Effectively managing model risk is critical as more and more business processes are relying on predictive machine learning models for decisioning. This trend has emphasized the importance of model risk management, which has become a hot topic in the regulatory and compliance-rich industry of financial services.
With DataRobot, financial institutions now have a tool that will not only automate the building of highly-accurate predictive models, but also automates the documentation required for Model Risk Management.
In addition, DataRobot AI Services provides the banking-specific experience and expertise to help you quickly and easily get up-and-running with your improved model risk management efforts, offering insights and practical support for building and deploying models, creating challenger models for compliance, and automating documentation to streamline your regulatory efforts.
This executive briefing covers:
- The challenges - and need - for effective model risk management in today's regulatory environment
- How an automated process delivers efficiency, consistency, and speed to the model risk management workflow
- The importance of challenger model benchmarking to model risk, and how DataRobot accomplishes it
- An introduction to DataRobot AI Services for Model Risk Management and how they can jumpstart your efforts