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The application of model risk management is becoming ever more important for banks as the reliance on models to meet regulatory challenges and improve business performance increases. As banks become more dependent on models for pricing, risk, capital, stress testing and performance optimisation ñ their boards are demanding a clearer view of how much risk these models entail and the implications for the banks financial position. This podcast provides a critical understanding of opportunities and challenges of MRM across capital planning, balance sheet management and multiple risk exposure and advancing technology to prepare for market changes. Key questions our panel of experts will address include: - What impact is the growth in financial models having on banks and what are the emerging risks? - What are some of the challenges and best practices that have emerged with the development, monitoring and maintenance of new models? - To what extent have regulatory initiatives such as SR 11-7 and TRIM improved standards? - Network review vs independent model review: How are leading banks managing the interconnected risk? - What are the recent advancements in machine learning interpretability techniques and what are the main considerations for its adoption? Whitepaper Machine Learning Model Governance: https://www.sas.com/gms/redirect.jsp?detail=GMS116548_160909