Traditional portfolio optimization techniques often fall short when dealing with multiple objectives and complex, non-linear constraints—especially in the insurance sector where risk capital requirements add an extra layer of complexity.
In this Insurance Asset Risk and Ortec Finance webinar we will explore how Scenario-Based Machine Learning (SBML) can redefine the optimization process by leveraging stochastic scenarios and advanced machine learning techniques.
Ashish Doshi
Senior Business Specialist,
Ortec Finance
Iain Ritchie
Insurance Solutions,
M&G
Vincent Huck (Moderator)
Editor
Insurance Asset Risk
Smarter portfolios: how SBML beats traditional optimization
3D optimization: balancing multiple objectives with complex constraints
Trust in AI: transparency and validation with GLASS
Clearer decisions: making asset allocation easy to explain
What’s next: SBML coming soon as a GLASS module
Channels:Private market
