Ortec Finance has announced the launch of GLASS PRISM, a Strategic Asset Allocation (SAA) optimisation tool powered by its Scenario-Based Machine Learning (SBML) methodology, designed to help insurers and other institutional investors better align investment strategy with balance sheet objectives.
GLASS PRISM allows insurers to move beyond traditional mean-variance models, applying machine learning across multiple forward-looking scenarios to design SAAs that are adaptive, robust, and tailored to institutional requirements.
The tool enables insurers to target critical balance sheet metrics directly, manage non-linear and multi-period objectives natively, and generate SAAs that satisfy institutional objectives without approximation.
Results are delivered quickly, within existing operational processes, allowing insurers to integrate SAA insights seamlessly into risk and capital management workflows.
Linda Hooft, Managing Director Insurance Strategy at Ortec Finance, said, “Strategic asset allocation is the most important investment decision institutions make, yet many tools still lack a targeted approach to optimising SAA’s. GLASS PRISM fundamentally changes that. By combining the accuracy of brute-force methods with the efficiency of advanced optimisation techniques, our clients can optimise asset portfolios based on any objective or constraint required.”
Designed for insurers, asset managers, pension funds, and long-term investors, GLASS PRISM embeds SBML in a dedicated, scalable SAA framework, reducing the complexity and time demands traditionally associated with portfolio optimisation.
Ortec Finance said the launch reinforces its position in forward-looking risk and return management, equipping insurers with tools to design resilient portfolios amid market volatility and macro uncertainty.
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