A Fireside Chat with Farmers Insurance

webinar

In this on-demand webinar, Scot Barton, Head of Business Insurance R&D, provides an overview of how Farmers Insurance created a sustainable, cost-effective, and customer-centric predictive analytics strategy through machine learning automation.

Satadru Sengupta, General Manager of Insurance at DataRobot, then reviews the full spectrum of use cases that DataRobot clients are currently solving with machine learning automation – and deliver a demo.

You'll discover:

  • The critical aspects of predictive analytics
  • The predictive analytics challenges that drove Farmers to consider machine learning
  • How machine learning automation helped Farmers to overcome these challenges

Speakers

Scot Barton

Head of Business Insurance R&D, Farmers Insurance;

Satadru Sengupta

General Manager - Insurance, 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.
    Evariant