabilities
  • Conducting a fraud risk assessment
  • Strategies for fraud risk mitigation
  • Fraud prevention vs. fraud detection

 

Implementing an EFMS Framework

  • EFMS components and architecture
  • Data collection and integration
  • Rules-based and anomaly-based detection
  • Case management and investigation workflows

 

Day 4: Advanced Fraud Detection Techniques

  • Data analytics and machine learning in fraud detection
  • Behavioural analytics and pattern recognition
  • Real-time monitoring and alerting
  • Cross-channel fraud detection

 

Legal and Ethical Aspects of Fraud Management

  • Regulatory compliance in fraud management
  • Data privacy and confidentiality
  • Reporting and documentation of fraud incidents
  • Case studies on legal and ethical issues in fraud management

 

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