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

 

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

 

Why SBML

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