Advancing model risk management (MRM) in financial institutions requires adapting to evolving definitions and applications of models. Increased data, use cases, and capabilities burden business models from anti-money laundering to MRM tools. Discrepancies arise due to varying definitions and applications of models across organizations and evolving regulatory standards. Effective governance, targeted questioning for fairness in AI models, and robust MRM processes are essential. Common challenges include human error, demand for transparency, regulatory compliance, and fast-paced business growth. Solutions include well-documented processes, frequent validation, and technology adoption to handle complex models and regulatory scrutiny.

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