AI Solutions for Investment Banking

AI Solutions for Investment Banking

The level of interest in artificial intelligence (AI) technologies across investment banking is unprecedented. Investment banks can take advantage of AI and machine learning to increase revenue and drastically improve efficiency across areas from research to trading. But, where to begin?

In this live webinar, Peter Simon, a Data Scientist at DataRobot with over 20 years’ securities industry experience will discuss key high-value areas in which to deploy AI solutions in investment banks. Register to learn how some of the world’s largest investment banks are leveraging Automated Machine Learning to build and maintain competitive advantage across their businesses.

AI Solutions for Investment Banking

Speaker

Peter Simon
Peter Simon

Senior Data Scientist, 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