Webinar: Model Risk Management with Automated Machine Learning
Thursday, March 29, 1 pm ET/ 10 am PT
Model Risk Management has recently become a very hot topic in regulatory and compliance-rich industries. But traditional model development methods are time-consuming, tedious, and subject to user error and bias.
Automated Machine Learning offers a much more robust framework for managing and minimizing model risk than traditional manual modeling. It not only automates the building of highly-accurate predictive models, but also automates the documentation required for Model Risk Management.
- The tools that Automated Machine Learning (AML) provides to optimize and accelerate your model risk management framework.
- How AML increases the efficiency of your model development and validation processes, while also further aligning modeling and validation processes to regulatory expectations for model risk management.
- How AML reduces model risk, while developing cutting-edge machine learning models.
- How AML automates the necessary compliance documentation process with the click of a button.
Seph Mard - Head of Model Validation, DataRobot
As the head of Model Validation at DataRobot, Seph is responsible for model risk management, model validation, and model governance products, as well as services engagements. Seph is leading the initiative to bring AI-driven solutions into the model risk management industry.