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Model risk management: building trust and governance

As organisations increasingly rely on models that cover a wide range of business functions, there is an increasing need to create and maintain a comprehensive model inventory for enhanced collaboration and regulatory compliance across multiple regions and geographies. The adoption of AI has also increased the need for organisations to manage risk associated with the use of artificial intelligence (AI) models to ensure you can trust them to perform as intended

The panel

  • John Thomas, Distinguished Engineer, and Director, Data and Artificial Intelligence Expert Labs, IBM
  • Sanja Stefanovic, Model Risk Vice-President, Citi
  • Hariom Tatsat, Vice-President, Barclays
  • Moderated by: Marc Cassagnol, Product Manager, Governance, Risk Management and Compliance, IBM

As organisations increasingly rely on models that cover a wide range of business functions, there is an increasing need to create and maintain a comprehensive model inventory for enhanced collaboration and regulatory compliance across multiple regions and geographies. The adoption of AI has also increased the need for organisations to manage risk associated with the use of artificial intelligence (AI) models to ensure you can trust them to perform as intended.

Key topics discussed:

  • Creating and maintaining a comprehensive model inventory
  • Supporting compliance with a variety of model-focused regulations across multiple regions and jurisdictions
  • Validating pre-production AI models and monitoring production AI models
  • The state of model usage and model risk across the enterprise.

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