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 webcast, 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.