Mitigating model risk in AI

Advancing a model risk management (MRM) framework for artificial intelligence (AI)/machine learning models at financial institutions

Financial institutions are increasingly leveraging AI and machine learning models to enhance decision-making, customer insights and operational efficiencies. This shift from traditional to AI-driven models introduces unique challenges that require significant updates to existing MRM frameworks.

This paper highlights the key AI/machine learning risks and risk cultures between Silicon Valley – the purveyors of AI/machine learning technology – and the financial services industry, a regulated industry with a mature model risk practice. The paper explores the nature of AI/machine learning models and the nuances of MRM as applicable to financial services, and follows with a discussion about AI/machine learning risk across various stages of the model lifecycle. The aim of the paper is to provide practical guidelines to integrate AI/machine learning capabilities into MRM frameworks, drawing on best practices from larger institutions while considering the resource constraints typical of smaller institutions.

Download the Chartis report, Mitigating model risk in AI: advancing an MRM framework for AI/machine learning models at financial institutions

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