About the program
This course provides a structured approach to governing, regulating, and managing risks associated with AI in banking. It focuses on ethical implementation, risk identification, regulatory compliance, and incident management to ensure responsible and resilient AI adoption.
New Giza University CampusWhat You’ll Learn
Design and implement
AI governance frameworks for banking institutions
Apply ethical principles
fairness, and explainability in AI systems
Identify, assess,
and mitigate AI-specific risks
Ensure compliance,
with local and international AI regulations
Manage AI incidents
crises, and recovery processes
Highlights
Comprehensive coverage of AI governance, ethics, risk, and compliance
Strong alignment with banking regulatory and supervisory requirements
Practical frameworks for oversight, monitoring, and reporting
Focus on transparency, accountability, and responsible AI use
End-to-end approach from prevention to incident response and recovery
Modules
AI Governance Framework for Banking
Covers the design of AI governance structures, policies, decision-making processes, and monitoring systems. Focuses on oversight, accountability, and reporting aligned with Module banking regulatory requirements.
Ethical AI Implementation
Addresses ethical frameworks, bias detection and mitigation, transparency, explainability, and accountability. Enables organizations to embed fairness and trust Module across AI-driven banking operations.
Risk Management Framework
Focuses on identifying AI-specific technical, operational, and business risks. Covers risk assessment methods, mitigation strategies, monitoring systems, and response procedures.
Compliance and Regulatory Requirements
Explains how to implement local and international AI regulations, establish audit and Module documentation frameworks, and develop compliance monitoring and reporting systems.
Incident Response and Crisis Management
Covers AI incident response planning, crisis management, communication strategies, recovery procedures, and continuous improvement following AI-related incidents.