- Gary Brackenridge, Global Head of Research and Development, North America, Linedata
- Philitsa Hanson, Head of Transformation, Linedata
- Gordon Liu, Executive Vice-President and US Head of Global Risk Analytics, HSBC
- Jiahao Sun, Lead Artificial Intelligence Engineer, RBC Wealth Management
- Moderator: Victor Anderson, Editor-in-Chief, WatersTechnology
Increasingly, buy-side firms are accepting that machine learning and analytics offer the potential to make more insightful and accurate front-office decisions, manage operational and compliance risk more precisely, and streamline back-office processing.
Successfully deploying machine learning and data analytics is an enticing proposition, but it is not without its technology, business strategy and operational challenges. Organizations struggle to understand how their data can be used to solve problems—internal expertise may be limited. There is no single reference model to follow that will gain the insights necessary to make impactful decisions.
A panel of experts discusses these challenges, current trends and what steps to begin to leverage and adopt machine learning technology and advanced data analytics. Among the topics discussed:
- Necessary functional ingredients for machine learning/advanced data analytics tools to be useful to end-user firms
- How buy-side firms make business cases for developing and adopting such technologies
- How buy-side firms should develop such capabilities, and what to look for in an external partner to assist this development.