Ortec Finance’s Scenario-Based Machine Learning (SBML) combines AI with stochastic ALM modelling in our GLASS platform to help insurers meet real-world objectives faster and more precisely.

SBML naturally accounts for capital, solvency, ESG, and liquidity constraints—delivering portfolios that perform better under real-world conditions.

Featured Resources

1. Optimizing Insurance Portfolios with SBML: Ortec Finance & M&G Investments

See how M&G Investments partnered with Ortec Finance to pilot SBML within GLASS—optimizing portfolios under complex regulatory constraints and uncovering more efficient results than traditional methods. 

Download Client Story

 

Scenario-Based Machine Learning

2. Unlock the Next Dimension of Portfolio Optimization

Discover how 3D SBML optimization, developed with M&G Investments, delivers superior portfolios by balancing multiple insurer objectives while maintaining full transparency.

Download Client Story

3. How AI Can Help Manage Insurance Portfolios

Learn how AI-driven scenario analysis helps insurers uncover high-performing portfolios traditional methods miss—combining realism, speed, and explainability.

Download the whitepaper

 

How AI can help manage insurance portfolio whitepaper cover

Why SBML

  • Handles complex, non-linear regulatory constraints
  • Optimizes for insurer-specific metrics
  • Enables rapid iteration and transparent decision-making
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