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Five Automated Machine Learning Solutions for P&C Insurance

In an insurance marketplace where the average P&C combined ratio is hovering close to 99 points, a single point improvement can yield a dramatic increase in profitability. AI and automated machine learning bring five new dynamics to P&C insurance operations that empower companies to shed previous constraints and break out of the pack to pursue substantial improvements in loss and combined ratios.

Read our eBook, Five Automated Machine Learning Solutions for P&C Insurance, to learn about the five ways that P&C insurance companies are taking advantage of AI and automated machine learning, including:

  1. Rapid product development with dynamic pricing
  2. Individually developed loss predictions for claims, pricing, and reserving
  3.  Distribution optimization
  4. Automated underwriting and marketing triage
  5. Underwriting risk portfolio optimization

Learn about the extraordinary returns that enterprises are seeing from their AI projects.

  • 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