Ortec Finance Launches a New Standard in Strategic Asset Allocation Powered by Scenario-Based Machine Learning

Designed for insurers, asset managers, pension funds, and other long-term investors. In a world defined by volatility, persistent macro uncertainty and ever more complex investor objectives, traditional optimization approaches are increasingly outdated

Ortec Finance announces the launch of GLASS PRISM, a targeted Strategic Asset Allocation (SAA) optimization tool powered by its Scenario-Based Machine Learning (SBML) methodology. This marks a major evolution in how institutional investors design long-term investment strategy.

GLASS PRISM moves beyond static assumptions and linear relationships by applying machine learning within a forward-looking, multi-scenario framework, enabling investors to design Strategic Asset Allocations that are more adaptive, more robust, and better aligned with their objectives.

— Ortec Finance today announces the launch of GLASS PRISM, a targeted Strategic Asset Allocation (SAA) optimization tool powered by its Scenario-Based Machine Learning (SBML) methodology – marking a major evolution in how institutional investors design long-term investment strategy.

In a world defined by volatility, persistent macro uncertainty and ever more complex investor objectives, traditional optimization approaches are increasingly outdated. GLASS PRISM moves beyond static assumptions and linear relationships by applying machine learning within a forward-looking, multi-scenario framework, enabling investors to design Strategic Asset Allocations that are more adaptive, more robust, and better aligned with their objectives.

“Strategic asset allocation is the most important investment decision institutions make, yet many tools still lack a targeted approach to optimizing SAA’s,” said Linda Hooft, Managing Director Insurance Strategy at Ortec Finance. “GLASS PRISM fundamentally changes that. By combining the accuracy of brute-force methods with the efficiency of advanced optimization techniques, our clients can optimize asset portfolios based on any objective or constraint required.”

Unlike conventional mean-variance models, GLASS PRISM:

• Insurers can directly target the balance sheet metrics that matter most within the constraints under which they operate
• Non-linear and multi-period objectives and constraints are handled natively, without proxies
• A set of SAAs is produced that best satisfies institutional objectives, rather than approximating these objectives
• Results are delivered faster, more targeted, and within existing processes

Designed for insurers, asset managers, pension funds, and other long-term investors, GLASS PRISM transforms complex SAA analysis into a scalable, decision-ready framework. By embedding SBML within a dedicated SAA optimization tool, GLASS PRISM transforms what has historically been a highly technical and time-intensive process into a scalable, decision-ready framework.

“Strategic asset allocation is the most important investment decision institutions make, yet many tools still lack a targeted approach to optimizing SAAs,” said Linda Hooft, Managing Director for Insurance Strategy at Ortec Finance. “GLASS PRISM fundamentally changes that. By combining the accuracy of brute-force methods with the efficiency of advanced optimization techniques, our clients can optimize asset portfolios based on any objective or constraint required.”

Unlike conventional mean-variance models, GLASS PRISM:

• Insurers can directly target the balance sheet metrics that matter most—within the constraints under which they operate
• Non-linear and multi-period objectives and constraints are handled natively, without proxies
• A set of SAAs is produced that best satisfies institutional objectives, rather than approximating these objectives
• Results are delivered faster, more targeted, and within existing processes

With GLASS PRISM, Ortec Finance reinforces its leadership in forward-looking risk and return manageme—equippingng institutional investors with the tools needed to build resilient portfolios in an uncertain world.