Combating Financial Fraud

A comprehensive foundational program designed to provide participants with a solid understanding of the nature of financial fraud, its various forms, detection methodologies, and preventive strategies. The program emphasizes the practical application of emerging technologies—including artificial intelligence (AI), data analytics, and blockchain—to strengthen enterprise-wide financial fraud prevention and detection frameworks.

Duration: 3 Days
Training Hours: 18 Training Hours
Target Audience: Finance professionals, compliance officers, internal auditors, risk managers and risk management staff, legal advisors, and professionals new to fraud prevention and financial crime compliance.
Delivery Mode: In-person / Live Online / Hybrid

Detailed Learning Objectives

By the end of the program, participants will be able to:

• Understand the classification of financial fraud schemes based on the Association of Certified Fraud Examiners (ACFE) Fraud Tree and the Fraud Triangle model.
• Develop the skills required to identify early warning signs of fraud through behavioral indicators, transactional anomalies, and data analysis.
• Design and implement effective fraud prevention strategies, including internal controls, segregation of duties, fraud risk indicators, and governance measures.
• Understand the legal and ethical framework for fraud prevention, including whistleblowing programs and cooperation with regulatory and law enforcement authorities.
• Leverage artificial intelligence (AI), blockchain technologies, and advanced data analytics to enhance automated fraud detection and prevention capabilities.

Key Topics

• Introduction to Financial Fraud: Types of financial fraud, the Fraud Triangle, the ACFE Fraud Tree, and the organizational and economic impact of fraud.
• Early Fraud Detection: Fraud red flags, fraud risk assessments, anomaly detection, and data-driven fraud analytics.
• Fraud Prevention Strategies: Internal control frameworks, Know Your Customer (KYC), Anti-Money Laundering (AML) controls, whistleblowing programs, and fraud governance.
• Legal and Regulatory Considerations: The Saudi legal and regulatory framework, fraud case management, evidence preservation, and coordination with competent authorities.
• Technology in Fraud Prevention: Applications of artificial intelligence, blockchain, and automated fraud management platforms for proactive fraud detection and risk mitigation.