Deploying AI for Success on the Buy Side
Predictive analytics is a key differentiator for asset management firms, but how does an organization do it at scale for business impact? Buyside firms — and the broader financial services industry — are capitalizing on AI advances to predict activities across the front, middle and back office to increase revenue, improve efficiencies, reduce costs — and improve risk management. Some of the hundreds of use cases on the buyside include: asset allocation modeling, fund net flow prediction, economic forecasting, trade failure optimization, investor/advisor churn reduction, improved targeted marketing and cross-selling, and anti-money laundering. However, predictive analytics can be difficult to deploy successfully. Fortunately, artificial intelligence (AI) has progressed to the point where predictive analytics can be self-creating needing only your own data and experience to build world-class predictive models. In this session, you will see AI in action, and learn how asset managers are using AI and machine learning (ML) to build and successfully deploy predictive models with measurable business impact.
Session ID: Presentation Type: On-Demand Session (Recorded)
Date / Time: [Content On-Demand] @ On Demand ET (US)
Presented by:DataRobot is the leader in enterprise AI, delivering trusted AI technology and ROI enablement services to global enterprises. DataRobot’s enterprise AI platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models. Click for more details and additional sessions and content.
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