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White Paper

Advancing Financial Services Models Beyond GLMs

Back in the 1990s, the financial services sector adopted generalized linear models (GLMs) because of their accuracy and the increasing complexity of decision-making. But GLMs suffer from several disadvantages. Specifically, they can be resource-intensive and time-consuming to build. They cannot work with missing values, and they require data to be collected from rigorously conducted experiments.


Enter automated machine learning and DataRobot’s automated machine learning platform. Our solution not only surmounts these obstacles but also provides more accurate, human-friendly explanations for how it uses the data, the patterns found in the data, and the reasons for a specific decision or prediction.

Read our white paper Advancing Financial Services Models Beyond GLMs , where we cover such topics as:

  • What is a GLM and how this modeling technique was not designed for the banking or insurance industries
  • How automated machine learning deals with missing values while also handling outliers in data
  • How machine learning deals with the non-linear impact of socio-economic features that are an important driver of both financial risk and marketing activity
  • 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.