This session takes a practical view related to the successful incorporation of Liquidity Risk and Machine Learning for Replicating Portfolios within ERM/ALM systems. While regulatory requirements are important considerations, the key drivers are to transform the business processes by providing actionable risk information to key business stakeholders. Participants will take away important lesson learned related to determining the appropriate implementation scope, data requirements and challenges, modeling choices and working across multiple departments and stakeholders to deliver tangible business benefits within a limited implementation timeframe. The handout will include functional architecture diagrams, modeling and methodology descriptions and examples of key deliverables to stakeholders.
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