The 4th Annual Advanced Model Risk USA focuses on optimizing model risk management strategies, enhancing compliance with AI regulations, and addressing challenges in the validation and governance of AI models.
Topics
- Optimizing model risk management strategies for compliance, efficiency, and AI integration
- Addressing overfitting in AI/ML: effective detection, mitigation, and implementation techniques
- Evaluating global, regional, and state-level AI/ML regulations and their effects on model risk management
- Enhancing model governance to detect credit risk trends early and ensure board accountability
- Refining financial crime models for adaptability to fraud patterns and regulatory changes
- Managing data practices for consistent and accurate risk assessment, addressing stress testing gaps
- Integrating automation into risk identification and monitoring processes
- Developing strategies to mitigate risks such as model hallucinations and bias in AI models
- Analyzing the impact of geopolitical events on financial sectors and model risk management
- Identifying and managing qualitative and hybrid risks in model lifecycle management
- Enhancing model validation efficiency through automation and risk-tier categorization
- Optimizing performance metrics and sampling for anti-money laundering (AML) and sanctions screening
- Reviewing governance practices for validating generative AI models
Who should Attend
- Model risk management professionals
- Financial and regulatory compliance experts
- AI and machine learning researchers
- Credit risk managers and analysts
- Compliance officers and risk managers in financial institutions
- Professionals from small and large banks integrating AI applications
- Experts focused on enhancing AI model governance and validation practices
