Cybersecurity Fundamentals for AI-Driven Fraud Detection

This training course is delivered through instructor-led sessions, supported by real-world examples and conceptual explanations. It offers a balanced mix of cybersecurity fundamentals and AI system risks, presented in a format accessible to both technical and non-technical professionals. No programming or AI development experience is required.

By the end of this Cybersecurity Fundamentals for AI-Driven Fraud Detection training course, participants will be able to:

• Understand the intersection of cybersecurity and AI in fraud detection
• Identify vulnerabilities in AI-powered fraud detection systems
• Apply key cybersecurity principles to protect AI data, models, and infrastructure
• Recognise risks such as adversarial attacks and data poisoning
• Implement governance and risk management practices to secure AI environments

This Gulf Rowad Cybersecurity Fundamentals for AI-Driven Fraud Detection training course is designed for professionals working at the intersection of cybersecurity, fraud prevention, and digital transformation, including:

• Cybersecurity and IT risk professionals
• Fraud detection and investigation teams using AI systems
• Data protection officers and compliance managers
• Risk managers and audit professionals
• Technical leads implementing AI-enabled fraud platforms

Organisational Impact

By attending this Cybersecurity Fundamentals for AI-Driven Fraud Detection training course, organisations will be able to:

• Strengthen the security posture of AI-driven fraud detection systems
• Reduce the risk of data breaches, adversarial attacks, and system manipulation
• Align AI fraud detection with cybersecurity and compliance frameworks
• Build greater trust in AI tools used for fraud detection and risk assessment
• Improve collaboration between fraud, cybersecurity, and data science teams

Personal Impact

Participants will gain:

• A working knowledge of cybersecurity concepts relevant to AI and fraud detection
• Insight into securing data pipelines, AI models, and detection algorithms
• Awareness of cyber threats specific to AI systems in fraud prevention
• Skills to assess and mitigate AI-related cybersecurity risks
• Confidence to contribute to secure design and implementation of AI fraud platforms