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Ebook

Model Risk Management with DataRobot

Effectively managing model risk is critical as more business processes are relying on machine learning models for decision making. This trend has emphasized the importance of model risk management, which in particular 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 machine learning models but also automates the documentation required for model risk management.

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
  • DataRobot's platform makes my work exciting, my job fun, and the results more accurate and timely – it's almost like magic!
    Omair Tariq
    Omair Tariq

    Data Analyst, Symphony Post Acute Network

  • I think we need to take it upon ourselves in the industry to build the predictive models that understand what the needs and wants of our customers are, and go through the whole curation process, become their concierge.
    Oliver Rees
    Oliver Rees

    General Manager – Torque Data at Virgin Australia

  • At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource.
    Akshay Tandon
    Akshay Tandon

    VP of Strategy Analytics, LendingTree

  • We know part of the science and the heavy lifting are intrinsic to the DataRobot technology. Prior to working with DataRobot, the modeling process was more hands-on. Now, the platform has optimized and automated many of the steps, while still leaving us in full control. Without DataRobot, we would need to add two full-time staffers to replace what DataRobot delivers.
    Evariant