The Road to Successful CECL Compliance with Automated Machine Learning

The Road to Successful CECL Compliance with Automated Machine Learning

The new Current Expected Credit Loss (CECL) accounting standard is expected to vastly increase costs associated with loan provisioning and loan loss reserve processes. To ensure compliance, banks of all sizes will need to develop accurate and reasonable loan loss forecasts using modeling methods, which poses a serious operational challenge.


On this webinar, we discuss CECL and provide a holistic roadmap for how banks can successfully use automated machine learning to quickly and cost effectively build highly accurate and transparent loss forecasting models for CECL compliance.

The Road to Successful CECL Compliance with Automated Machine Learning

You’ll Discover:

  • An overview of CECL and how banks can build and maintain a compliant CECL program
  • How to build highly accurate expected credit loss models, including dual-risk rating models (PD/LGD)
  • How to automatically generate industry standard compliance documentation with the click of a button
  • How to maximize transparency while ensuring adaptability and scalability with Automated Machine Learning


Seph Mard

Head of Model Risk, DataRobot

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

    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

  • DataRobot allows us to understand the data that’s being fed into our models without blindly feeding whatever we get into our system. DataRobot makes my team very effective.
    Deena Narayanaswamy
    Deena Narayanaswamy

    Head of Data Insights, Avant

  • 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.