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6 AI Solutions Every Asset Manager Needs

The Asset Management industry is undergoing the most dramatic change in its history.  Long-standing pressure points – and emerging revolutions – are converging to create a unique, once-in-a-generation opportunity for the buy side to harness the power of Artificial Intelligence and Machine Learning (AI/ML).  In addition, the widespread adoption of emerging AI/ML technologies combined with the increasing ubiquity of data has presented a unique opportunity for asset managers to accelerate their use of predictive analytics.


As the buy side faces the most challenging period in its history, AI and Machine Learning are being used today to counter the onslaught of obstacles – and help those same firms achieve significant ROI.

In this new eBook, we highlight six of the top AI solutions in use by asset management firms today:

  • For Chief Investment Officers - Optimizing the use of funds
  • For Portfolio Management - Credit ratings upgrade/downgrade predictions
  • For Trading - Best execution decision support
  • For Operations - Operational failure prediction and remediation
  • For Client Services - Predicting and resolving client churn
  • For Marketing - Targeted marketing and cross-selling
  • 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.
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