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Managing Risk of Machine Learning Models

Financial Institutions Manage Many Complex and Integrated Areas of Risk, and of them management of model risk is critical so as to meet regulatory requirements and to protect institutions from operational and reputational risk. Some of the model risks being – Variety of ML environments to be managed, Fairness issues in model predictions, Explainable AI/ML, Drifting models, Model quality, Difficult to get a single view of governance in production. IBM Watson OpenScale offers customers the ability to validate and monitor models pre- and post-deployment to help their organizations comply with regulation and mitigate business risk. This session will give an understanding of how OpenScale can be used to understand and mitigate the risk of the machine learning models in both pre-production and production environments.