The 6th 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.
Key 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
